Version
3.4.0
Version 3.4.0
November 2019
Technical Overview
Atoll 3.4.0 Technical Overview
Table of Contents
1
Introduction............................................................................................................................. 21
Supported Wireless Technologies ..................................................................................... 21
Supported Operating Systems ........................................................................................... 21
Supported operating systems for Atoll 64-bit ............................................................. 21
Supported operating systems for Atoll 32-bit ............................................................. 21
Supported Database Management Systems ..................................................................... 22
Scalable Installation Configurations.................................................................................. 22
Standalone Configuration ........................................................................................... 22
Multi-user Thick Client Configuration ......................................................................... 22
Multi-user Thin Client Configuration ........................................................................... 22
Multi-user Cloud-based Configuration ........................................................................ 23
Recommended Hardware and Software ........................................................................... 23
Modular Architecture ........................................................................................................ 24
2
Atoll Core Features .................................................................................................................. 26
User Interface.................................................................................................................... 26
2.1.1
Menus ......................................................................................................................... 27
2.1.2
Toolbars ...................................................................................................................... 27
2.1.3
Explorer Windows ....................................................................................................... 27
2.1.4
Map Window .............................................................................................................. 29
2.1.5
Data Tables ................................................................................................................. 30
2.1.6
Panoramic Window .................................................................................................... 30
2.1.7
Legend Window .......................................................................................................... 31
2.1.8
Event Viewer Window ................................................................................................. 31
2.1.9
Favourite Views Window ............................................................................................ 31
2.1.10 Other Windows ........................................................................................................... 32
Geographic Information System (GIS) ............................................................................... 32
2.2.1
High-performance Display .......................................................................................... 32
2.2.2
Multi-resolution Geographic Database ....................................................................... 33
2.2.3
Supported Geo Data Types and File Formats .............................................................. 33
2.2.4
Terrain Elevation Data ................................................................................................ 34
2.2.5
Clutter Class Data ....................................................................................................... 35
2.2.6
Clutter Height Data ..................................................................................................... 36
2.2.7
Traffic Data ................................................................................................................. 36
Raster Traffic Data ...................................................................................................... 36
Vector Traffic Data...................................................................................................... 37
Live Traffic Data .......................................................................................................... 37
Traffic Density Data .................................................................................................... 38
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Atoll 3.4.0 Technical Overview
Fixed Subscribers......................................................................................................... 38
Multi-layer Traffic Data .............................................................................................. 39
Cumulated Traffic Maps ............................................................................................. 39
2.2.8
2D and 3D Vector Data ............................................................................................... 39
2.2.9
Population Data .......................................................................................................... 40
2.2.10 Online Maps ................................................................................................................ 41
2.2.11 Web Map Services ...................................................................................................... 41
2.2.12 Images ........................................................................................................................ 41
2.2.13 Text Data .................................................................................................................... 42
2.2.14 Other Data Types ........................................................................................................ 42
2.2.15 Working Zones ............................................................................................................ 43
2.2.16 Integrated Cartography Editors .................................................................................. 43
Vector Data Editor ...................................................................................................... 43
Clutter Data Editor ...................................................................................................... 43
Traffic Data Editor ...................................................................................................... 44
2.2.17 Worldwide Coordinate Systems Database .................................................................. 44
2.2.18 Units............................................................................................................................ 44
Calculation and Memory Management ............................................................................ 45
Propagation Models .......................................................................................................... 46
2.4.1
Integrated Propagation Model Library ....................................................................... 46
Aster Propagation Model ............................................................................................ 46
CrossWave Propagation Model .................................................................................. 48
Standard Propagation Model (SPM) ........................................................................... 49
3GPP 38.900 Propagation Model................................................................................ 49
Okumura-Hata and Cost-Hata Propagation Models ................................................... 50
Sakagami Extended Propagation Model..................................................................... 50
Erceg-Greenstein Propagation Model ......................................................................... 50
ITU 1546 Propagation Model ...................................................................................... 50
ITU 529 Propagation Model ........................................................................................ 50
ITU 526 Propagation Model ........................................................................................ 50
ITU 1812 Propagation Model ...................................................................................... 50
ITU 452 Propagation Model ........................................................................................ 50
ITU 370 Propagation Model ........................................................................................ 51
Longley-Rice Propagation Model ................................................................................ 51
2.4.2
Optimised Multi-resolution Path Loss Calculations ..................................................... 51
2.4.3
Open Interface to External Propagation Models ........................................................ 52
2.4.4
Propagation Model Calibration .................................................................................. 52
2.4.5
Real-time Transmitter-to-Point Profile Prediction ...................................................... 52
2.4.6
Link Budget Tool ......................................................................................................... 53
Network Data Management ............................................................................................. 53
2.5.1
© Forsk 2019
Network Data Import and Export ............................................................................... 53
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Atoll 3.4.0 Technical Overview
2.5.2
Network Element Creation and Editing ....................................................................... 54
2.5.3
Network Element Selection ......................................................................................... 54
2.5.4
Network Element Grouping ........................................................................................ 54
2.5.5
Network Element Filtering .......................................................................................... 55
2.5.6
Network Element Sorting ............................................................................................ 56
2.5.7
Network Element Lists ................................................................................................ 56
2.5.8
User Configurations .................................................................................................... 57
Network Lifecycle Management ....................................................................................... 57
Database and Multi-user Management ............................................................................ 59
2.7.1
Customisable Multi-technology Database Model ....................................................... 60
2.7.2
Database Management .............................................................................................. 61
2.7.3
Multi-level Database Management ............................................................................ 62
2.7.4
Multi-Operator RAN Management and RAN Sharing ................................................. 63
2.7.5
Data Modifications History Management .................................................................. 64
User Management ............................................................................................................ 64
Calculation Result Reports and Statistics .......................................................................... 65
2.9.1
Printing ....................................................................................................................... 66
2.9.2
Exporting..................................................................................................................... 66
Distributed Computing and Multi-threading ..................................................................... 66
Scripting and Customisation ............................................................................................. 67
2.11.1 Scripting ...................................................................................................................... 68
2.11.2 Customisation ............................................................................................................. 68
General API ................................................................................................................. 68
Propagation Model API ............................................................................................... 69
3
Atoll Live Features ................................................................................................................... 71
Live Network Data Management in Atoll .......................................................................... 71
Live Network Data Import ................................................................................................. 72
3.3.1
KPI/PM Data Mapping ................................................................................................ 72
3.3.2
KPI/PM Data Import ................................................................................................... 73
3.3.3
UE/Cell/MDT Trace Mapping ...................................................................................... 74
3.3.4
UE/Cell/MDT Trace Import ......................................................................................... 75
3.3.5
Configuration Management Data Import ................................................................... 76
3.3.6
GSM OSS Data Import ................................................................................................. 76
Live Network Data Display and Analysis ........................................................................... 76
3.4.1
KPI Data Tables ........................................................................................................... 76
3.4.2
KPI-Based Sector Display and Best Server Plots .......................................................... 77
3.4.3
UE/Cell/MDT Trace Locations and Density ................................................................. 78
Live Network Data Comparative Analysis ......................................................................... 79
© Forsk 2019
3.5.1
Comparison between Two Sets of Single-Server KPIs .................................................. 79
3.5.2
Comparison between Single-Server KPIs and Predicted Values .................................. 80
3.5.3
Comparison between Multi-Server KPIs and Neighbour Relations ............................. 80
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Atoll 3.4.0 Technical Overview
3.5.4
Comparison between Two Sets of Multi-Server KPIs ................................................... 81
Combined Path Loss Matrices ........................................................................................... 81
Coverage Plots Including Live Network Data .................................................................... 82
3.7.1
KPI Quality Zones ........................................................................................................ 82
3.7.2
UE/Cell/MDT Trace Measurement Plots ..................................................................... 83
3.7.3
UE/Cell/MDT Trace Coverage Plots ............................................................................ 84
3.7.4
Combined Prediction and Measurement Plots ............................................................ 84
3.7.5
Comparison Between UE/Cell/MDT Trace Measurements and Predictions ................ 85
Network Optimisation Using Live Network Data in the ACP ............................................. 85
Prediction and KPI-Based Neighbour Planning.................................................................. 88
3.9.1
Automatic Neighbour Planning Using KPIs ................................................................. 88
3.9.2
Neighbour Importance Calculation Including KPIs ...................................................... 89
3.9.3
Automatic Creation of Black Lists and White Lists (Exceptional Pairs) ....................... 89
Automatic Frequency, PCI, and PRACH Planning Using Live Network Data in the LTE AFP90
Traffic Maps from Live Network Data ............................................................................... 91
4
Antenna and Radio Equipment Features ................................................................................. 94
Antenna Model ................................................................................................................. 94
Antenna Features .............................................................................................................. 94
4.2.1
2D and 3D Antenna Pattern Import ............................................................................ 94
4.2.2
Antenna Selection Assistant........................................................................................ 95
4.2.3
Antenna Pattern Comparison Tool .............................................................................. 95
4.2.4
Antenna Pattern Smoothing ....................................................................................... 96
4.2.5
Antenna-to-Sector Assignment Audit ......................................................................... 96
4.2.6
Antenna Parameter Audit ........................................................................................... 96
Antenna – Sector Configurations ...................................................................................... 96
4.3.1
Single Antenna Configurations ................................................................................... 97
4.3.2
Co-located Multiple Antenna Configurations .............................................................. 97
4.3.3
Geographically Distributed Antenna Configurations .................................................. 98
4.3.4
Multi-beam Antenna Configurations .......................................................................... 99
4.3.5
C-RAN Configurations ............................................................................................... 101
Radio Equipment Model .................................................................................................. 102
5
4.4.1
Transmitter Equipment ............................................................................................. 102
4.4.2
Feeders ..................................................................................................................... 102
4.4.3
Tower Mounted Amplifiers (TMA) ............................................................................ 102
5G NR Features ..................................................................................................................... 103
5G NR Network Model .................................................................................................... 103
© Forsk 2019
5.1.1
Sites .......................................................................................................................... 104
5.1.2
Transmitters.............................................................................................................. 104
5.1.3
Cells........................................................................................................................... 105
5.1.4
Site Templates .......................................................................................................... 106
5.1.5
Repeaters .................................................................................................................. 106
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Atoll 3.4.0 Technical Overview
5G NR Network Parameters ............................................................................................ 107
5.2.1
Frequency Bands and Carriers .................................................................................. 107
5.2.2
Global Network Settings ........................................................................................... 108
5.2.3
Network Layers ......................................................................................................... 108
5.2.4
Schedulers ................................................................................................................. 109
5.2.5
Radio Equipment....................................................................................................... 109
5G NR 3D Beamforming and Massive MIMO .................................................................. 112
5.3.2
3D Beamforming Models .......................................................................................... 113
5.3.3
3D Beam Pattern Generator ..................................................................................... 115
5.3.4
3D Beam Usage Calculation ...................................................................................... 116
5.3.5
Massive MIMO .......................................................................................................... 117
5G NR Carrier Aggregation ............................................................................................. 119
5G NR/LTE Dual Connectivity (EN-DC) ............................................................................. 120
5G NR Traffic Model ........................................................................................................ 120
5.6.1
Services ..................................................................................................................... 121
5.6.2
Terminals .................................................................................................................. 122
5.6.3
Mobility Types ........................................................................................................... 122
5.6.4
User Profiles .............................................................................................................. 122
5.6.5
Traffic Data ............................................................................................................... 123
5G NR Monte Carlo Simulations ...................................................................................... 123
5.7.1
Generation of Realistic User Distributions ................................................................ 123
5.7.2
Scheduling and Radio Resource Management.......................................................... 123
5.7.3
Monte Carlo Simulation Management ..................................................................... 125
5.7.4
Simulation Graphical Analysis ................................................................................... 126
Graphical Display: Mobile Activity Status ................................................................. 126
Graphical Display: Throughput ................................................................................. 127
Graphical Display: Mobile Connection Status ........................................................... 127
Individual Mobile Results Graphical Display ............................................................. 128
5.7.5
Simulation Reports .................................................................................................... 128
Reports of a Single Simulation .................................................................................. 128
Reports of a Group of Simulations ............................................................................ 129
5.7.6
Updating Cell Loads .................................................................................................. 130
5.7.7
Exporting Results ...................................................................................................... 130
5G NR Coverage Predictions............................................................................................ 130
© Forsk 2019
5.8.1
Coverage Prediction Calculation and Management ................................................. 130
5.8.2
Coverage Prediction Types ........................................................................................ 131
5.8.3
Coverage Prediction Reports ..................................................................................... 138
5.8.4
Coverage Prediction Comparison .............................................................................. 138
5.8.5
Coverage Prediction Export....................................................................................... 138
5.8.6
Point Analysis Tool .................................................................................................... 139
5.8.7
Multi-Point Analysis .................................................................................................. 139
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Atoll 3.4.0 Technical Overview
5G NR Neighbour Planning ............................................................................................. 140
5.9.1
Automatic Neighbour Allocation .............................................................................. 141
5.9.2
Graphical Neighbour Plan Editing ............................................................................. 141
5.9.3
Neighbour Consistency Check Tool ........................................................................... 142
5G NR Automatic Physical Cell ID and PRACH RSI Planning ............................................ 142
5.10.1 AFP Cost Components ............................................................................................... 143
5.10.2 Automatic Physical Cell ID Planning .......................................................................... 144
5.10.3 Automatic PRACH Root Sequence Index Planning .................................................... 145
5.10.1 Physical Cell ID and PRACH Root Sequence Index Plan Analysis ............................... 146
Cell Parameter Search Tool ....................................................................................... 146
Cell Parameter Display on Map ................................................................................ 147
5G NR Automatic Cell Planning ....................................................................................... 147
5G NR Co-planning With Other Radio Access Technologies ............................................ 148
6
LTE/LTE-Advanced Features .................................................................................................. 149
LTE/LTE-Advanced Network Model ................................................................................. 149
6.2.2
Sites .......................................................................................................................... 150
6.2.3
Transmitters.............................................................................................................. 150
6.2.4
Cells........................................................................................................................... 151
6.2.5
Site Templates .......................................................................................................... 152
6.2.6
Repeaters .................................................................................................................. 152
6.2.7
Relay Nodes .............................................................................................................. 153
LTE/LTE-Advanced Network Parameters......................................................................... 154
6.3.1
Frequency Bands and Carriers .................................................................................. 154
6.3.2
Global Network Settings ........................................................................................... 155
6.3.3
Network Layers ......................................................................................................... 155
6.3.4
Schedulers ................................................................................................................. 156
6.3.5
UE Categories ........................................................................................................... 156
6.3.6
Radio Equipment....................................................................................................... 156
LTE/LTE-Advanced 3D Beamforming and Massive MIMO .............................................. 159
6.4.2
3D Beamforming Models .......................................................................................... 160
6.4.3
3D Beam Pattern Generator ..................................................................................... 162
6.4.4
3D Beam Usage Calculation ...................................................................................... 163
6.4.5
Massive MIMO .......................................................................................................... 164
LTE/LTE-Advanced Carrier Aggregation .......................................................................... 166
LTE/LTE-Advanced Coordinated Multipoint Operation (CoMP) ...................................... 167
LTE/LTE-Advanced Inter-Cell Interference Coordination (ICIC) ........................................ 168
LTE/LTE-Advanced Enhanced ICIC (eICIC) ........................................................................ 169
LTE/LTE-Advanced License-Assisted Access (LAA) ........................................................... 170
LTE/LTE-Advanced Traffic Model .................................................................................... 170
6.10.2 Services ..................................................................................................................... 171
Voice over LTE (VoLTE) Service .................................................................................. 172
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Atoll 3.4.0 Technical Overview
6.10.3 Terminals .................................................................................................................. 172
6.10.4 Mobility Types ........................................................................................................... 173
6.10.5 User Profiles .............................................................................................................. 173
6.10.6 Traffic Data ............................................................................................................... 174
LTE/LTE-Advanced Monte Carlo Simulations .................................................................. 174
6.11.1 Generation of Realistic User Distributions ................................................................ 174
6.11.2 Scheduling and Radio Resource Management.......................................................... 174
6.11.3 Monte Carlo Simulation Management ..................................................................... 176
6.11.4 Simulation Graphical Analysis ................................................................................... 177
Graphical Display: Mobile Activity Status ................................................................. 177
Graphical Display: Throughput ................................................................................. 178
Graphical Display: Mobile Connection Status ........................................................... 178
Individual Mobile Results Graphical Display ............................................................. 179
6.11.5 Simulation Reports .................................................................................................... 179
Reports of a Single Simulation .................................................................................. 179
Reports of a Group of Simulations ............................................................................ 180
6.11.6 Updating Cell Loads .................................................................................................. 181
6.11.7 Exporting Results ...................................................................................................... 181
LTE/LTE-Advanced Coverage Predictions ........................................................................ 181
6.12.1 Coverage Prediction Calculation and Management ................................................. 181
6.12.2 Coverage Prediction Types ........................................................................................ 182
6.12.3 Coverage Prediction Reports ..................................................................................... 195
6.12.4 Coverage Prediction Comparison .............................................................................. 195
6.12.5 Coverage Prediction Export....................................................................................... 196
6.12.6 Point Analysis Tool .................................................................................................... 196
6.12.7 Multi-Point Analysis .................................................................................................. 197
LTE/LTE-Advanced Neighbour Planning .......................................................................... 198
6.13.1 Automatic Neighbour Allocation .............................................................................. 198
6.13.2 Graphical Neighbour Plan Editing ............................................................................. 199
6.13.3 Neighbour Consistency Check Tool ........................................................................... 200
LTE/LTE-Advanced Automatic Frequency, Physical Cell ID, and PRACH RSI Planning...... 200
6.14.2 AFP Cost Components ............................................................................................... 201
6.14.3 Automatic Physical Cell ID Planning .......................................................................... 202
6.14.4 Automatic PRACH Root Sequence Index Planning .................................................... 203
6.14.5 Automatic Frequency Planning ................................................................................. 204
6.14.6 Frequency, Physical Cell ID, and PRACH Root Sequence Index Plan Analysis ............ 205
Cell Parameter Search Tool ....................................................................................... 205
Cell Parameter Display on Map ................................................................................ 205
Cell Identifier Collision Zones Prediction ................................................................... 206
LTE/LTE-Advanced Automatic Cell Planning.................................................................... 206
LTE/LTE-Advanced Co-planning With Other Radio Access Technologies ......................... 207
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Atoll 3.4.0 Technical Overview
7
NB-IoT Features ..................................................................................................................... 208
NB-IoT Network Model.................................................................................................... 208
7.2.2
Sites .......................................................................................................................... 208
7.2.3
Transmitters.............................................................................................................. 209
7.2.4
Cells........................................................................................................................... 210
7.2.5
Site Templates .......................................................................................................... 211
7.2.6
Repeaters .................................................................................................................. 211
NB-IoT Network Parameters ........................................................................................... 212
7.3.1
Frequency Bands and Carriers .................................................................................. 212
7.3.2
Global Network Settings ........................................................................................... 213
7.3.3
Network Layers ......................................................................................................... 213
7.3.4
UE categories ............................................................................................................ 214
7.3.5
Radio Equipment....................................................................................................... 214
NB-IoT Multicarrier Operation ........................................................................................ 216
NB-IoT Traffic Model ....................................................................................................... 217
7.5.2
Services ..................................................................................................................... 217
7.5.3
Terminals .................................................................................................................. 218
7.5.4
Mobility Types ........................................................................................................... 219
7.5.5
User Profiles .............................................................................................................. 219
7.5.6
Traffic Data ............................................................................................................... 219
NB-IoT Monte Carlo Simulations ..................................................................................... 220
7.6.1
Generation of Realistic User Distributions ................................................................ 220
7.6.2
Monte Carlo Simulation Management ..................................................................... 220
7.6.3
Simulation Graphical Analysis ................................................................................... 221
Graphical Display: Mobile Activity Status ................................................................. 221
Graphical Display: Mobile Connection Status ........................................................... 222
Individual Mobile Results Graphical Display ............................................................. 222
7.6.4
Simulation Reports .................................................................................................... 222
Reports of a Single Simulation .................................................................................. 222
Reports of a Group of Simulations ............................................................................ 223
7.6.5
Exporting Results ...................................................................................................... 223
NB-IoT Coverage Predictions ........................................................................................... 224
7.7.1
Coverage Prediction Calculation and Management ................................................. 224
7.7.2
Coverage Prediction Types ........................................................................................ 224
7.7.3
Coverage Prediction Reports ..................................................................................... 234
7.7.4
Coverage Prediction Comparison .............................................................................. 234
7.7.5
Coverage Prediction Export....................................................................................... 235
7.7.6
Point Analysis Tool .................................................................................................... 235
7.7.7
Multi-Point Analysis .................................................................................................. 236
NB-IoT Automatic Frequency and Narrowband Physical Cell ID Planning ....................... 237
7.8.2
© Forsk 2019
AFP Cost Components ............................................................................................... 238
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Atoll 3.4.0 Technical Overview
7.8.3
Automatic Narrowband Physical Cell ID Planning .................................................... 239
7.8.4
Automatic Frequency Planning ................................................................................. 240
7.8.5
Frequency and Narrowband Physical Cell ID Plan Analysis ....................................... 240
Cell Parameter Search Tool ....................................................................................... 240
Cell Parameter Display on Map ................................................................................ 241
Cell Identifier Collision Zones Prediction ................................................................... 241
NB-IoT Automatic Cell Planning ...................................................................................... 242
NB-IoT Co-planning With Other Radio Access Technologies ........................................... 242
8
UMTS/HSPA Features ............................................................................................................ 243
UMTS Network Model ..................................................................................................... 243
8.1.1
Sites .......................................................................................................................... 244
8.1.2
Transmitters.............................................................................................................. 244
8.1.3
Cells (R99, HSDPA, HSPA, and HSPA+) ...................................................................... 245
8.1.4
Site Templates .......................................................................................................... 246
8.1.5
Repeaters .................................................................................................................. 246
UMTS Network Configuration Parameters...................................................................... 247
8.2.1
Frequency Bands and Carriers .................................................................................. 247
8.2.2
Global Network Settings ........................................................................................... 247
8.2.3
Network Layers ......................................................................................................... 248
8.2.4
Radio Bearers (R99, HSDPA, and HSUPA) ................................................................. 248
8.2.5
Schedulers ................................................................................................................. 249
8.2.6
UE categories (HSDPA and HSUPA) ........................................................................... 249
8.2.7
Quality Indicators (R99, HSDPA, HSUPA) .................................................................. 249
UMTS Radio Equipment .................................................................................................. 249
8.3.1
Site Equipment .......................................................................................................... 250
8.3.2
Reception Equipment (R99, HSDPA, HSPA, HSPA+) ................................................... 250
UMTS Traffic Model ........................................................................................................ 253
8.4.1
Services ..................................................................................................................... 253
8.4.2
Terminals .................................................................................................................. 254
8.4.3
Mobility Types ........................................................................................................... 255
8.4.4
User Profiles .............................................................................................................. 255
8.4.5
Traffic Data ............................................................................................................... 256
UMTS Monte Carlo Simulations ...................................................................................... 256
8.5.1
Generation of Realistic User Distributions ................................................................ 256
8.5.2
Power Control and Radio Resource Management .................................................... 256
8.5.3
Monte Carlo Simulation Management ..................................................................... 258
8.5.4
Simulation Graphical Analysis ................................................................................... 259
Graphical Display: Mobile Connection Status ........................................................... 259
Individual Mobile Result Graphical Display ............................................................... 260
8.5.5
Simulation Reports .................................................................................................... 260
Reports of a Single Simulation .................................................................................. 261
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Atoll 3.4.0 Technical Overview
Reports of a Group of Simulations ............................................................................ 261
8.5.6
Updating Cell Loads .................................................................................................. 262
8.5.7
Exporting Results ...................................................................................................... 262
UMTS Coverage Predictions ............................................................................................ 262
8.6.1
Coverage Prediction Calculation and Management ................................................. 262
8.6.2
Coverage Prediction Types ........................................................................................ 262
8.6.3
Coverage Prediction Reports ..................................................................................... 267
8.6.4
Coverage Prediction Comparison .............................................................................. 267
8.6.5
Coverage Prediction Export....................................................................................... 268
8.6.6
Point Analysis Tool .................................................................................................... 268
8.6.7
Multi-Point Analysis .................................................................................................. 269
UMTS Neighbour Planning .............................................................................................. 270
8.7.1
Automatic Neighbour Allocation .............................................................................. 270
8.7.2
Graphical Neighbour Plan Editing ............................................................................. 271
8.7.3
Neighbour Consistency Check Tool ........................................................................... 272
UMTS Primary Scrambling Code Planning ...................................................................... 272
8.8.1
Automatic Scrambling Code Planning Tool ............................................................... 272
8.8.2
Scrambling Code Consistency Check Tool ................................................................. 273
8.8.3
Scrambling Code Interference Analysis ..................................................................... 274
UMTS Automatic Cell Planning ....................................................................................... 274
UMTS Co-planning With Other Radio Access Technologies ............................................ 274
9
GSM/GPRS/EDGE Features.................................................................................................... 275
GSM/GPRS/EDGE Network Model .................................................................................. 275
9.1.1
Sites .......................................................................................................................... 276
9.1.2
Transmitters.............................................................................................................. 276
9.1.3
Subcells and TRXs (Transceivers)............................................................................... 277
9.1.4
Site Templates .......................................................................................................... 278
9.1.5
Repeaters .................................................................................................................. 278
GSM/GPRS/EDGE Network Configuration Parameters ................................................... 279
9.2.1
Frequency Bands and Carriers .................................................................................. 279
9.2.2
Global Network Settings ........................................................................................... 280
9.2.3
HCS (Hierarchical Cell Structure) Layers .................................................................... 280
9.2.4
Voice Codec Configuration ........................................................................................ 281
9.2.5
GPRS/EGPRS/EGPRS2 Coding Scheme Configuration................................................ 281
9.2.6
Timeslot Configuration ............................................................................................. 282
9.2.7
TRX Configuration ..................................................................................................... 282
9.2.8
Quality Indicators...................................................................................................... 283
GSM/GPRS/EDGE Radio Equipment ................................................................................ 283
GSM/GPRS/EDGE Traffic Model ...................................................................................... 283
© Forsk 2019
9.4.1
Services ..................................................................................................................... 283
9.4.2
Terminals .................................................................................................................. 284
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Atoll 3.4.0 Technical Overview
9.4.3
Mobility Types ........................................................................................................... 284
9.4.4
User Profiles .............................................................................................................. 284
9.4.5
Traffic Data ............................................................................................................... 285
GMS/GPRS/EDGE Network Capacity Analysis and Dimensioning ................................... 285
GSM/GPRS/EDGE Monte Carlo Simulations .................................................................... 287
9.6.1
Generation of Realistic User Distributions ................................................................ 287
9.6.2
Scheduling and Radio Resource Management.......................................................... 288
9.6.3
Monte Carlo Simulation Management ..................................................................... 289
9.6.4
Simulation Graphical Analysis ................................................................................... 290
Graphical Display: Mobile Connection Status ........................................................... 290
Graphical Display: Codec Modes and Coding Schemes ............................................. 290
Individual Mobile Results Graphical Display ............................................................. 291
9.6.5
Simulation Reports .................................................................................................... 291
Reports of a Single Simulation .................................................................................. 291
Reports of a Group of Simulations ............................................................................ 292
9.6.6
Updating Cell Loads .................................................................................................. 292
9.6.7
Exporting Results ...................................................................................................... 292
GSM/GPRS/EDGE Coverage Predictions .......................................................................... 292
9.7.1
Coverage Prediction Calculation and Management ................................................. 292
9.7.2
Coverage Prediction Types ........................................................................................ 293
9.7.3
Coverage Prediction Reports ..................................................................................... 297
9.7.4
Coverage Prediction Comparison .............................................................................. 297
9.7.5
Coverage Prediction Export....................................................................................... 298
9.7.6
Point Analysis Tool .................................................................................................... 298
9.7.7
Multi-Point Analysis .................................................................................................. 299
GSM/GPRS/EDGE Neighbour Planning............................................................................ 300
9.8.1
Automatic Neighbour Allocation .............................................................................. 301
9.8.2
Graphical Neighbour Plan Editing ............................................................................. 301
9.8.3
Neighbour Consistency Check Tool ........................................................................... 302
GSM/GPRS/EDGE Automatic Frequency Planning .......................................................... 302
9.9.1
Interference Histogram Matrices .............................................................................. 303
Interference Matrix Generation ................................................................................ 303
Interference Matrix Analysis ..................................................................................... 304
Interference Matrix Export........................................................................................ 304
9.9.2
Automatic Frequency Planning Parameters.............................................................. 305
9.9.3
Automatic Frequency Planning Outputs ................................................................... 306
9.9.4
Interactive Frequency Planning................................................................................. 307
9.9.5
Frequency Plan Analysis ............................................................................................ 307
Frequency Plan Audit ................................................................................................ 307
Frequency Channel Search ........................................................................................ 308
Sector-to-Sector Interference Analysis ...................................................................... 308
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GSM/GPRS/EDGE Automatic Cell Planning ..................................................................... 309
GSM/GPRS/EDGE Co-planning With Other Radio Access Technologies .......................... 309
10
CDMA2000 Features ............................................................................................................. 310
CDMA2000 Network Model ............................................................................................ 310
10.1.2 Sites .......................................................................................................................... 311
10.1.3 Transmitters.............................................................................................................. 311
10.1.4 Cells (1xRTT, 1xEV-DO) .............................................................................................. 312
10.1.5 Site Templates .......................................................................................................... 313
10.1.6 Repeaters .................................................................................................................. 313
CDMA2000 Network Configuration Parameters ............................................................. 314
10.2.1 Frequency Bands and Carriers .................................................................................. 314
10.2.2 Global Network Settings ........................................................................................... 314
10.2.3 Radio Bearers ............................................................................................................ 315
10.2.4 Quality Indicators...................................................................................................... 315
CDMA2000 Radio Equipment .......................................................................................... 315
10.3.1 Site Equipment .......................................................................................................... 315
10.3.2 Reception Equipment (1xRTT, 1xEV-DO) ................................................................... 316
CDMA2000 Traffic Model ................................................................................................ 317
10.4.1 Services ..................................................................................................................... 317
10.4.2 Terminals .................................................................................................................. 318
10.4.3 Mobility Types ........................................................................................................... 320
10.4.4 User Profiles .............................................................................................................. 320
10.4.5 Traffic Data ............................................................................................................... 321
CDMA2000 Monte Carlo Simulation ............................................................................... 321
10.5.1 Generation of Realistic User Distributions ................................................................ 321
10.5.2 Power Control and Radio Resource Management .................................................... 321
CDMA2000 1xRTT Monte Carlo Simulation Algorithm.............................................. 322
CDMA2000 1xEV-DO Monte Carlo Simulation Algorithm ......................................... 323
10.5.3 Monte Carlo Simulation Management ..................................................................... 323
10.5.4 Simulation Graphical Analysis ................................................................................... 324
Graphical Display: Mobile Connection Status ........................................................... 324
Individual Mobile Result Graphical Display ............................................................... 325
10.5.5 Simulation Reports .................................................................................................... 325
Reports of a Single Simulation .................................................................................. 325
Reports of a Group of Simulations ............................................................................ 326
10.5.6 Updating Cell Loads .................................................................................................. 327
10.5.7 Exporting Results ...................................................................................................... 327
CDMA2000 Coverage Predictions ................................................................................... 327
10.6.1 Coverage Prediction Calculation and Management ................................................. 327
10.6.2 Coverage Prediction Types ........................................................................................ 327
10.6.3 Coverage Prediction Reports ..................................................................................... 331
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10.6.4 Coverage Prediction Comparison .............................................................................. 332
10.6.5 Coverage Prediction Export....................................................................................... 332
10.6.6 Point Analysis Tool .................................................................................................... 333
10.6.7 Multi-Point Analysis .................................................................................................. 333
CDMA2000 Neighbour Planning ..................................................................................... 334
10.7.1 Automatic Neighbour Allocation .............................................................................. 335
10.7.2 Graphical Neighbour Plan Editing ............................................................................. 336
10.7.3 Neighbour Consistency Check Tool ........................................................................... 336
CDMA2000 PN Offset Planning ....................................................................................... 337
10.8.1 Automatic PN Offset Planning Tool .......................................................................... 337
10.8.2 PN Offset Consistency Check Tool ............................................................................. 338
10.8.3 PN offset interference analysis ................................................................................. 338
CDMA2000 Automatic Cell Planning ............................................................................... 338
CDMA2000 Co-planning Features ................................................................................... 339
11
Multi-RAT Features ............................................................................................................... 340
Multi-RAT Network Model .............................................................................................. 340
Multi-RAT Network Configuration Parameters ............................................................... 342
Multi-RAT Radio Equipment ............................................................................................ 342
Multi-RAT Traffic Model (Multi-technology Services and Users) ..................................... 343
11.4.1 Services ..................................................................................................................... 343
11.4.2 Terminals .................................................................................................................. 344
11.4.3 Mobility Types ........................................................................................................... 344
11.4.4 User Profiles .............................................................................................................. 344
11.4.5 Traffic Data ............................................................................................................... 344
Multi-RAT Monte Carlo Simulations ................................................................................ 344
11.5.1 Definition .................................................................................................................. 345
11.5.2 Generation of Realistic User Distributions ................................................................ 345
11.5.3 Scheduling and Radio Resource Management.......................................................... 345
11.5.4 Monte Carlo Simulation Management ..................................................................... 345
11.5.5 Simulation Graphical Analysis ................................................................................... 346
Individual Mobile Result Graphical Display ............................................................... 347
11.5.6 Simulation Reports .................................................................................................... 347
Reports of a Single Simulation .................................................................................. 347
Reports of a Group of Simulations ............................................................................ 348
11.5.7 Updating Cell Loads .................................................................................................. 349
11.5.8 Exporting Results ...................................................................................................... 349
Multi-RAT Coverage Predictions...................................................................................... 349
11.6.1 Coverage Prediction Calculation and Management ................................................. 349
11.6.2 Coverage Prediction Types ........................................................................................ 349
11.6.3 Coverage Prediction Reports ..................................................................................... 349
11.6.4 Coverage Prediction Comparison .............................................................................. 349
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11.6.5 Coverage Prediction Export....................................................................................... 350
11.6.6 Point Analysis Tool .................................................................................................... 350
11.6.7 Multi-Point Analysis .................................................................................................. 350
Multi-RAT Inter-technology Neighbour Planning ............................................................ 351
11.7.1 Automatic Inter-technology Neighbour Allocation ................................................... 352
11.7.2 Graphical Neighbour Plan Editing ............................................................................. 352
11.7.3 Neighbour Consistency Check Tool ........................................................................... 353
Multi-RAT Inter-technology Interference Analysis .......................................................... 353
Multi-RAT Automatic Cell Planning ................................................................................. 354
12
TD-SCDMA Features .............................................................................................................. 355
TD-SCDMA Network Model ............................................................................................. 355
12.1.1 Sites .......................................................................................................................... 356
12.1.2 Transmitters.............................................................................................................. 356
12.1.3 Cells (R99, HSDPA, and HSUPA) ................................................................................ 357
12.1.4 Site Templates .......................................................................................................... 358
12.1.5 Repeaters .................................................................................................................. 358
TD-SCDMA Network Configuration Parameters .............................................................. 359
12.2.1 Frequency Bands and Carriers .................................................................................. 359
12.2.2 Global Network Settings ........................................................................................... 359
12.2.3 Radio Bearers (R99, HSDPA, and HSUPA) ................................................................. 360
12.2.4 UE categories (HSDPA and HSUPA) ........................................................................... 361
TD-SCDMA Radio Equipment .......................................................................................... 361
12.3.1 Site Equipment .......................................................................................................... 361
12.3.2 Reception Equipment (R99, HSDPA, and HSUPA)...................................................... 361
12.3.3 Smart Antenna Equipment........................................................................................ 362
TD-SCDMA Traffic Model ................................................................................................ 363
12.4.1 Services ..................................................................................................................... 364
12.4.2 Terminals .................................................................................................................. 364
12.4.3 Mobility Types ........................................................................................................... 365
12.4.4 User Profiles .............................................................................................................. 366
12.4.5 Traffic Data ............................................................................................................... 366
TD-SCDMA Monte Carlo Simulations .............................................................................. 366
12.5.1 Generation of Realistic User Distributions ................................................................ 367
12.5.2 Power Control and Radio Resource Management .................................................... 367
12.5.3 Monte Carlo Simulation Management ..................................................................... 368
12.5.4 Simulation Graphical Analysis ................................................................................... 369
Graphical Display: Mobile Connection Status ........................................................... 369
Individual Mobile Result Graphical Display ............................................................... 370
12.5.5 Simulation Reports .................................................................................................... 370
Reports of a Single Simulation .................................................................................. 370
Reports of a Group of Simulations ............................................................................ 371
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12.5.6 Updating Cell Loads .................................................................................................. 371
12.5.7 Exporting Results ...................................................................................................... 371
TD-SCDMA Coverage Predictions .................................................................................... 371
12.6.1 Coverage Prediction Calculation and Management ................................................. 372
12.6.2 Coverage Prediction Types ........................................................................................ 372
12.6.3 Coverage Prediction Reports ..................................................................................... 378
12.6.4 Coverage Prediction Comparison .............................................................................. 379
12.6.5 Coverage Prediction Export....................................................................................... 379
12.6.6 Point Analysis Tool .................................................................................................... 379
TD-SCDMA Neighbour Planning ...................................................................................... 380
12.7.1 Automatic Neighbour Allocation .............................................................................. 380
12.7.2 Graphical Neighbour Plan Editing ............................................................................. 381
12.7.3 Neighbour Consistency Check Tool ........................................................................... 382
TD-SCDMA Master/Slave Carrier Planning in N-Frequency Mode .................................. 382
TD-SCDMA Scrambling Code Planning ............................................................................ 383
12.9.1 Automatic Scrambling Code Planning Tool ............................................................... 383
12.9.2 Scrambling Code Consistency Check Tool ................................................................. 384
TD-SCDMA Co-planning With Other Radio Access Technologies..................................... 384
13
LPWA Features ...................................................................................................................... 385
LPWA Network Model ..................................................................................................... 385
13.1.1 Sites .......................................................................................................................... 385
13.1.2 Transmitters.............................................................................................................. 386
13.1.3 Cells........................................................................................................................... 386
13.1.4 Site Templates .......................................................................................................... 387
13.1.5 Repeaters .................................................................................................................. 387
LPWA Network Configuration Parameters ...................................................................... 388
13.2.1 Frequency Bands ....................................................................................................... 388
13.2.2 Channel Configurations............................................................................................. 388
13.2.3 Radio Bearers ............................................................................................................ 389
13.2.4 Quality Indicators...................................................................................................... 389
LPWA Radio Equipment .................................................................................................. 389
13.3.1 LPWA Reception Equipment ..................................................................................... 389
LPWA Traffic Model ........................................................................................................ 390
13.4.1 Services ..................................................................................................................... 390
13.4.2 Terminals .................................................................................................................. 391
13.4.3 Mobility Types ........................................................................................................... 391
LPWA Coverage Predictions ............................................................................................ 392
13.5.1 Coverage Prediction Calculation and Management ................................................. 392
13.5.2 Coverage Prediction Types ........................................................................................ 392
13.5.3 Coverage Prediction Reports ..................................................................................... 395
13.5.4 Coverage Prediction Comparison .............................................................................. 395
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Atoll 3.4.0 Technical Overview
13.5.5 Coverage Prediction Export....................................................................................... 396
13.5.6 Point Analysis Tool .................................................................................................... 397
13.5.7 Multi-Point Analysis at Device Locations .................................................................. 397
LPWA Neighbour Planning .............................................................................................. 398
13.6.1 Automatic Neighbour Allocation .............................................................................. 398
13.6.2 Graphical Neighbour Plan Editing ............................................................................. 399
13.6.3 Neighbour Consistency Check Tool ........................................................................... 399
LPWA Automatic Cell Planning ....................................................................................... 399
14
Wi-Fi Features ....................................................................................................................... 402
Wi-Fi Network Model ...................................................................................................... 402
14.1.2 Sites .......................................................................................................................... 403
14.1.3 Transmitters.............................................................................................................. 403
14.1.4 Cells........................................................................................................................... 404
14.1.5 Site Templates .......................................................................................................... 405
Wi-Fi Network Configuration Parameters ....................................................................... 405
14.2.1 Frequency Bands and Channels ................................................................................ 405
14.2.2 Frame Configurations ............................................................................................... 405
14.2.3 Radio Bearers ............................................................................................................ 406
14.2.4 Quality Indicators...................................................................................................... 406
Wi-Fi Radio Equipment.................................................................................................... 407
14.3.1 Reception Equipment and MIMO Gains .................................................................... 407
Wi-Fi Traffic Model ......................................................................................................... 407
14.4.2 Services ..................................................................................................................... 408
14.4.3 Terminals .................................................................................................................. 408
14.4.4 Mobility Types ........................................................................................................... 409
14.4.5 User Profiles .............................................................................................................. 409
14.4.6 Traffic Data ............................................................................................................... 410
Wi-Fi Monte Carlo Simulations ....................................................................................... 410
14.5.1 Generation of Realistic User Distributions ................................................................ 410
14.5.2 Scheduling and Radio Resource Management.......................................................... 410
14.5.3 Monte Carlo Simulation Management ..................................................................... 411
14.5.4 Simulation Graphical Analysis ................................................................................... 412
Graphical Display: Mobile Connection Status ........................................................... 412
Individual Mobile Results Graphical Display ............................................................. 413
14.5.5 Simulation Reports .................................................................................................... 413
Reports of a Single Simulation .................................................................................. 413
Reports of a Group of Simulations ............................................................................ 415
14.5.6 Updating Cell Loads .................................................................................................. 415
14.5.7 Exporting Results ...................................................................................................... 415
Wi-Fi Coverage Predictions ............................................................................................. 415
14.6.1 Coverage Prediction Calculation and Management ................................................. 415
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14.6.2 Coverage Prediction Types ........................................................................................ 416
14.6.3 Coverage Prediction Reports ..................................................................................... 418
14.6.4 Coverage Prediction Comparison .............................................................................. 419
14.6.5 Coverage Prediction Export....................................................................................... 419
14.6.6 Point Analysis Tool .................................................................................................... 420
14.6.7 Multi-Point Analysis .................................................................................................. 420
Wi-Fi Neighbour Planning ............................................................................................... 421
14.7.1 Automatic Neighbour Allocation .............................................................................. 421
14.7.2 Graphical Neighbour Plan Editing ............................................................................. 421
14.7.3 Neighbour Consistency Check Tool ........................................................................... 421
Wi-Fi Automatic Frequency Planning .............................................................................. 422
14.8.2 AFP Cost Components ............................................................................................... 422
14.8.3 Automatic Frequency Planning ................................................................................. 423
14.8.1 Frequency Plan Analysis ............................................................................................ 424
Frequency Search Tool .............................................................................................. 424
Frequency Display on Map ........................................................................................ 424
Wi-Fi Automatic Cell Planning ......................................................................................... 424
Wi-Fi Co-planning With Mobile Radio Access Technologies ............................................ 424
15
WiMAX Features ................................................................................................................... 426
WiMAX Network Model .................................................................................................. 426
15.2.1 Sites .......................................................................................................................... 427
15.2.2 Transmitters.............................................................................................................. 427
15.2.3 Cells........................................................................................................................... 428
15.2.4 Site Templates .......................................................................................................... 429
15.2.5 Repeaters .................................................................................................................. 429
WiMAX Network Configuration Parameters ................................................................... 430
15.3.1 Frequency Bands and Channels ................................................................................ 430
15.3.2 Global Network Settings ........................................................................................... 431
15.3.3 Frame Configurations ............................................................................................... 432
15.3.4 Radio Bearers ............................................................................................................ 433
15.3.5 Schedulers ................................................................................................................. 433
15.3.6 Quality Indicators...................................................................................................... 433
WiMAX Radio Equipment ................................................................................................ 433
15.4.1 Reception Equipment and MIMO Gains .................................................................... 433
15.4.2 Smart Antenna Equipment........................................................................................ 435
WiMAX Traffic Model ...................................................................................................... 436
15.5.1 Services ..................................................................................................................... 436
15.5.2 Terminals .................................................................................................................. 437
15.5.3 Mobility Types ........................................................................................................... 437
15.5.4 User Profiles .............................................................................................................. 437
15.5.5 Traffic Data ............................................................................................................... 438
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Atoll 3.4.0 Technical Overview
WiMAX Monte Carlo Simulations .................................................................................... 438
15.6.1 Generation of Realistic User Distributions ................................................................ 438
15.6.2 Scheduling and Radio Resource Management.......................................................... 438
15.6.3 Monte Carlo Simulation Management ..................................................................... 440
15.6.4 Simulation Graphical Analysis ................................................................................... 441
Graphical Display: Mobile Activity Status ................................................................. 441
Individual Mobile Results Graphical Display ............................................................. 441
15.6.5 Simulation Reports .................................................................................................... 441
Reports of a Single Simulation .................................................................................. 441
Reports of a Group of Simulations ............................................................................ 442
15.6.6 Updating Cell Loads .................................................................................................. 443
15.6.7 Exporting Results ...................................................................................................... 443
WiMAX Coverage Predictions ......................................................................................... 443
15.7.1 Coverage Prediction Calculation and Management ................................................. 443
15.7.2 Coverage Prediction Types ........................................................................................ 443
15.7.3 Coverage Prediction Reports ..................................................................................... 452
15.7.4 Coverage Prediction Comparison .............................................................................. 452
15.7.5 Coverage Prediction Export....................................................................................... 452
15.7.6 Point Analysis Tool .................................................................................................... 453
15.7.7 Multi-Point Analysis .................................................................................................. 453
WiMAX Neighbour Planning ........................................................................................... 454
15.8.1 Automatic Neighbour Allocation .............................................................................. 455
15.8.2 Graphical Neighbour Plan Editing ............................................................................. 455
15.8.3 Neighbour Consistency Check Tool ........................................................................... 456
WiMAX Automatic Frequency, Preamble Index, and Zone Permbase Planning .............. 456
15.9.2 AFP Cost Components ............................................................................................... 457
15.9.3 Automatic Preamble Index Planning ......................................................................... 458
15.9.4 Automatic Frequency Planning ................................................................................. 459
15.9.5 Automatic Downlink and Uplink Zone Permbase Planning ....................................... 460
15.9.6 Frequency, Preamble Index, and Zone Permbase Plan Analysis................................ 460
Cell Parameter Search Tool ....................................................................................... 460
Cell Parameter Display on Map ................................................................................ 461
Cell Identifier Collision Zones Prediction ................................................................... 461
WiMAX Automatic Cell Planning ..................................................................................... 461
WiMAX Co-planning With Other Radio Access Technologies .......................................... 461
16
Measurements and Drive Test Data Features ....................................................................... 463
CW Measurements .......................................................................................................... 463
Drive Test Data ............................................................................................................... 464
Propagation Model Calibration ....................................................................................... 465
Path Loss Tuning ............................................................................................................. 466
17
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Automatic Cell Planning (ACP) Features ................................................................................ 468
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Atoll 3.4.0 Technical Overview
Automatic Cell Planning Scenario Definition ................................................................... 469
17.1.1 Optimisation Targets ................................................................................................ 470
Network Layers ......................................................................................................... 470
Working Zones .......................................................................................................... 471
Cost Control .............................................................................................................. 471
Optimisation Constraints .......................................................................................... 472
Multi-Storey Optimisation ........................................................................................ 472
EMF Exposure Optimisation ...................................................................................... 473
17.1.2 Optimisation Objectives ............................................................................................ 473
Radio Quality Objectives ........................................................................................... 474
Throughput Objective ............................................................................................... 476
Load Balancing Objective .......................................................................................... 476
Optimisation Zones and Weighting Maps................................................................. 477
17.1.3 Cell Parameter Reconfiguration ................................................................................ 477
17.1.4 Site Selection ............................................................................................................. 479
17.1.5 Antenna Management .............................................................................................. 480
Automatic Cell Planning Results ...................................................................................... 481
17.2.1 ACP Optimisation Process ......................................................................................... 481
17.2.2 ACP Implementation Plan ......................................................................................... 482
17.2.3 ACP Coverage Predictions ......................................................................................... 486
17.2.4 ACP Implementation Plan Comparison ..................................................................... 487
18
Automatic Frequency Planning (AFP) Features ..................................................................... 488
Atoll 5G NR AFP ........................................................................................................ 488
Atoll LTE AFP ............................................................................................................. 488
Atoll NB-IoT AFP ........................................................................................................ 488
Atoll GSM AFP ........................................................................................................... 488
Atoll Wi-Fi AFP .......................................................................................................... 489
Atoll WiMAX AFP ...................................................................................................... 489
19
Automatic Site Positioning (ASP) Features ............................................................................ 490
Automatic Site Positioning Scenario Definition ............................................................... 491
19.1.1 Design Methods ........................................................................................................ 492
19.1.2 Population- and Traffic-driven Site Positioning......................................................... 493
19.1.3 Site Deployment Objectives ...................................................................................... 494
Automatic Site Positioning Results .................................................................................. 494
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Introduction
Atoll 3.4.0 Technical Overview
1 Introduction
Atoll is a native 64-bit multi-technology wireless network design and optimisation platform that supports wireless operators
throughout the network lifecycle, from initial design to densification and optimisation.
This document provides an overview of Atoll from a technical perspective. The current chapter provides an introduction to
Atoll, the second chapter presents the general features of the Atoll platform (Atoll Core), and the following chapters describe
features related to the various mobile radio access technology supported by Atoll.
A technical overview of Atoll Microwave is available as a separate document.
Supported Wireless Technologies
Atoll supports the following wireless radio access technologies:










5G NR
LTE/LTE-Advanced
NB-IoT
UMTS/HSPA
GSM/GPRS/EDGE
CDMA2000 1xRTT/EV-DO
TD-SCDMA
LPWA IoT technologies (LoRa, Sigfox, Ingenu, Wireless MBus, etc.)
Wi-Fi
WiMAX
Atoll supports integrated network planning for multi-RAT networks. It features a multi-technology network database, a
unified traffic model, a combined Monte Carlo simulator, and a multi-RAT ACP (Automatic Cell Planning) module. Atoll
provides operators with a comprehensive and evolutionary framework for planning and optimising multi-technology
networks including small cells and integrated Wi-Fi.
Atoll also enables Internet of Things (IoT) wireless network operators to design, plan, and optimise their networks based on
Low Power Wide Area (LPWA) technologies, such as LoRa, Sigfox, Ingenu, Wireless MBus, etc.
Atoll Microwave supports backhaul design and planning for networks comprising microwave and other backhaul links.
Supported Operating Systems
Atoll supports the following versions of Microsoft Windows operating systems:
Supported operating systems for Atoll 64-bit







Microsoft Windows 10 Professional and Enterprise (64‐bit)
Microsoft Windows 8 and 8.1 Professional and Enterprise (64‐bit)
Microsoft Windows 7 (64‐bit)
Microsoft Windows Server 2019
Microsoft Windows Server 2016
Microsoft Windows Server 2012 and 2012 R2
Microsoft Windows Server 2008 R2
Supported operating systems for Atoll 32-bit





Microsoft Windows 10 Professional and Enterprise (32‐bit and 64‐bit)
Microsoft Windows 8 and 8.1 Professional and Enterprise (32‐bit and 64‐bit)
Microsoft Windows 7 (32‐bit and 64‐bit)
Microsoft Windows Server 2012 and 2012 R2
Microsoft Windows Server 2008 R2
Atoll also supports VMWare ESXi 4.x, 5.x, and 6.x virtualisation platforms.
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Introduction
Atoll 3.4.0 Technical Overview
Supported Database Management Systems
Databases allow several users to share data without the risk of data inconsistency. In a multi-user environment, user
documents are connected to a central database, in which users store their work on a common project. Atoll supports the
following RDBMS:



Oracle 11g, 12c, and 18c
Microsoft SQL Server 2005, 2008, 2012, 2014, and 2017
Microsoft Access
Scalable Installation Configurations
Atoll supports a full range of implementation scenarios, from standalone to enterprise-wide server-based configurations
using distributed and parallel computing. For example, Atoll can be configured for use as follows:
Standalone Configuration
Atoll is installed on each individual user computer with a fixed licence key plugged in each computer. Geographic data files
and path loss calculation results can be stored locally or on network servers for sharing between multiple users. Network
data and links to geographic data and path loss results are stored in the Atoll document files.
Figure 1.1
Standalone configuration: User computers run Atoll and store network, geo, and calculation results data
Multi-user Thick Client Configuration
Atoll is installed on each individual user computer on a network with a floating licence management server that allocates
licence tokens to Atoll sessions run by users on their computers. The network database, geographic data files and path loss
calculation results are stored on network servers for sharing between multiple users.
Figure 1.2
Multi-user thick client configuration: User computers run Atoll
Multi-user Thin Client Configuration
Atoll is installed on servers connected to user computers and a floating licence management server on a network. The floating
licence management server allocates licence tokens to Atoll sessions run by the users on the servers. The servers can be
Citrix-based, where users run Atoll sessions on the servers through the Citrix interface. The network database, geographic
data files and path loss calculation results are stored on network servers for sharing between multiple users.
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Introduction
Atoll 3.4.0 Technical Overview
Figure 1.3
Multi-user thin client configuration: Application servers run Atoll
Multi-user Cloud-based Configuration
Atoll is installed on the cloud accessed by users through their computers. The software licence management service allocates
licence tokens to Atoll sessions run by the users on the cloud. The network database, geographic data files and path loss
calculation results are stored on the cloud’s elastic storage system.
Figure 1.4
Multi-user cloud-based configuration
Recommended Hardware and Software
The following table lists the recommended hardware and software for user computers (clients) intended for running Atoll.
Processor
Core i7 at 2.5GHz or more
RAM
8 GB or more
Storage
SSD with 512 GB1 or more
Operating system
Microsoft Windows 10
Other requirements


Fixed licence: 1 USB port required for the fixed licence key
Floating licence: nethasp.ini file in the Atoll installation folder
The following table lists the recommended hardware and software for application servers intended for running Atoll through
thin clients such as Remote Desktop or Citrix.
1
Processor
Xeon E5, E7 or equivalent
2 cores at 2.5GHz or more per user
RAM
4 GB per user or more (min 8 GB)
The required space depends on the size of the geographic data, prediction and calculation results stored on disk.
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Introduction
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Storage
SSD with 256 GB or more
Operating system
Microsoft Windows Server 2012 R2
Thin client
Remote Desktop or Citrix XenApp 6.5 or later
Virtualisation
VMWare ESXi 5.5
The following table lists the recommended hardware and software for an Oracle database server. The same configuration
can be considered valid for other database systems as well.
Processor
Xeon E5, E7 or equivalent
RAM
8 GB or more
Storage
2x146 GB (RAID 1) or more2
Operating system
RDBMS
Oracle: Windows / UNIX / Linux / Solaris
Microsoft SQL Server: Microsoft Windows
Oracle 11g or 12c
Microsoft SQL Server 2012, 2014, or 2017
Modular Architecture
Atoll is based on an open, object-oriented, modular architecture. It comprises a platform (Atoll Core) which connects all Atoll
technology modules and extensions together. All Atoll technology modules and extensions are based on Atoll Core and take
full advantage of its high-performance features.
The figure below shows the recommended modular configurations for different technologies. In addition to the modules
developed by Forsk, products and applications available from 3rd party developers (propagation models, optimisation tools,
etc.) can also be integrated with Atoll without any modifications to other existing components.
Atoll Core is the platform which connects all Atoll technology modules and extensions into an integrated framework providing
user-friendly, powerful, fast, and accurate radio planning and optimisation features. The features provided by Atoll Core to
other modules are described in Atoll Core Features.
The Atoll Live module allows operators to integrate live network measurements (KPIs 3 & UE4/cell/MDT5 traces) into Atoll’s
advanced planning and optimisation features to offer open-loop SON capabilities. The Atoll Live module enables augmented
network planning and optimisation features in Atoll that intelligently combine reliable predictions with real-world data from
live networks. The features provided by Atoll Live to other modules are described in Atoll Live Features.
2
A table space of 400 MB per 10000 transmitters must be provided.
KPI: key performance indicator
4 UE: user equipment
5 MDT: minimisation of drive tests
3
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Introduction
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Figure 1.5
Atoll modules
Different Atoll modules allow planning and optimisation of specific radio access technologies. Design, planning, and
optimisation features of different modules are described in their respective chapters.
A technical overview of Atoll Microwave is available as a separate document.
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2 Atoll Core Features
Atoll is a native 64-bit application. All of its modules, including the Atoll Core, technology modules, AFP, ACP, ASP, propagation
models, etc., are 64-bit components. Atoll 64-bit takes full advantage of the extensive computational capacity offered by the
64-bit computer architecture, hence, significantly extending the memory space available for calculations and data
management. This enables Atoll users to design, plan, and optimise large-scale, complex radio and microwave networks, for
which the memory requirements exceed the 32-bit limits. In addition to enhanced radio network planning and optimisation
capacity, the 64-bit architecture provides considerable advantages in the following Atoll Core features:
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User interface
Geographic information system
Calculation and memory management
Data and user management
Licence management
Data exchange services
Task automation and development services
User Interface
Atoll delivers a powerful and intuitive user interface that enables locating, accessing, and editing data directly on the map.
Atoll’s object-oriented user interface provides quick access to all the functions relevant to the objects selected on the map,
in the data explorer, or in the data tables. Atoll’s main window consists of:
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Menus
Toolbars
Workspace, where the map window, data tables, and reports are displayed
Explorer windows containing the network data and calculation results, geo data, and network parameters
Additional windows for dedicated tools such as the find tool, the legend window, the panoramic view, the site
configuration window, the point analysis tool, the CW measurement and drive test data analysis tools, the event
viewer, etc.
The Atoll user interface is easily configurable and allows creating customised working environments. An example of Atoll user
interface is presented in the figure below.
Menus
Toolbars
Workspace
windows
Explorer
windows
Figure 2.1
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Atoll user interface – main windows
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2.1.1 Menus
Atoll menus consist of the main menu and context menus. The main menu provides access to commands applicable to the
Atoll working environment or the current Atoll document.
Figure 2.2
Atoll main menu bar
The context menus provide access to the commands relevant to the currently selected items in the explorer windows or the
map window.
Figure 2.3
Transmitter context menu
2.1.2 Toolbars
Toolbars provide a quick, one-click access to the most frequently used commands. Commands available in the toolbars range
from general commands to dedicated commands related to radio network planning. Atoll toolbars are fully customisable.
External tools, such as add-ins and macros, can also add dedicated buttons to the toolbars for quick access.
Figure 2.4
Radio planning toolbar
2.1.3 Explorer Windows
The explorer windows manage different types of data. There are three explorer windows in Atoll:
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Network explorer: The Network explorer enables you to manage radio data and calculation results. Depending on
the modules installed with Atoll, the Network explorer contains folders for the following:
o Sites
o Transmitters
o Predictions
o Monte Carlo simulations
o Traffic analysis
o Interference matrices
o Multi-point analyses
o Automatic cell planning
o Hexagonal design
o Microwave links
o CW Measurements
o Drive test data
Geo explorer: The Geo explorer enables you to manage multi-resolution geographic data. The number of folders
depends on the number and types of geographic data (vector data, scanned images, etc.) you import or create:
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o Clutter classes
o Clutter heights
o Digital terrain model
o Population data
o Traffic maps
o Geoclimatic parameters
o Any other geo data map (images, transport routes, etc.)
Parameters explorer: The Parameters explorer enables you to manage propagation models and network-level
parameters. It contains:
o Propagation models
o Radio network equipment (antennas, 3D beamforming antennas, transmitter equipment, repeater and
smart antenna equipment, and waveguides, cables, and feeders.)
o Traffic parameters (services, mobility types, terminals, user profiles, and environments)
o Network settings (station templates, frequencies and bands, bearers, reception equipment, quality
indicators, etc.)
o Microwave link network settings and equipment
o Any additional module created using the API
The figure below presents the explorer windows.
Figure 2.5
Explorer windows
Note that each folder of the explorer windows allows you to create groups, selections, filters, and lists, based on graphic
selections or by user-definable flags. This feature facilitates managing large amounts of data. For more information, see 2.5
Network Data Management. Users can create folders and subfolders in the Network and Geo explorers in order to organize
vector and image data.
An additional site explorer window displays all the radio network elements, such as transmitters, remote antennas, repeaters,
microwave links, etc., that are installed at a site in a hierarchical series of folders. It allows a quick access to planning and
optimisation functions for collocated cells.
Figure 2.6
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Site explorer
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2.1.4 Map Window
The map window displays the objects corresponding to network data, geographic data, and calculation results such as
coverage predictions and simulation results, as geographic overlays.
The display properties such as layer order, style, colour, transparency, scale, zoom level, etc., are user-definable. More than
one map window can be opened simultaneously allowing you to work with multiple views of the same project, for example
with different zoom levels. You can zoom in and out using the mouse wheel, and move the map using the centre mouse
button.
Figure 2.7
Map window
Atoll can display information related to objects under the mouse cursor in real time. The information displayed in the tool
tips is user-definable. This tool tip feature is shown in the figure above.
Atoll’s object-oriented user interface allows:
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Allows selecting objects on the map and in the explorer windows
Provides access to all available functions for the selected objects through context menus
Allows interactive modification of object parameters (site location, sector azimuth, cell colour, etc.) using the mouse
on the map window.
Figure 2.8
Transmitter coordinates and azimuth modification
Network element parameters can be thematically mapped according to their values. Atoll enables defining object display
attributes (colour, style, etc.) according to the values of a selected parameter. In the above figure, sectors are displayed using
a symbol based on antenna beamwidth.
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The current map configuration (the map zoom level and centre, the geographic data visibility as well as display order and
settings, and optionally the definition of the computation and focus zones) can be stored as a favourite view enabling the
user to quickly switch back to the stored configuration. For more information, see 2.1.9 Favourite Views Window.
2.1.5 Data Tables
Atoll stores network data (sites, transmitters, repeaters, antennas, cells, network parameters, etc.) in the form of tables,
containing all their parameters and characteristics. The data contained in prediction reports are also stored in the form of
tables.
You can filter, sort, and group the data content of the tables, and view statistical analyses of the data. You can also export or
import data to Atoll data tables. Various commands applicable to data tables are available from the context menu or from
the toolbar displayed above the table. For example, you can assign different colour codes to the table columns. Network data
table configuration, i.e., column order, format, and visibility status, can be stored to and loaded from user configuration files.
Figure 2.9
Sites data table
You can customise the data table structure as needed. Custom fields can be added to data tables. Custom text fields may also
optionally support hypertext links, allowing the users to enter and click hypertext links to URLs from within the Atoll’s user
interface.
Figure 2.10 URL editor
2.1.6 Panoramic Window
The panoramic window displays the entire area covered by your project’s geographic data and outlines the area currently
displayed in the map window.
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Figure 2.11 Panoramic window
2.1.7 Legend Window
The legend window displays the symbols and colours associated to various user-selected radio network elements as well as
calculation results.
Figure 2.12 Legend window
2.1.8 Event Viewer Window
Atoll displays messages in the event viewer. The event viewer displays information, warning, and error messages, as well as
the progress of calculations for all open Atoll documents.
2.1.9 Favourite Views Window
The favourites view window allows you to store multiple map locations and to quickly switch from one to the other. Each
favourite view stores a subset of the user configuration, i.e., the map zoom level and centre, the geographic data visibility as
well as display order and settings, and optionally the definition of the computation and focus zones.
Favourite views can be stored per-user, i.e., applicable to all the Atoll projects opened on a computer, or within the Atoll
documents enabling sharing between users.
Figure 2.13 Favourite views window
For more information on user configurations, see 2.5.8 User Configurations.
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2.1.10 Other Windows
Other tools available in Atoll can have their respective windows. Such tools include the find on map tool, the point analysis
tool, the CW measurement and drive test data analysis tools, etc.
Figure 2.14 The find on map tool (left); the point analysis and CW measurement analysis tools (right)
Geographic Information System (GIS)
Atoll includes a high-performance built-in GIS exclusively designed for radio network planning and optimisation. Atoll’s GIS is
fully integrated with the user interface and provides full and fast access to network and geo data. Atoll’s GIS supports all
digital geographic data types. These geographic data can be stored either locally on each workstation or on a shared server.
The Atoll 64-bit architecture enables users to work with high-resolution, wide-area geographic data sets without the need for
splitting the set into smaller regions or subprojects.
2.2.1 High-performance Display
Using a unique dynamic sampling mechanism, the Atoll GIS delivers a real-time zooming, locating, and panning experience,
even with high-resolution country-wide geographic data sets. Atoll’s dynamic sampling mechanism intelligently loads and
unloads geographic data from memory according to the displayed map area and zoom. This allows Atoll to work with large
geographic data objects, without any limitations on the object size.
Figure 2.15 Instant zoom using dynamic sampling (10 GB of DTM data)
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In addition to dynamic sampling for displaying raster geographic data objects, Atoll displays vector objects (points, lines, and
polygons), including network elements such as sites, transmitters, microwave links, etc., using graphic primitives. These
mechanisms enable Atoll to provide a high-performance GIS for the purpose of radio network planning and optimisation.
These features enable Atoll to optimise memory usage, and therefore allow users to comfortably work with large-scale,
country-wide, multi-technology projects.
2.2.2 Multi-resolution Geographic Database
Atoll supports multiple resolutions for the geographic database. This allows, for example, the integration of high-resolution
urban data (up to 1m resolution) with a medium-resolution regional or countrywide data. The figure below provides an
example of multi-resolution terrain elevation data.
Urban area DTM
Rural area DTM
Microcell DTM
Figure 2.16 Multi-resolution geographic data
2.2.3 Supported Geo Data Types and File Formats
Atoll supports the following geographic data types:
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Terrain elevation (up to 1m resolution)
Clutter classes (up to 255 classes)
Clutter heights
Traffic maps
Raster images
2D and 3D vector data
Population maps
Online maps
Text data
Atoll’s GIS supports numerous industry-standard file formats including. Geo data objects, coverage predictions, and other
calculation results can also be exported from Atoll to various formats. The various supported geo data formats are:
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BIL
TIFF
BMP
JPEG
JPEG 2000
ECW
PNG
Vertical Mapper GRD and GRC
MapInfo MIF and TAB
ArcView grid TXT and ASC
ArcView SHP and PRJ
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Atoll 3.4.0 Technical Overview
Google Earth KML and KMZ
Erdas IMG
AutoCAD DXF
Planet
Raw binary data
Geographic data are managed through the Geo explorer window as presented in the figure below.
Figure 2.17 Geo explorer
Geographic data are displayed as layers in the map window. Any number of layers can be managed and displayed
simultaneously with different transparency levels. An example of a two-layer overlay is presented in the figure below.
Figure 2.18 Clutter and terrain elevation overlay
2.2.4 Terrain Elevation Data
Atoll supports 16-bit terrain elevation maps. Each terrain elevation map is a geo-referenced matrix that contains the altitude
value (in m) for each pixel. In a multi-resolution case, you can specify the priority for each map. Atoll uses the map with the
highest priority level for points covered by more than one terrain elevation map. The figure below shows an example of a
terrain elevation map.
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Figure 2.19 Terrain elevation map
2.2.5 Clutter Class Data
Atoll supports 8-bit colour-coded clutter data. This corresponds to a maximum of 255 clutter classes. Each clutter class
represents a type of land usage. The figure below gives an example of a clutter map.
Figure 2.20 Clutter classes map
Average height and shadow fading standard deviations per frequency band are assigned to each clutter class as presented in
the figure below. Atoll also allows you to define an indoor loss per frequency per clutter class in order to model building
penetration losses for signals at different frequencies. Specific clutter parameters corresponding different propagation
models can be defined separately for each propagation model. This allows different propagation models to be used in the
same project. Multi-layer clutter maps are supported with the same priority mechanism as for the terrain elevation maps.
Figure 2.21 General clutter parameters
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2.2.6 Clutter Height Data
Atoll supports 16-bit clutter height maps. Each clutter height map is a geo-referenced matrix that contains the clutter height
value (in m) for each pixel. The figure below shows an example of a clutter height map. The clutter height data is optional. If
unavailable, Atoll uses the clutter height information specified in the clutter class map. For more information on clutter class
maps, see 2.2.5 Clutter Class Data. High resolution raster building data can be used by the Aster propagation model for raytracing calculations.
Figure 2.22 Clutter height map
2.2.7 Traffic Data
Atoll supports the following traffic data types:
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Raster traffic data
Vector traffic data
Live traffic data
Traffic density data
Fixed subscribers
Different traffic layers of various types can be overlaid to define the total traffic. Furthermore, a clutter weighting function
and an indoor/outdoor ratio can be applied to each layer in order to spread the traffic according to the clutter.
Raster Traffic Data
Atoll supports raster traffic maps. Each raster traffic map is a geo-referenced matrix containing traffic information (e.g.,
service, user density, user mobility, etc.) per pixel. The definition of traffic maps is independent of radio access technologies.
This allows the exact content of traffic information to be based on multi-technology service definitions. For more information,
see the specific technology chapter that interests you. The figure below provides an example of a raster traffic map.
Figure 2.23 Raster traffic map
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Vector Traffic Data
Atoll can use traffic data in vector formats (lines, polygons, and vectors) in calculations. Here, the traffic information (e.g.,
service, user density, user mobility, etc.) is an attribute of the vector. The definition of traffic maps is independent of radio
access technologies. This allows the exact content of traffic information to be based on multi-technology service definitions.
For more information, see the specific technology chapter that interests you. The figure below provides an example of traffic
vectors.
Figure 2.24 Vector traffic
Live Traffic Data
Atoll can use live traffic data in calculations. The corresponding traffic map associates different input traffic data to each
sector: throughput per service, number of users per service (as shown in the figure below), Erlangs (as shown in the figure
following that), etc. Furthermore, for each sector, traffic is spread within the sector according to the clutter weighting
function, if specified.
Figure 2.25 UMTS live traffic data
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Figure 2.26 GSM live traffic data
Traffic Density Data
Atoll supports traffic density maps. A traffic density map is a geo-referenced matrix that contains traffic density information
for each pixel. Circuit-switched traffic density maps are expressed in Erlangs/km2 while packet-switched traffic density maps
are specified in kbps/km2. The figure below presents an example of a traffic density map.
Figure 2.27 Traffic density map
Fixed Subscribers
Fixed subscriber lists or traffic maps enable the modelling of subscribers at fixed locations. It is possible to define traffic
parameters for each subscriber in the fixed subscriber traffic map. You can then run multi-point analysis predictions on
subscriber lists to determine the received signal levels, signal quality, and throughputs.
The fixed subscriber traffic maps can be imported from external files in text or Excel formats, or created interactively using
the mouse on the map window. Fixed subscriber traffic maps contain data related to different subscribers, such as:
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X and Y coordinates
Height
Terminal
Service
Mobility type
Serving cell name (optionally user-defined, can be calculated by Atoll)
Antenna azimuth and tilt (optionally user-defined, can be calculated by Atoll)
Indoor/outdoor flag
The figure below shows a fixed subscriber traffic map.
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Figure 2.28 Fixed subscriber traffic map
Multi-layer Traffic Data
Different traffic maps, whether raster, vector, or live data, can be overlaid. The figure below shows an example of such a
situation.
Figure 2.29 Multi-layer, multi-format traffic data
Cumulated Traffic Maps
Different traffic maps, irrespective of their types (raster, vector, live data, or traffic density map), can be combined on a pixelby-pixel basis. Cumulated traffic maps can be generated based on various criteria: service type (e.g., circuit switched or packet
switched), mobility type, terminal type, etc. Thus created aggregated traffic maps can then be handled as any other traffic
map.
By using this feature, you can sum up, for example, live network traffic (existing customers) with additional expected traffic
(predicted customer base growth). The cumulated traffic map created can then be used as a basis for network capacity
analysis and potential network extension.
2.2.8 2D and 3D Vector Data
Atoll supports vector data such as:
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Multi-layer linear objects: roads, railways, airports, rivers, coastlines, etc.
Liner objects or 2D polygons for traffic spreading. For more information, see 2.2.7 Traffic Data.
2D polygon vectors for land use data.
3D urban vector data including building contours and heights. This information can be used with certain advanced
propagation models such as Aster and the Atoll CrossWave propagation model.
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The figure below provides an example of 3D urban vector data.
Figure 2.30 3D building data
2.2.9 Population Data
Atoll supports population data such as population figures or population densities. These data can be in raster or vector
formats. The figure below provides an example of a population density map.
Figure 2.31 Population density map
Population data can then be used in conjunction with coverage predictions for generating coverage reports. For example, the
report presented in the figure below gives the population covered by the network for a particular region (population figures
and percentages). Additionally, population data maps can also be weighted by clutter class. For more information on coverage
prediction reports, see 2.9 Calculation Result Reports.
Figure 2.32 Population-based coverage report
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2.2.10 Online Maps
Atoll can display various types of online maps in the map window. Once imported by specifying server URLs, online maps are
listed and accessible in the Atoll Geo explorer as shown in the figure below.
Figure 2.33 An online map displayed as a geo data layer
Using the Find on Map tool, you can search online for a location by its street address and view it in the Atoll map window.
2.2.11 Web Map Services
Web Map Services (WMS) are also supported by Atoll. The maps can be located on WMS servers either on the Internet or on
internal servers. It is also possible to connect to secure WMS servers using the https protocol.
Figure 2.34 Elevation contour map via WMS
2.2.12 Images
Atoll supports raster images such as scanned maps, aerial photos, and satellite photos. An aerial photo example is displayed
in the figure below. The raster image opacity and contrast can be adjusted by the user.
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Figure 2.35 Satellite image
2.2.13 Text Data
Atoll is capable of working with text data. The figure below provides an example where area names are displayed on the map
window. Other text data examples could be region names, street names, river names, site names, and so on.
Figure 2.36 Text data display
2.2.14 Other Data Types
Atoll is capable of importing any data type, raster and vector, as long as it is compatible with the import formats described in
2.2.3 Supported Geo Data Types and File Formats. The name, type, and supported format of the data object must be specified
by the user. Like any other geographic data layer, statistical functions are available for other data types as well. The figure
below gives an example of an income map providing raster information about the average annual salary (in $ per year).
Figure 2.37 Annual revenue map (example of an “other data type” map)
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2.2.15 Working Zones
Atoll provides you with a set of tools, called zones, to define geographic and map regions for different uses. Zones are multipolygonal areas on the maps, which can be created and modified as required, and used to define areas of the map for the
following purposes:
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Filtering zone: The filtering zone is a graphical filter that restricts the radio network objects displayed on the map
and in the Network explorer to those inside the filtering zone polygon. It also defines which objects are used in
calculations such as coverage predictions, etc.
Computation zone: The computation zone is used to define which base stations are to be taken into consideration
in calculations and the area where Atoll calculates path loss matrices, coverage predictions, etc.
Focus zone and hot spots: The focus zone and hot spots define the areas of coverage predictions or other
calculations on which you want to generate reports and results.
Printing zone: The printing zone allows you to define the areas to be printed.
Geographic export zone: The geographic export zone is used to define part of the map to be exported as a bitmap.
2.2.16 Integrated Cartography Editors
Atoll’s GIS enables editing geo data objects as well as network elements using dedicated editing tools within Atoll. Vector,
clutter, and traffic data can be edited within Atoll.
Vector Data Editor
Atoll incorporates a vector data editor. You can create, edit, and delete polygons, lines, and points. Additional operations
such as splitting, combining, or intersecting are available for polygons. The created objects can be stored locally or integrated
into a reference geographic database. The vector data editor is presented in the figure below.
Figure 2.38 Vector data editor
Clutter Data Editor
Clutter data can be edited in Atoll. You can create, edit, and delete existing/new clutter data. These modifications can be kept
locally or integrated into a reference geographic database. The figure below shows the clutter editor dialog box.
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Figure 2.39 Clutter editor
Traffic Data Editor
Atoll incorporates a traffic data editor. You can create, edit, and delete existing/new traffic data. Both vector (traffic value
associated with a line, polygon or point) and raster (traffic density value associated with each pixel) traffic data can be
modified. These modifications can be kept locally or integrated into a reference geographic database.
2.2.17 Worldwide Coordinate Systems Database
Atoll’s default coordinate system library includes more than a thousand different coordinate systems. All standard coordinate
systems are supported, as well as many regional and local ones. You can create and edit coordinate systems as required.
Atoll uses two coordinate systems simultaneously:
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The “projection” (main) coordinate system: This is the actual geographic database coordinate system.
The “display” (secondary) coordinate system: All geographic coordinates are displayed and entered according to
this coordinate system. If the selected display coordinate system differs from the projection coordinate system,
Atoll makes the required conversion between the two. This feature allows easy integration of external data such as
survey data or GPS coordinates.
The figure below shows the Atoll coordinate system settings window.
Figure 2.40 Coordinate system settings
2.2.18 Units
The following units are available in Atoll:
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Radiated power:
Antenna gain:
Transmission:
Reception:
Distance:
Height and offset:
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ERP, EIRP
dBi, dBd
dBm, W, kW
dBm, dBμv, dBμv/m, V/m
m, km, mi
m, ft
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Temperature:
°C, °F
Calculation and Memory Management
Atoll is designed to process large volumes of network and geographic data at input and output. Efficient memory
management algorithms enable Atoll to optimise memory usage and provide optimum performance when accessing and
processing network and geographic data as well as calculation results.
As a native 64-bit application, Atoll is capable of accessing and efficiently utilising more than 4 GB of memory, which is the
limit for 32-bit applications. This also enables Atoll to use large contiguous memory segments to handle large amounts of
data and perform complex calculations. Atoll 64-bit provides extensive computation capabilities in demanding tasks such as:
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Loading and working with large, country-wide network data
High-resolution path loss calculation with large calculation radii
Monte Carlo simulations with a large number of mobiles distributed over large areas
Neighbour calculations
Report generation on prediction plots over large geographical areas (e.g., country-wide)
Interference matrix generation with a large number of transmitters
AFP and ACP over large geographical areas
Figure 2.41 USA-wide multi-technology network
During calculations, Atoll allocates and frees memory in an incremental manner using algorithms that take into account the
size of the network and geographic data that must be loaded for the task at hand. If needed, Atoll dynamically divides large
map objects into smaller chunks which can be loaded as needed without exceeding the available physical memory.
Atoll
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Installed on
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Microsoft Windows 32-bit
Microsoft Windows 64-bit
Microsoft Windows 64-bit
Memory limit
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2 GB / 3 GB(1)
4 GB
2000 GB(2)
Atoll 32-bit
(1)
(2)
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Atoll 64-bit
3 GB with the 4GT mode enabled. For more details, refer to the Microsoft article here.
This corresponds to the physical memory limit of Microsoft Windows Server 2008 R2
Datacenter and Enterprise versions. For a detailed list of memory limits of different
versions of Microsoft Windows, refer to the Microsoft article here.
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Propagation Models
Atoll includes a comprehensive catalogue of integrated and optional propagation models. Atoll’s propagation model library
includes empirical, statistical, deterministic, ray-tracing, as well as advanced universal propagation models. Atoll’s
propagation calculation engine provides a high level of performance thanks to the following features:
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Incremental prediction updates: Before calculating path loss matrices, Atoll detects differences between the
current network configuration and the previous one. Only out-of-date path loss matrices and the related coverage
predictions are updated.
Dynamic data extraction: Atoll supports calculations over large networks using dynamic data extractors which load
and unload only the required data (geographic data and path loss results) during the calculation process. This
calculation architecture prevents memory saturation when working with large networks.
Multi-resolution geographic data: Atoll generates composite path profiles during calculations extracting data from
multi-resolution geographic data objects. For more information, see 2.2.2 Multi-resolution Geographic Database.
Multi-resolution prediction: Atoll provides the possibility to set and use different calculation resolutions for
different transmitters. Each transmitter can also have two different calculation resolutions and radii.
Interference calculation thresholds: Minimum interfering signal cut-off values can be defined in order to restrict
the calculation of interference within reasonable RF limits. Absolute (e.g., -120 dBm) and relative (e.g., 20 dB below
the thermal noise level) cut-off values can be defined.
Joint calculation of path losses for co-site co-located transmitters: Atoll calculates path loss matrices of co‐located
co‐site transmitters in a single step, i.e., per site, instead of calculating each transmitter’s matrix separately. Path
losses comprise two mutually independent components: the path loss due to electromagnetic wave propagation
and the attenuation due to antenna patterns. The first component, which is the most time consuming, is the same
for all co‐located co‐site transmitters. Therefore, Atoll is able to provide high performance by calculating path loss
matrices per site.
Propagation models can be tuned and calibrated within Atoll using CW measurements and drive test data. For more
information, see 16.3 Propagation Model Calibration. Atoll includes propagation models specifically for use in microwave link
planning and analysis. Atoll also enables integration of 3rd party propagation models via a dedicated API. For more
information, see 2.11 Scripting and Customisation.
2.4.1 Integrated Propagation Model Library
Atoll includes numerous propagation models suitable for all radio access and microwave transmission frequencies. Atoll
includes the following propagation models in its default library:
Aster Propagation Model
The Aster propagation model (option) is a high-performance advanced ray-tracing propagation model developed by Forsk. It
supports all radio access technologies and especially suits urban and dense urban propagation environments with small cells.
Aster can provide highly accurate propagation results using high resolution raster building data for vertical and horizontal
diffraction calculations in addition to vector building data. Aster comes with default macro, micro, and small cell
configurations, as well as pre-calibrated parameters for rural environments. It can be optionally tuned using measurements.
Figure 2.42 Propagation phenomena in Aster
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Angles
Corner
Figure 2.43 Aster ray-tracing
Aster offers a unique versatile approach to input data. It can carry out calculations based on clutter classes, ray-tracing based
on raster as well as vector building data without the need of pre-processing vector data. Using advanced ray-tracing
techniques, Aster is able to accurately model horizontal radio wave propagation along the streets in small cell deployment
scenarios where cells are mostly located below the average rooftop.
Figure 2.44 Example of a signal level prediction using Aster
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CrossWave Propagation Model
The Atoll CrossWave propagation model (option) is a universal high-performance propagation model developed by Orange
Labs. It supports all radio access technologies and all types of propagation environments, from rural to dense urban areas,
and is capable of providing highly accurate propagation results even without prior calibration or tuning. The CrossWave model
is delivered pre-calibrated to match numerous types of propagation environments, but it can optionally be tuned using CW
measurements.
Figure 2.45 CrossWave propagation model properties
The CrossWave model provides realistic results by combining various propagation phenomena such as vertical diffraction,
horizontal guided propagation, and reflection. Optimised wave propagation calculation methods are available for over and
through forests and above water. As well, the model includes specialised methods are available for outdoor-to-indoor and
indoor-to-outdoor penetration calculations.
Figure 2.46 Propagation phenomena in CrossWave
In addition to traditional geographic data (DTM, clutter classes, clutter heights, etc.), more accurate calculations can be
carried out using the CrossWave model by providing it with vector data, such as 3D building polygons and route/railway lines.
In small cell deployment scenarios, where cells are mostly located below the average rooftop, propagation mostly occurs
horizontally along the streets. The CrossWave model can model this wave-guide-like behaviour of roads and streets using
graphs of street axes automatically calculated based on building vector data. The model determines all the contributing
signals from a cell along multiple paths provided by the graph.
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Figure 2.47 Example of a graph of street axes in an urban area
Figure 2.48 CrossWave propagation calculation
Standard Propagation Model (SPM)
This is a general model based on the Hata empirical formula with optional adjustments for diffraction and clutter. The
supported diffraction methods are: Deygout, Epstein-Peterson, Deygout with correction, and Millington. Several effective
antenna height algorithms are available including base height, spot height, average, slope, profile and absolute spot height.
An example of signal level calculation using the SPM is shown in the figure below.
Figure 2.49 SPM signal level prediction using building database and indoor clutter loss
3GPP 38.900 Propagation Model
The 3GPP 38.900 propagation model is based on the 3GPP TR 38.900. This report describes the "Study on channel model for
frequency spectrum above 6 GHz" and covers the channel models for frequencies above 6 GHz up to 100 GHz. Research and
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studies carried out by other companies and groups have largely contributed to the finalisation of this technical report. These
research works include projects such as the WINNER, WINNER II, METIS, ITU-R M, NYU WIRELESS, and other projects.
The 3GPP 38.900 propagation model is a semi-deterministic propagation model that covers various propagation scenarios.
Each propagation scenario uses defined sets of empirical formulas for line-of-sight (LoS) and non-line-of-sight (NLoS)
propagation. The coefficients of the path loss terms in these formulas can be user-defined and automatically calibrated using
measurement data. The 3GPP 38.900 propagation model is semi-deterministic in the sense that it applies empirical formulas
to calculate the path loss along transmitter-receiver profiles for which the LoS/NLoS status is determined based on actual geo
data (instead of LoS/NLoS probabilities as suggested in the 3GPP TR 38.900).
Okumura-Hata and Cost-Hata Propagation Models
Hata models in general are well suited for the urban environment. You can define several corrective formulas and associate
a formula with each clutter class to adapt the Hata model to a wide variety of environments. Additionally, the models can
use the Deygout diffraction method to calculate diffraction losses based on the DTM.
Sakagami Extended Propagation Model
The Sakagami Extended propagation model is based on a simplified version of the extended Sakagami-Kuboi propagation
model. The Sakagami Extended propagation model is valid for frequencies above 3 GHz.
Erceg-Greenstein Propagation Model
The Erceg-Greenstein (SUI) propagation model is suited for predictions in the 1900 and 6000 MHz range over distances
between 100 m and 8 km. The Erceg-Greenstein (SUI) propagation model is suited for WiMAX. The Erceg-Greenstein (SUI)
propagation model is well adapted for suburban environment. You can define several corrective formulas and associate a
formula with each clutter class to adapt the model to a wide range of environments.
ITU 1546 Propagation Model
The ITU 1546 propagation model is suited for predictions in the 30 to 3000 MHz range over distances from 1 to 1000 km. It
is appropriate for point-to-area predictions such as broadcast and land and maritime mobile services, and fixed services
employing point-to-multipoint systems. It uses the terrain profile to calculate propagation. This propagation model is based
on graphs of field strength as a function of distance provided in the ITU recommendations for different operating frequencies.
ITU 529 Propagation Model
The ITU 529 model is suited for predictions in the 300 to 1500 MHz range over long distances (from one to 100 km). You can
define several corrective formulas and associate a formula with each clutter class to adapt the ITU 529 model to a wide variety
of environments. Over long distances (20km<d<100 km), the model uses the corrective formula defined in the ITU
recommendation.
ITU 526 Propagation Model
The ITU 526-5 model is suitable for predictions in the 30 to 10000 MHz range with fixed receivers. According to the ITU 526
recommendations, if there are no obstacles, the propagation takes place in free space, and if there is an obstacle, attenuation
due to diffraction is calculated. The model uses the terrain profile and a diffraction mechanism (3-knife-edge Deygout
method), optionally with correction, to calculate path loss.
ITU 1812 Propagation Model
The ITU 1812 propagation model is suited for predictions in the 30 to 3000 MHz range over distances from 0.25 to 3000 km.
It is appropriate for point-to-area predictions such as broadcast and land and maritime mobile services, and fixed services
employing point-to-multipoint systems. The ITU 1812 recommendation takes into account propagation phenomena such as
diffraction (embracing smooth-Earth, irregular terrain and sub-path cases), tropospheric scattering, ducting and layer
reflection/refraction, and height-gain variation in clutter.
ITU 452 Propagation Model
The ITU 452 propagation model is suited for interference predictions in the 100 to 50000 MHz range over distances up to
10000 km. The ITU 452 recommendations take into account interference propagation phenomena such as diffraction,
tropospheric scattering, surface ducting, elevated layer reflection and refraction, and hydrometeor scattering (for MW
transmitters).
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ITU 370 Propagation Model
The ITU 370 model is based on the recommendations of the Vienna 1993 international conference on telecommunications
network coordination. This model is suited for predictions in the 100 to 400 MHz range over long distances (over 10 km), such
as in broadcast predictions. It uses the terrain profile to calculate propagation.
Longley-Rice Propagation Model
Longley-Rice is a theoretical model suited for predictions in the 40 MHz band in flat areas. The Longley-Rice propagation
model uses the terrain profile to calculate propagation. However, the parameters of the Longley-Rice propagation model can
be set using distance and an additional loss value.
2.4.2 Optimised Multi-resolution Path Loss Calculations
Atoll provides the possibility to set different propagation models, calculation radii, and resolutions per sector. This enables
radio planners to match the required accuracy of the calculation results to the environment of different sectors. For example,
predicting coverage for a rural area populated with few subscribers may require less accuracy than predicting coverage for
an urban area.
The calculation resolutions for path loss matrices are independent of the resolutions of the underlying geographic data
objects. This provides you a means to adjust the calculation accuracy as required. It is also possible to set two different
resolutions for each sector providing even further flexibility in terms of the required precision of the calculation results.
Atoll performs accurate and optimised path loss calculations: the path loss value stored for each pixel is accurate up to 1/16th
of a dB. Atoll’s matrix-based calculation approach, as opposed to more basic radial calculations, delivers a high level of
accuracy regardless of the transmitter-receiver distance. Compared to the matrix-based calculations, the radial approach
loses accuracy as the distance between the transmitter and the calculated pixel increases. For example, using the matrix
calculation method with a resolution of 20m, path losses are systematically calculated every 20m. On the other hand, using
the radial method with a 1° step, path losses are calculated every 1.75m at 100m from the transmitter location, and every
600m at 35km from the transmitter location.
Figure 2.50 Matrix vs. radial mode calculations
Atoll also provides the possibility to tune calculated path loss matrices using actual network measurements with drive test
data. For more information, see 16.4 Path Loss Tuning.
Coverage prediction plots can be calculated using different resolutions, independent of the path loss and geographic data
resolutions. Dynamic interpolation between multi-resolution geographic data and path loss results enables Atoll to predict
coverage according to the user-defined resolution. Coverage prediction maps are displayed and managed as any other
geographic data object, i.e., with the possibility to set transparency levels, multi-layer tooltips, and the order of appearance
on the map.
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Figure 2.51 Coverage prediction and path loss calculations using 2m and 20m resolutions for the same sector
Figure 2.52 Multi-resolution matrix definition
Atoll includes a path loss matrix optimisation function that automatically calculates the suitable calculation radii for path loss
matrices according to minimum required signal levels at the farthest location in the matrix. Different minimum signal levels
can be defined for different technologies in a multi-RAT environment. This optimises the sizes of path loss calculation result
files.
2.4.3 Open Interface to External Propagation Models
Atoll’s development kit provides a specific API to support the integration of external propagation models. For more
information, see 2.11 Scripting and Customisation.
2.4.4 Propagation Model Calibration
Atoll is capable of importing and processing measured data. The Okumura-Hata, Cost-Hata, and standard propagation models
can be automatically and manually calibrated using CW measurements and drive test data. For more information, see 16.3
Propagation Model Calibration.
2.4.5 Real-time Transmitter-to-Point Profile Prediction
Atoll includes a ‘transmitter to point’ prediction tool that provides you with a real-time prediction between a selected
transmitter and the mouse pointer. The point analysis window presents the path profile, the vertical half-power beamwidth
and the current tilt of the antenna, and key propagation information such as distance, altitude, clutter type, received signal
strength, shadow margin, loss per diffraction, Fresnel zone, etc.
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Figure 2.53 Point analysis window
2.4.6 Link Budget Tool
Atoll offers an integrated link budget analysis tool. For each transmitter, you can view the link budget statistics (distance,
power, EIRP, receiver gain, path loss, shadowing margin, and signal level) at the selected receiver location. The figure below
shows a link budget example.
Figure 2.54 Link budget analysis tool
Network Data Management
Atoll’s user interface is designed to enable you to easily manage and quickly access all sorts of data: network database, geo
data, configuration parameters, and calculation results. In addition to the map window, Atoll’s explorer windows provide
access to different data objects in the form of network planning and optimisation oriented tree views. Explorer windows
contain folders, and subfolders, which allow items to be grouped, filtered, and sorted, based on user-defined map regions or
user-defined flags in the corresponding data tables.
Atoll’s data tables and the backend databases can also be fully customised to include user-specific fields. User-defined fields
and data can then be used in Atoll for filtering, sorting, searching, and display settings, etc. Atoll’s network data tables also
facilitate editing and modifying multiple records in order to simplify long and repetitive tasks.
Atoll delivers a comprehensive set of data management features that allow you to easily handle large amounts of data. A few
key features are described below.
2.5.1 Network Data Import and Export
Atoll enables direct interfacing with external data sources and applications. Data can be imported to and exported from Atoll
data tables in various formats including simple text, CSV, MS Excel, and XML Spread Sheet formats. Data can be copied to and
pasted from Atoll data tables to MS Excel and other spread sheet software. In addition to copying and pasting in data tables,
Atoll also allows geo data import by dragging and dropping from the Windows explorer.
Atoll enables importing network data (sites, transmitters, cells, antennas, etc.) from external databases through various
means:


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
Direct import of ASCII TXT or CSV files
Full as well as partial database import/export using XML files
Direct import of Planet files
Through a custom import tool developed using the Atoll development kit. For more information, see 2.11 Scripting
and Customisation.
In addition to data tables, calculation outputs such as Monte Carlo simulation results and coverage prediction reports, can
be exported to text, CSV, MS Excel, and XML Spread Sheet files. This export function enables possible externalised archiving
or post-processing of simulation results in another application.
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2.5.2 Network Element Creation and Editing
Sites and transmitters can be created by:



Adding a site/transmitter directly on the map using the site template tool. This allows the creation of multiple multisector stations in a single step.
Entering parameters in the site/transmitter window
External data import (from ASCII text, CSV, or Excel files)
Atoll is capable of listing all the sites and transmitters along with all their respective parameters in a single table. An extract
from a transmitters table is presented in the figure below. Such a table provides convenient editing of the parameters.
Figure 2.55 Transmitters table
2.5.3 Network Element Selection
Multiple sites or transmitters can be selected on the map or in the explorer window using the mouse. This allows quickly
grouping and filtering network elements for calculations and analyses. Selecting multiple sites or transmitters also allows you
to compare the properties of the selected elements, as shown in the figure below.
Figure 2.56 Transmitter comparison example
A search tool is also available to help the user easily and quickly find a site or transmitter in the network.
2.5.4 Network Element Grouping
Sites or transmitters can be grouped by any of their parameters. Grouping can be performed in different ways:

Selecting multiple sites or transmitters on the map or in the explorer window, right-clicking to open the context
menu and selecting the Group by Selection command.
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Through the sites or transmitters folders.
Through a query function in which multiple grouping criteria can be combined, as shown in the figure below.
Figure 2.57 Transmitter grouping query function
The figure below gives an example of a GSM transmitter folder grouped in two different ways.
Figure 2.58 Transmitter grouping examples
2.5.5 Network Element Filtering
Sites or transmitters can be filtered by any of their parameters. Only the filtered sites and transmitters are taken into account
in calculations. Filtering can be performed in different ways:

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

Selecting multiple sites or transmitters on the map or in the explorer window, right-clicking to open the context
menu and selecting the Filter by Selection command.
By drawing or importing a filtering polygon as shown in the first figure below
Through the sites or transmitters tables as presented in the figure below that
Through a query function, in a similar manner to the grouping option, where multiple filtering criteria can be
combined.
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Sites filtered inside
user-drawn polygons
Figure 2.59 Site filtering using a user-drawn polygon
Figure 2.60 Site filtering through table
2.5.6 Network Element Sorting
Sites/transmitters can be sorted by any of their parameters. Sorting can be performed in two different ways:


Directly, by using the site/transmitter tables in a similar way to the filtering option
Through a query function, in a similar way to the grouping option, where multiple sorting criteria can be combined.
2.5.7 Network Element Lists
Static site and transmitter lists can be created, edited and deleted in Atoll. Import and Export functions are also available.
The figure below shows the dialog box of the site list management.
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Figure 2.61 Site list management
It is also possible to create site or transmitter lists by selecting multiple sites or transmitters on the map or in the explorer
window, right-clicking to open the context menu and selecting the Add to List command.
2.5.8 User Configurations
You can export the current configuration of your project or import existing ones in order to apply predefined settings to your
project. This enables sharing user-defined project configurations among different projects from the same user or from
different users. A user configuration file is made up of the following information (or a subset of it):

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Geographic data set: Geographic data file paths and display properties
Map centre and zoom level: Current view of the map window
Zones: Definition of the computation, focus, hot spot, printing, filtering, and geographic export zones
Network data table configuration: Table column order, width, colours, text alignment, character format, and
visibility status for data tables containing network data
Folder configuration: Grouping, filtering, and sorting configurations of the folders in the explorers
Automatic neighbours allocation parameters
Automatic scrambling code allocation parameters (UMTS and TD-SCDMA)
Automatic PN offset allocation parameters (CDMA2000)
Automatic frequency planning parameters (GSM)
Automatic frequency planning and physical cell ID planning constraint weights (LTE/NB-IoT)
Automatic frequency planning and preamble index planning constraint weights (WiMAX)
Prediction list: List and parameters of the coverage predictions defined in the project
Macros: Path to any macro files used in the project
The figure below shows the dialog box of the user configuration export function.
Figure 2.62 User configuration file export
Network Lifecycle Management
Atoll can manage multiple versions of network elements. It is possible to create different versions of any sector representing
stages or phases of deployment. Network lifecycle management in Atoll allows you to:


Configure as many versions as needed to manage your network lifecycle
Create and assign multiple versions of sectors
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Switch between different versions
Filter sectors by version
Compare differences between parameters of different versions by focusing on fields with different values.
The figure below shows an example of a network lifecycle.
Figure 2.63 Network element lifecycle example
In this example, “on-air” represents the current network without planned modification (final status in the lifecycle), “under
construction” represents on going modification, “planned” status represents planned modifications, “under study”
represents future changes to the network, and “undefined” implies sectors that are out of scope of the network evolution
process.
The figure below shows an example of sector version comparison dialog box.
Figure 2.64 Network element comparison
The network lifecycle management process applies to sectors, cells, subcells, TRXs, repeaters, remote antennas, and
secondary antennas.
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Database and Multi-user Management
Atoll supports multi-user configurations using database management systems. Supported database management systems
are listed in 1.3 Supported Database Management Systems. A typical multi-user configuration is presented in the figure
below. It includes:

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
Several Atoll workstations and laptops
A database server installed on a Windows or UNIX server
Geographic data and path loss results stored on dedicated servers or locally on each computer
Atoll installed on a centralised (Citrix) server or locally on each computer
Figure 2.65 Example of a multi-user configuration
In a multi-user environment, different pieces of information, input and output data, can be shared between users. Atoll allows
users to share the following data and information, according to their account rights and privileges:

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Units and coordinate systems
Radio network data (sites, antenna, transmitters, etc.)
Traffic data
Propagation models
Neighbours
Geographic data file paths and descriptions
Coverage prediction list and definition
Folder configuration
Computation, focus, filtering, printing, and other polygon zones
Path loss matrices
Coverage prediction results
The Atoll management console facilitates the management of Atoll databases, project templates, user accounts with
associated access rights and privileges. This tool enables the administrator to:
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
Create databases
Upgrade Atoll databases from one Atoll version to the next
Manage multi-level databases
Manage data modifications history in databases
Manage user accounts and privileges
The Atoll management console is presented in the figure below.
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Figure 2.66 Atoll Management Console window
2.7.1 Customisable Multi-technology Database Model
An Atoll database consists of a set of tables that describe a single-RAT or multi-RAT network. Each new project is created
based on an Atoll database template used initialise the database structure. Atoll database templates not only define the data
structure but also the default settings and initialisation parameters such as frequency bands, antenna database; propagation
model parameters, etc. Atoll database templates can be edited, created, and deleted by the user. The default template list is
shown in the figure below.
Figure 2.67 Default Atoll database templates
Each project type in Atoll corresponds to a database structure specifically designed to meet the requirements of the
technologies being modelled. All database structures include data tables that define:
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The network model (sites, transmitters, cells, repeaters, etc.)
The network configuration (frequency bands, etc.)
The radio equipment (antennas, feeders, reception equipment, etc.)
The traffic model (services, terminals, user profiles, etc.)
User-defined fields and flags can be integrated in the database structure. Any table can be customised to meet the
requirements of your project. This feature facilitates a smooth migration of an existing database to Atoll. The figure below
shows an example of data table customisation directly through the Atoll user interface.
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Figure 2.68 Database structure customisation
Note that the Atoll database templates can be customised in a similar manner, facilitating integration of new projects based
on user-defined templates.
2.7.2 Database Management
Atoll’s built-in database management system enables users to control data integrity and to consolidate work between users.
Users work on local workspaces (Atoll projects) linked to a reference database. Local workspaces are typically initialised by
uploading the reference database. Atoll does not require a permanent connection between the local workspaces and the
reference database. This enables users to:


Easily manage multiple “what if” scenarios
Work in a non-connected mode (e.g. in the field with a laptop) with an automatic synchronisation with the reference
database at reconnection
Data exchange between the local workspaces and the reference database are dealt by:


The archive function: updating the reference database with the modifications
The refresh function: loading data from the reference database to the Atoll document.
During an archive process, Atoll automatically generates the list of modifications, which then may or may not be committed.
The figure below gives such an example. In addition, details of each modification can be edited as shown in the figure below.
A change report can be generated when refreshing from the reference database to see changes made by other users since
the last project update.
Figure 2.69 Database archive: Automatic generation of the list of modifications
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Figure 2.70 Database archive: Change details
Atoll is capable of automatically detecting conflicts between changes made by different users, i.e., when different users
modify the same data. Atoll also includes a set of functions that allows you or the administrator to resolve any encountered
conflicts. The figure below gives a conflict management example.
Figure 2.71 Multi-user conflict detection and resolution
2.7.3 Multi-level Database Management
The Atoll management console enables data administration in a multi-level Oracle and MS SQL Server database environment.
It brings an additional level of data integrity control and security. A typical scenario, that includes a nationwide (master)
database and several regional (project) databases, is shown in the figure below.
Figure 2.72 Multi-level database environment
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All regional databases are linked to the nationwide database. Regional databases are typically initialised by loading the
relevant portion of the nationwide database using the Atoll management console. Each regional database is managed as
described in 2.7.2 Database Management. In a particular region, users work on local workspaces (Atoll projects) linked to
their regional database.
Data exchange between regional databases and the nationwide database are dealt by:


The archive function: updating the nationwide database with the regional modifications
The refresh function: updating the selected regional databases with data from the nationwide database
The corresponding dialog box is shown in the figure below.
Figure 2.73 Multi-level database administration
2.7.4 Multi-Operator RAN Management and RAN Sharing
The Atoll scenario manager is a specialised tool designed to facilitate the creation of specific projects and environments by
means of “scenarios”. It enables dynamic loading of radio network elements and attributes based on various criteria (content,
geographic areas, etc.). A RAN scenario in Atoll is defined by a geographic area (polygon regions), network elements (site and
sector filters), and attributes (custom fields and groups). The Atoll scenario manager enables data segregation based on
“scenarios”.
RAN sharing using the Atoll scenario manager involves three simple steps:
1.
2.
3.
Connect: The user connects with his Oracle credentials
Select: The user selects a scenario and a geographic area
Load: An Atoll document is created and data loaded for the selected area according to the scenario definition
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Figure 2.74 RAN sharing using the Atoll scenario manager
Atoll scenario manager supports regionalisation based on polygons used as geographic constraints, definition of user rights
for specific regions, and association of multiple scenarios with multiple regions. User profiles can be created as required, and
can be associated with one or more users and with one or more scenarios.
2.7.5 Data Modifications History Management
The Atoll management console allows you to keep and manage the history of modifications made in the network data by
different users. The history management tool keeps track of all the modifications made in the network data tables. The history
management tool is available for all technologies supported by Atoll and projects connected to Oracle database.
In addition to manual purges, regular purges of the data modifications history can be scheduled by the administrator as
required.
User Management
Atoll provides comprehensive user and user group management features as well as multi-level user privilege definition. User
accounts can be created for each database, central or regional, and user privileges can be defined for database tables,
columns, and records, as well as for various components of the Atoll’s user interface.
Figure 2.75 User account and privilege management
The following categories are available for database access rights:

No access: Users without read and write access to the database. The database is not visible to these users and they
are not allowed to create Atoll documents based on this database.
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Read-only: Users allowed to create Atoll documents from the database but without write permissions to any table
of the database, i.e., users cannot archive changes made in the Atoll document connected to the database.
Standard: Users with read and write access to network data tables.
Super-user: Users with read and write access to all the tables of the database.
Access rights to Atoll user interface elements can be managed as follows:

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
Access to radio data:
o Full: Users with read and write access to all the tables and properties dialog boxes.
o Standard: Users with read and write access to radio network data tables and properties dialog boxes.
o Read-only: Users with read-only access to tables and properties dialog boxes, i.e., users are not allowed
to modify radio network data and parameters.
Access to calculation settings:
o All: Users with read and write access to all coverage predictions, their calculation settings, and to
microwave calculation settings.
o Standard: Users with access to customised coverage predictions only, and allowed to modify coverage
conditions and display settings and the microwave calculation settings.
o Customised only: Users with access to customised coverage predictions only, but not allowed to modify
coverage conditions and display settings. These users do not have access to the microwave calculation
settings.
Access to propagation models:
o Full: Users with read and write access to all propagation models and their properties.
o Read-only: Users with read-only access to the properties of all the propagation models. Adding and
deleting propagation models is also not allowed.
Password confirmation:
o Yes: These users are asked to enter the password every time when opening a document connected to this
database or creating a new document from this database.
o No: These users are not required to enter the password every time when opening a document connected
to this database or creating a new document from this database.
Calculation Result Reports and Statistics
Atoll can generate reports on calculation results for user-defined zones. These reports contain statistical information (surface,
traffic, and clutter-based) related to the selected coverage prediction. Custom reports are also available using Atoll macros
and scripts. The figure below gives an example of a coverage prediction report for the focus zone.
Figure 2.76 Coverage prediction report on the focus zone
The focus and hot spot zones, over which reports can be generated, are usually different from the computation zone, over
which the calculations are carried out. This enables you to focus on specific sites in the generated reports. For example, the
figure below gives an example of how to exclude border sites from a report. As many focus zones and hot spots can be defined
for report generation as required.
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Computation zone
(Prediction Study
Calculation Area)
Focus zone
(‘Report
Zone’)
Figure 2.77 Computation zone and focus zone
Moreover, coverage prediction histograms and CDFs can also be viewed. It is also possible to compare these graphs of two
similar coverage predictions, for example, in order to see the effects of parameter tuning and optimisation. The figure below
shows a histogram window comparing two service area predictions.
Figure 2.78 Comparison of histograms of two service area predictions
2.9.1 Printing
Atoll supports all plotters/printers with drivers available for Microsoft Windows operating systems. All paper sizes, up to A0,
are handled. The area to be printed can be graphically defined in the map window. Other parameters such as legend position,
legend content, scale, etc. are also user-definable. Atoll prints the visible map layers with their respective transparency levels.
2.9.2 Exporting
Atoll includes numerous export functions enabling smooth interfacing with other software. Reports can be exported in ASCII
TXT, CSV, MS Excel, and XML Spread Sheet formats. Coverage predictions can be exported in numerous raster and vector
formats. Numerical values of coverage prediction results can be exported in BIL, Vertical Mapper GRD, and TXT formats.
Distributed Computing and Multi-threading
Atoll supports distributed calculations and multi-threading, i.e., calculations carried out on several computers with multiple
multi-core processors. Atoll provides the following advanced computing capabilities:

Calculations on multi-core workstations and servers
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Calculations are performed using all cores for enhanced performance.
Background calculation
Atoll carries out calculations in the background enabling you to continue to perform other actions in Atoll.
Automated calculations in batch mode
Calculations can be (scheduled to) run in a batch mode, where Atoll carries out tasks in a pre-defined sequence.
You can, for example, use Atoll to automatically create, calculate/update, and export coverage predictions for a
given network region on a daily basis, or for the daily update of the path loss matrices on a large country-wide
network.
Distributed computing for path loss calculations
Path loss calculations can be performed over a number of workstations and servers over a network (as shown in
the figures below).
Multiple instances of Atoll distributed calculation service can be run on designated calculation servers over a network in order
to distribute the task of calculating path loss matrices. Combined with multi-threading, this feature enables Atoll to make full
use of available hardware resources on multiple computers for calculations. For example, 4 calculation servers with 16 cores
each can calculate 64 path loss matrices simultaneously.
Figure 2.79 Distributed computing over workstations in a network
Figure 2.80 Distributed computing over dedicated calculation servers
Scripting and Customisation
Atoll includes scripting features and capabilities for customisation and integration with other, in-house or 3rd party, software.
Atoll provides access to data, import/export, calculations, etc., via the Atoll API (application programming interface).
The Atoll API enables users to add their own functions to the Atoll user interface. It allows integrating a wide range of
applications and interfaces to other software.
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2.11.1 Scripting
Atoll’s scripting features enable scheduling frequent user actions, such as path loss result updating, database synchronisation,
coverage plot calculation, etc., using simple VBScript routines. This enables regular execution of repetitive actions and
resource-consuming tasks.
An example of scripting in Atoll could be calculating a country-wide coverage map and exporting it to a PNG file for publication
on a website. An Atoll script can carry out this task on a regular basis while also taking care of any preliminary actions that
may be required, for example, the Atoll document may have to be synchronised with the database and path loss matrices
may require recalculation before proceeding to calculating the coverage map.
Scripts can be written directly within Atoll and scheduled using the Windows task scheduler. Once set up, the defined series
of actions are performed automatically as scheduled.
Figure 2.81 A macro integrated in the Atoll user interface
2.11.2 Customisation
The Atoll API offers a set resources for the customisation and integration of Atoll extensions and plug-ins. The Atoll API is
based on a set of Microsoft COM (component object model) interfaces that allows communication between Atoll and external
modules.
The Atoll API makes it possible to integrate a variety of functions with Atoll, such as for example simulators, optimisation
tools, and post-processing add-ins. Dedicated interfaces are also available for adding propagation models to Atoll. Functionwise, the Atoll API comprises:


General API
Propagation model API
General API
The general API provides access to generic functions and data, such as network data and path loss matrices, to developers.
Custom modules developed using the Atoll SDK can add dedicated elements to the Atoll user interface. Custom modules can
be integrated into Atoll with dedicated toolbar icons, data folders, commands, menus, parameter settings, and dialog boxes.
Such modules also benefit from Atoll’s data management capabilities, and can even store data in Atoll document files and
databases.
The figure below provides an example of the Add-ins toolbar with custom toolbar buttons added for various functions (SingleRAT to multi-RAT document conversion, eMBMS planning and analysis, small cell planning, multi-storey predictions, export
to Google Earth, etc.
Figure 2.82 Various functions available through custom buttons in the Add-ins toolbar using the general API
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The figure below shows an example of a custom dialog box added to the Atoll user interface.
Figure 2.83 Custom dialog box for eMBMS planning and analysis added to the Atoll user interface
Data can be exported and processed using an external application by clicking a toolbar button added through the general API.
For example, the site data, transmitter data, coverage prediction results, and microwave link data can be exported from Atoll
to Google Earth using the general API.
Figure 2.84 Export of sites, transmitters, coverage predictions, and microwave links to Google Earth via the API
Propagation Model API
The propagation model API is a dedicated API for integrating external propagation models with Atoll. The figure below shows
the Atoll propagation model library with a custom propagation model added through the API.
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Custom propagation model
Figure 2.85 Custom propagation model
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3 Atoll Live Features
The Atoll Live module allows operators to integrate live network data (CM6 data, PM7 data, KPIs8, UE9/cell/MDT10 traces, and
crowdsourced data) with Atoll’s advanced planning and optimisation features. The Atoll Live module adds live network data
management, processing and display features to Atoll, and enables measurement-based functionalities in technology and
optimisation modules. By combining measurement-based and prediction-based approaches, Atoll provides operators with
extended accuracy and a broader scope of use.
The following figure depicts the place of the Atoll Live module within a radio network planning and optimisation ecosystem
incorporating Atoll.
Figure 3.1
Schematic view of a radio network planning and optimisation ecosystem incorporating Atoll
Live Network Data Management in Atoll
The Atoll Live module enables acquisition of measured and analytics data from live networks. It enables updating the Atoll
radio network database with configuration management data, using KPIs/performance management data, UE/cell/MDT trace
collections, and crowdsourced data in various planning and optimisation activities in Atoll.
The Atoll Live module adds new folders to the Network and Parameters explorer windows in Atoll. These folders provide the
user with an intuitive and direct access to all functions relevant to live network data within Atoll:


Network explorer:
o KPIs: This folder contains all the imported KPIs and cell statistics. It also provides access to all the data
acquisition and analysis features related to KPIs.
o UE Traces: This folder lists all the live connections to UE/cell/MDT trace sources. It also provides access
to all the data acquisition and analysis features related to UE/cell/MDT traces.
Parameters explorer:
o KPI and UE Trace Parameters: This folder contains the user-definable KPI definitions and UE trace mapping
parameters.
6
CM: configuration management
PM: performance management
8 KPI: key performance indicator
9 UE: user equipment
10 MDT: minimisation of drive tests
7
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Figure 3.2
GUI elements related to the Atoll Live module
Live Network Data Import
The Atoll Live module enables accessing live network data (CM data, PM data, KPIs, UE /cell/MDT traces, and crowdsourced
data) from different sources using vendor-neutral or OSS-specific interfaces, as well as through direct connections to
databases. Once imported, live network data can be displayed and analysed in Atoll and used in network planning and
optimisation features.
Forsk has agreements with major equipment vendor partners through the OSSii (Operations Support Systems interoperability
initiative) initiative. The aim of the OSSii initiative is to enable OSS interoperability between different OSS vendor’s
equipment; it allows independent software vendors (ISVs) like Forsk to interface their products with equipment suppliers
through a comprehensive framework from specifications to integration testing.
The OSSii agreements authorise Forsk to develop specific interfaces between Atoll and various vendor OSS systems. These
dedicated interfaces, called OSS Interfaces for Atoll, are available from Forsk and enable Atoll Live users to integrate KPIs and
UE traces into Atoll Live directly through vendor-specific OSS data output sources.
3.3.1 KPI/PM Data Mapping
The KPI definitions table enables operators to set up KPI definitions according to their own conventions. This also enables
operators to configure definitions to match various equipment used in the network and different data sources that may exist.
The KPI definitions table allows creating and modifying KPI characteristics from a pre-defined list of “predictable” KPIs (i.e.,
KPIs that can also be calculated by Atoll enabling comparisons between measured and predicted values, or by setting up a
custom definition according to a combination of the following parameters:










Category: The 3GPP category of the defined KPI: Accessibility, Retainability, Integrity, Availability, and Mobility. This
parameter is used by Atoll for filtering KPIs in different planning and optimisation features.
Measured Parameter: The radio parameter measured for the construction of this KPI: RSRP, RSRQ, RSCP, etc.
Unit: The unit of the KPI: Percentage, Time, kbps, dB, dBm, etc.
Reference Value: For KPIs whose unit is percentage, this value serves as the reference value of the measured
parameter with respect to which the KPI is evaluated.
Direction: Uplink, downlink, or all.
Min: The smallest value the KPI may have.
Max: The highest value the KPI can attain.
Target: Whether the aim of the operator would be to increase or decrease the KPI.
Threshold low: Value below which the KPI is considered “bad” (represented in red).
Threshold high: Value above which the KPI is considered “good” (represented in green).
Between Threshold low and Threshold high, the KPI is considered “acceptable” (represented in light orange).
Hence, the KPI definitions table is open, user-definable, and inherently multi-technology. Moreover, it can also contain
definitions matching various vendors in the same project.
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Figure 3.3
Example of a predictable KPI definition
Figure 3.4
Figure 3.5
Example of a custom KPI definition
Default multi-technology KPI definitions
3.3.2 KPI/PM Data Import
Multi-technology KPIs can be imported from various sources:



ASCII text files (TXT and CSV)
Oracle databases
MS SQL Server databases
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Figure 3.6
KPI import from various sources
Atoll can acquire two types of KPIs:


Performance statistics of individual network elements (call drop rates, served users, etc.)
Traffic flow (relationships) between network elements of the same or different technologies (numbers of
handovers, etc.)
Atoll can manage multiple KPI tables, each including multiple fields. The Atoll Live module supports customisable mapping
configurations for various sources, equipment, and technologies. Furthermore, specialised and dedicated interfaces can be
developed to directly access the operator’s KPI source using pre-configured parameters.
Figure 3.7
KPI import window
KPIs in Atoll can be updated as long as a connection with the data source is maintained. The update function downloads the
latest values of KPIs found in the KPI source and updates these in the Atoll document. This may be particularly useful when
the data source is managed by tools that update data from time to time to give the network planner with the most up-todate picture of network performance.
Figure 3.8
KPI context menu – Update command
3.3.3 UE/Cell/MDT Trace Mapping
The UE trace mappings table enables operators to set up UE/cell/MDT trace mappings according to their own conventions.
This also enables operators to configure mappings to match various equipment used in the network and different data
sources that may exist. The UE trace mappings table allows creating mappings between predicted radio parameters in Atoll
and measured UE/cell/MDT traces. For example, if the UE/cell/MDT trace source contains bit-wise representations of RSRP,
RSRQ, etc., these can be mapped to Atoll’s dBm and dB units using this table. It also allows filtering measurement values
outside the defined range.

Name: Name of the measured UE/cell/MDT trace parameter to map with Atoll.
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
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Measured Parameter: The measured parameter’s equivalent in Atoll.
Unit: Unit of the measured parameter.
Direction: Uplink, downlink, all, or undefined.
Min Reported Value: Lowest reported value of the measured parameter in the UE/cell/MDT trace source.
Max Reported Value: Highest reported value of the measured parameter in the UE/cell/MDT trace source.
Min Measured Value: Lowest measured value matching the lowest reported value of the measured parameter.
Max Measured Value: Highest measured value matching the highest reported value of the measured parameter.
For example, in order to map the bit-wise representation of RSRP to dBm, you can define:








Name: RSRP
Measured Parameter: RSRP
Unit: dBm
Direction: Downlink
Min Reported Value: 0
Max Reported Value: 97
Min Measured Value: -141
Max Measured Value: -44
If the min-max mapping is left empty, Atoll considers that the reported value is the same as the measured value.
Figure 3.9
Default UE/cell/MDT trace mappings
3.3.4 UE/Cell/MDT Trace Import
The Atoll Live module can connect Atoll documents to one or more sources of UE/cell/MDT traces. Atoll establishes a live
connection with the UE/cell/MDT trace source, which means that the latest and most up-to-date information is read from
the source whenever the UE/cell/MDT trace is used in planning and optimisation tasks.
Figure 3.10 UE/cell/MDT trace connections
The Atoll Live module supports connections to multiple UE/cell/MDT trace sources with customisable mapping configurations
for various equipment and technologies.
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Figure 3.11 UE/cell/MDT trace connection window
3.3.5 Configuration Management Data Import
Atoll Live can be complemented with dedicated, vendor-specific OSS interface tools developed by Forsk. Currently, these OSS
interface tools enable the operators to import configuration management data for:




Ericsson LTE: versions L13 to L18
Ericsson UMTS
Huawei LTE: versions SRAN11.1 to SRAN 13.1
Huawei UMTS
Configuration management data imported using the OSS interface tools is directly loaded to the network data tables:







Activity status (“on air” cells)
Frequency band and carrier
PCI (LTE) or PSC (UMTS)
Transmission power (LTE) or pilot power (UMTS)
Min RSRP (LTE), min RSCP (UMTS)
Intra-RAT and inter-RAT neighbour lists
Number of TRX antenna ports
3.3.6 GSM OSS Data Import
GSM network data can be obtained in the form of flat files from OSS configuration management tools of different equipment
vendors. The following live network data can be imported from GSM OSS:


Interference matrices
From Huawei MR files, Ericsson ICDM (.msmt and .conf) files, NSN DAC and CF files, ZTE CI files, and Alcatel RMS
and T180 files.
Traffic counters (CS traffic Erlangs, PS traffic, HR traffic ratio, cell traffic loads, etc.)
From Huawei TCHF and TCHH files, Ericsson FAS export files, NSN RX files, and ZTE RX files.
GSM OSS data can help improve the GSM network traffic analysis and capacity planning. These data can also be integrated
into the AFP process to improve the frequency planning results. As well, the Atoll GSM AFP can merge predicted and live
interference matrices from various sources, hence enhancing the quality of input data.
Live Network Data Display and Analysis
The Atoll Live module enables displaying live network data such as KPIs and UE/cell/MDT traces on the map as well as in data
tables, and allows performing various quick analyses before using the data in network planning and optimisation functions.
3.4.1 KPI Data Tables
Once imported, KPIs are available in Atoll in the Network explorer window under the KPIs folder. Each KPI item in the explorer
is associated with a data table that contains the imported KPI data. The KPI data table lists the actual values of KPIs imported
from the defined source.
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For each KPI with an assigned definition, the data table cells are coloured according to the KPI quality: good (above Threshold
high), acceptable (between Threshold high and Threshold low), or bad (below Threshold low). KPIs can be assigned definitions
at the time of import or later.
The KPI data tables are linked with the map window and any cell can be located on the map directly from within a KPI table.
Moreover, cell properties can also be directly accessed from within the KPI table. This enables quick analyses of the radio
environment around cells whose KPIs indicate performance issues.
Figure 3.12 Example of a KPI data table
3.4.2 KPI-Based Sector Display and Best Server Plots
The KPI data tables are linked with the network elements. Transmitter symbols on the map can be coloured and labelled
according to the quality levels of any related KPI. This enables geographical visualisation of sectors whose KPIs indicate
performance issues.
Figure 3.13 Transmitter representation on map based on KPIs
Similarly, per sector or best server coverage plots can be coloured according to KPI quality levels as shown in the figure below.
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Figure 3.14 Best server coverage plot representing KPI quality levels (red=bad; orange=acceptable; green=good)
3.4.3 UE/Cell/MDT Trace Locations and Density
UE/cell/MDT traces can be viewed on the map by clicking the display check box of the relevant UE/cell/MDT trace item.
Figure 3.15 UE/cell/MDT trace locations displayed on the map
Moreover, the geographic density of the UE/cell/MDT traces can be displayed as a heat map using the Atoll’s weighting map
feature. This map provides a global view of the density of points located on the map and can be used in the Atoll ACP to assign
more importance to pixels with higher traffic and less importance to pixels with low traffic. Atoll is capable of creating
weighting maps using indoor, outdoor, or both types of UE and MDT traces.
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Figure 3.16 Density map of UE/cell/MDT traces
Live Network Data Comparative Analysis
Atoll provides simple means to compare two sets of KPIs as well as to compare KPIs with the same parameters calculated by
Atoll.
For KPIs, it is possible to compare:
1.
2.
3.
4.
Two sets of single-server KPIs (call drop rates, served users, etc.): For example, to assess the variation in KPI values
before and after parameter changes in the network
A set of single-server KPIs with equivalent parameters predicted by Atoll: For example, to determine the difference
between the predictions and measured network performance
A set of multi-server KPIs with the corresponding neighbour relations table in Atoll: For example, to analyse the
inconsistencies between predicted and actual network behaviour
Two sets of multi-server KPIs (numbers of handovers, etc.): For example, to evaluate the performance of handover
parameter optimisations
For UE/cell/MDT traces, it is possible to compare predicted RSRP and RSRQ values with the measured ones. For more
information, see 3.7.5 Comparison Between UE/Cell/MDT Trace Measurements and Predictions.
3.5.1 Comparison between Two Sets of Single-Server KPIs
Single-server KPIs (call drop rates, served users, etc.) are cell-level or sector-level statistics associated with one cell or sector.
In order to assess the variation in KPI values before and after some parameter changes in the network, a simple comparison
can be carried out showing a comparative data table with KPI values side-by-side.
Figure 3.17 Example of comparison between two sets of KPIs
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3.5.2 Comparison between Single-Server KPIs and Predicted Values
Single-server KPIs (call drop rates, served users, etc.) are cell-level or sector-level statistics associated with one cell or sector.
In order to assess the difference between predicted and measured network performance, Atoll can predict KPI values and
show a side-by-side comparison between the measured and predicted KPI values directly in the KPI data table.
These predicted values and the difference between measured and predicted values are available for transmitter and coverage
prediction display similar to the measured KPIs.
Figure 3.18 Example of comparison between KPIs and predicted values
3.5.3 Comparison between Multi-Server KPIs and Neighbour Relations
Multi-server KPIs (numbers of handovers, etc.) are cell-level or sector-level statistics associated with two cells or sectors.
Multi-server KPIs usually depict the flow of traffic flow between network elements of the same or different technologies
(intra-RAT and inter-RAT relations). The Atoll Live module allows analysing the difference between actual traffic flow in the
network, based on handover-related KPIs, and the neighbour lists defined in Atoll. Neighbour lists in Atoll may be imported
from external sources, created automatically based on extensive radio criteria, or defined and adjusted manually.
For this type of comparison, Atoll provides a detailed comparative results table showing multi-server KPI values and data
from Atoll neighbour lists side-by-side. Among other information, the comparative results also shows missing neighbour
relations that can be directly added to the Atoll’s neighbour lists.
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Figure 3.19 Example of comparison between handover KPIs and neighbour lists
3.5.4 Comparison between Two Sets of Multi-Server KPIs
Multi-server KPIs (numbers of handovers, etc.) are cell-level or sector-level statistics associated with two cells or sectors.
Multi-server KPIs usually depict the flow of traffic between network elements of the same or different technologies (intraRAT and inter-RAT relations). The Atoll Live module allows analysing the difference between two sets of KPIs. Such a
comparison can help assess the variation in traffic flow KPIs before and after some parameter changes in the network. The
resulting comparative data table shows KPI values side-by-side.
Figure 3.20 Example of comparison between two sets of KPIs
Combined Path Loss Matrices
The Atoll Live module allows integrating live network measurements into Atoll’s advanced planning and optimisation
capabilities. Using UE/cell/MDT trace data, it is possible to combine predicted path losses with measured path losses.
Combined path losses provide a more accurate view of radio propagation. Once combined, path loss matrices including both
predicted and measured data are available for all subsequent calculations such as coverage plots, Monte Carlo simulations,
neighbour planning, interference matrices calculation for the AFP, and the ACP for network optimisation as well as site
selection.
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Figure 3.21 Schematic representation of the path loss combining process
Coverage Plots Including Live Network Data
The Atoll Live module allows calculating coverage plots depicting the live network performance on the map and assessing the
results using associated reports and statistics. In addition to accurate predictions, coverage plots can be based on
measurements alone and on intelligent combination of measurements with predictions.
3.7.1 KPI Quality Zones
In Atoll, KPI data tables are linked with network elements (cells or transmitters). This enables you to view cell coverage areas
using colours associated with KPI quality level definitions. It is also possible to filter per-sector coverage plots according to
their KPI values. Also, KPI quality zones coverage plots enable you to view cell coverage areas according to multiple KPIs. For
example, if an RSRP-related KPI and an RSRQ-related KPI both indicate problems in certain areas of the network, this can be
displayed on the map using the KPI quality zone coverage plot.
Figure 3.22 Example of logical combination for a KPI quality zone coverage plot
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Figure 3.23 Example of logical combination of KPIs: RSRP-related KPI (top-left), RSRQ-related KPI (top-right), bad RSRP &
bad RSRQ quality zone (bottom)
3.7.2 UE/Cell/MDT Trace Measurement Plots
The Atoll Live module is able to process measurement data contained in the UE/cell/MDT trace files and display this
information in the form of measurement plots. These measurement plots are based on the same architecture as Atoll’s
coverage predictions and benefit from the related export, reporting, and statistics features.
Figure 3.24 Example of a UE/cell/MDT trace measurement plot
These measurement plots provide a means to quickly visualise any type of measurement data present in the source
UE/cell/MDT traces. Furthermore, UE/cell/MDT trace measurements can be combined with predicted plots to obtain an
augmented prediction plot. For more information, see 3.7.4 Combined Prediction and Measurement Plots.
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3.7.3 UE/Cell/MDT Trace Coverage Plots
The Atoll Live module can generate coverage plots from measurement data contained in the UE/cell/MDT trace files. As
measurement values are only available on some locations, these are interpolated in order to obtain probable values at
locations where measurements are not available. These measurement-based coverage plots are based on the same
architecture as Atoll’s coverage predictions and benefit from the related export, reporting, and statistics features.
Figure 3.25 Example of a UE/cell/MDT trace coverage plot
3.7.4 Combined Prediction and Measurement Plots
In addition to UE/cell/MDT trace-based measurement plots (3.7.2 UE/Cell/MDT Trace Measurement Plots) and coverage plots
(3.7.3 UE/Cell/MDT Trace Coverage Plots), Atoll is also capable of intelligently combining measured values with predicted
ones taking into account radio and geographic environments. With the ability of combining UE/cell/MDT trace measurements
with highly accurate predictions from advanced propagation models, Atoll provides operators with a unique tool to analyse
their networks in more detail with higher precision.
Figure 3.26 Example of a predicted RSRP coverage plot
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Figure 3.27 Example of the predicted RSRP coverage combined with UE/cell/MDT trace measurements
3.7.5 Comparison Between UE/Cell/MDT Trace Measurements and Predictions
Atoll enables comparing UE/cell/MDT trace measurement plots and coverage plots with equivalent coverage predictions
directly on the map using the tooltip function and numerically by creating a pixel-wise value difference plot.
Figure 3.28 Visual (left) and value difference (right) between UE/cell/MDT measurements and predictions
Reports and statistics can be obtained on the measurement plots, coverage predictions, as well as on the value difference
plots.
Network Optimisation Using Live Network Data in the ACP
The Atoll ACP (Automatic Cell Planning) module enables operators to optimise and densify their networks to improve
coverage, capacity, and performance. The Atoll ACP can optimise parameters of installed antennas (patterns, heights,
azimuths, and tilts) and cell transmission powers. As well, the ACP can perform site selection for macro as well as small cell
deployments.
The ACP takes into account various standard and user-defined optimisation objectives, such as coverage, interference,
capacity, service quality, and EMF exposure levels at building facades. Moreover, the ACP can calculate objectives on different
floors for evaluating optimisation plans in multi-storey buildings. The ACP optimisation process is based on flexible and user-
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definable directives which may include a number of weighted criteria depending on the network configuration and radio
environment data.
Figure 3.29 Atoll ACP optimisation process
The Atoll Live module allows the Atoll ACP to receive feedback from a live network based on user-defined key performance
indicators. Moreover, the Atoll Live module can process KPI values into metrics that can be directly employed by the ACP to
identify problematic cells and critical network zones based on a single KPI or on logical combinations of multiple KPIs. For an
example of critical zones based on logical combinations of KPI, see the figure below.
Figure 3.30 Definition of KPI-based critical zones for optimisation
Once the critical zones have been identified with the help of the Atoll Live module, the optimisation engineer can define
specific ACP optimisation objectives dedicated to these zones in addition to the global optimisation objectives.
This allows the ACP to focus more on the critical network zones and attempt at improving the overall network performance
as well as resolving possible issues for the problematic cells. The ACP enables defining multi-tier optimisation objectives based
on KPI quality definitions, for example, corresponding to critical cells, their neighbouring cells, and other cells.
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Figure 3.31 Example of global and critical-zone optimisation objectives
Figure 3.32 Example of a critical-zone optimisation objective
In addition to KPIs, the ACP can also be provided with traffic density information from weighting maps based on UE/cell/MDT
traces. For example, within the critical zones, the operator can obtain a general idea of user density from UE/cell/MDT traces.
This user density can be converted into a weighting map and provided to the ACP for pixel-weighting, i.e., assigning an
importance to each pixel being assessed according to the density of users present on that pixel. For an example of the
weighting maps, see the figure below.
Figure 3.33 Density map of UE/cell/MDT traces
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Prediction and KPI-Based Neighbour Planning
The Atoll Live module enables a number of enhanced automatic neighbour planning features using multi-server KPIs that
depict the flow of traffic between network elements, such as numbers of handovers, etc. Multi-server KPIs can be cell-level
or sector-level statistics associated with two cells or sectors of the same or different technologies (intra-RAT and inter-RAT
relations).
With the Atoll Live module, Atoll can take into account KPIs in automatic neighbour planning and importance calculation.
Moreover, a feature for creating black and white lists of neighbour cells (called exceptional pairs in Atoll) is also available.
Additionally, as described in 3.5.3 Comparison between Multi-Server KPIs and Neighbour Relations, multi-server KPIs can be
compared with neighbour lists in Atoll and missing neighbour links can be manually added to the Atoll neighbour lists.
3.9.1 Automatic Neighbour Planning Using KPIs
Using the live network key performance indicators based on traffic flow between cells and sectors, Atoll’s automatic
neighbour planning function can provide more reliable and realistic results.
Figure 3.34 KPI-based automatic neighbour planning
This allows Atoll to perceive handover relations that might not have been significant based on pure radio criteria, hence
improving the results provided by the algorithm.
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Figure 3.35 KPI-based automatic neighbour relations
3.9.2 Neighbour Importance Calculation Including KPIs
The importance values, used in the AFP for parameter planning, can be evaluated including KPI data from the live network to
provide more weightage to real traffic flow in the network.
Figure 3.36 Neighbour importance component weights
3.9.3 Automatic Creation of Black Lists and White Lists (Exceptional Pairs)
The Atoll Live module enables the automatic creation of black and white lists of cell-pairs based on multi-server handover
KPIs. The aim of this feature is to help the user automatically create lists of forced and forbidden neighbours in Atoll which
are then taken into account during the automatic neighbour planning.
The creation of black and white lists of cell-pairs (exceptional pairs) provides a simple means to filter target cells based on a
number of criteria: distance, number of handovers, handover failure/success rate, and the importance ratio calculated
automatically by Atoll based on the numbers of handovers from any cell towards all of its target cells.
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Figure 3.37 Automatic creation of black and white lists
Figure 3.38 Example of black listed (red) and white listed (green) neighbour relations
Automatic Frequency, PCI, and PRACH Planning Using Live Network Data in the LTE AFP
The Atoll LTE AFP module enables automatically configuring network parameters such as the frequency carriers, physical cell
IDs, and PRACH root sequence indexes. The aim of the AFP is to allocate resources in a way that minimises interference,
collision, and confusion while respecting the user-definable constraints.
In addition to the existing types of constraints taken into account by the AFP, i.e., interference matrices, neighbour relations,
and allowed ranges of resources for allocation, the Atoll Live module enables the AFP to also take into account multi-server
KPIs and automatically determine inter-cell relations based on UE traces. This allows the AFP to identify relations between
cells based on actual network measurements.
Multi-server KPIs are cell-level or sector-level statistics associated with two cells or sectors defining traffic flow or mutual
impact in terms of interference between them. UE traces help the AFP identify additional inter-cell relations based on the
numbers of UE traces corresponding to each server-neighbour pair.
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Figure 3.39 KPI-based automatic parameter planning using the LTE AFP
This allows the Atoll LTE AFP to identify relations that might have been overlooked based on pure radio criteria, hence
improving the allocation results.
Figure 3.40 PCI collision zones detected through KPIs
Traffic Maps from Live Network Data
Atoll can use traffic-oriented KPIs, such as throughput demands and numbers of users, to create KPI-based sector traffic maps.
Sector traffic maps use per-sector traffic data from KPIs and spread the traffic demand intelligently over the predicted
coverage area of each corresponding sector.
Figure 3.41 KPI-based sector traffic maps
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Figure 3.42 Example of a KPI-based sector traffic map
KPI data imported in Atoll can be refreshed to load the latest values from the KPI source. Similarly, KPI-based sector traffic
maps can also be updated to match the latest traffic KPI values from the live network.
Figure 3.43 Automatic update of a KPI-based sector traffic map
Furthermore, the traffic distribution within each sector of a sector traffic map can be geographically weighted by clutter class
as well as a weighting map based on UE/cell/MDT traces.
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Figure 3.44 Sector traffic map weighted by UE trace densities
These traffic maps can be used to carry out comprehensive traffic analyses using Monte Carlo simulations. Moreover, traffic
data, i.e., one or more combined traffic maps, can be provided to the ACP for steering the optimisation engine towards more
important areas, i.e., zones of high traffic.
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Atoll 3.4.0 Technical Overview
4 Antenna and Radio Equipment Features
Atoll includes a comprehensive model for radio antennas and equipment. It allows you to import 2D and 3D antenna models
in various formats, assign antennas to sectors using an intelligent antenna selection assistant, and set up antennas sharing
between collocated sectors of the same or different radio access technologies. Atoll also includes various handy tools such
as an antenna pattern comparison tool and an antenna pattern smoothing tool.
Antenna Model
Each antenna is defined in Atoll by the following parameters:
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Gain
Horizontal and vertical patterns
Half-power beamwidth
Operating frequency range (minimum and maximum values)
Pattern electrical tilt
Pattern electrical azimuth
A default set of antennas is available in Atoll. Additional antennas, with 2D and 3D patterns, can be created and imported
from external ASCII TXT, CSV, or MS Excel files. Atoll supports antenna patterns with high precision, i.e., up to 0.1 degree
steps.
The figure below presents the antenna properties window.
Figure 4.1
Antenna properties window
Antenna Features
The following features enable you to work with antennas in Atoll.
4.2.1 2D and 3D Antenna Pattern Import
Atoll allows you to import antennas with 2D and 3D patterns from external ASCII TXT, CSV, or MS Excel files. Atoll supports
antenna patterns with high precision, i.e., up to 0.1 degree steps.
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Figure 4.2
3D antenna pattern import
4.2.2 Antenna Selection Assistant
Atoll includes an antenna selection assistant that allows you to quickly find the best suited antenna for each sector based on
sector-antenna compatibility criteria such as the operating frequencies, beamwidth, electrical tilts and azimuths.
Figure 4.3
Antenna selection assistant
4.2.3 Antenna Pattern Comparison Tool
Atoll enables you to compare different antenna patterns using antenna comparison tool.
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Figure 4.4
Atoll 3.4.0 Technical Overview
Antenna pattern comparison
4.2.4 Antenna Pattern Smoothing
Smoothing the vertical antenna patterns may improve the emulation of reflection and diffraction effects with some empirical
propagation models. In Atoll, you can smooth vertical as well as horizontal antenna patterns by flattening high-attenuation
points of the pattern.
Figure 4.5
Antenna pattern smoothing
4.2.5 Antenna-to-Sector Assignment Audit
Atoll allows you to automatically check that the antenna operating frequencies match the operating frequencies of the
sectors to which the antennas are assigned. Inconsistencies are listed in the event viewer.
4.2.6 Antenna Parameter Audit
Atoll allows you to automatically compare electrical azimuth and tilt parameters stored in the antenna model with those
calculated from the antenna pattern. For calculations, Atoll always uses the electrical azimuth and tilt values calculated from
the antenna pattern. Values stored as antenna model parameters can be used to filter the antenna model for assignment to
sectors.
Antenna – Sector Configurations
Atoll can model various configurations of physical antennas installed at base stations:
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Single antenna configurations
Co-located multiple antenna configurations
Geographically distributed antenna configurations
Multi-beam antenna configurations
C-RAN configurations
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4.3.1 Single Antenna Configurations
Single antenna configurations correspond to the traditional installation scenario with one physical antenna installed per
sector. This configuration is modelled in Atoll using the following analogies:
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One transmitter and cell per sector
The single antenna panel installed at the sector modelled using the main antenna of the transmitter
The single physical antenna panel may however comprise multiple ports fed by the same power source. This is the case for
MIMO antenna panels comprising two, four, or eight rows of antenna elements.
The figure below shows an example of the definition of the single antenna sector configuration in Atoll.
Figure 4.6
Single antenna sector configuration example in Atoll
The figure below shows the corresponding sector coverage footprints.
Figure 4.7
Schematic representation of a single antenna sector coverage
4.3.2 Co-located Multiple Antenna Configurations
Co-located multiple antennas pointing in different directions may be installed at a sector. Such antennas may help optimise
the coverage by directing the antennas towards preferred zones to cover. This configuration is modelled in Atoll using the
following analogies:
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One transmitter and cell per sector
Each antenna panel installed at the sector modelled using the main antenna and one or more secondary antennas
The main and secondary antennas share a common source of power, i.e., the cell transmit power is divided between all the
antennas installed at the sector. Secondary antennas may have different azimuths and tilts. Atoll assumes that the main and
secondary antennas all use the same number of ports.
The figure below shows an example of the definition of the multi-antenna sector configuration in Atoll.
Figure 4.8
Multi-antenna sector configuration example in Atoll
The figure below shows the corresponding sector coverage footprints.
Figure 4.9
Schematic representation of a multi-antenna sector coverage
4.3.3 Geographically Distributed Antenna Configurations
Geographically distributed antenna configurations or distributed antenna systems (DAS) use RF cables or fibre optic cables to
connect multiple antennas to a DAS baseband unit common to all the antennas located at different locations. DAS are usually
employed vertically, for covering multiple building floors using the same radio resources. They are also used for extending
the covered surface horizontally. This configuration is modelled in Atoll using the following analogies:
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One transmitter and cell located at the DAS hub common to all the distributed antennas
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One remote antenna per distributed antenna/sector corresponding to the installed antenna panels at a given
location
Each distributed/remote antenna is located at its own site but linked to a donor transmitter that can be considered equivalent
to a DAS hub. Atoll considers the whole system, hub and remote antennas, as a single radio entity for coverage.
The figure below shows an example of the definition of the distributed antenna configuration in Atoll.
Figure 4.10 Distributed antenna configuration example in Atoll
The figure below shows the corresponding sector coverage footprints.
Figure 4.11 Schematic representation of a geographically distributed antenna coverage
4.3.4 Multi-beam Antenna Configurations
Multi-beams antennas, also referred to as dual-beam or split-beam antennas, use two or more beams with different, e.g.,
negative and positive, electrical azimuth offsets with respect to the mechanical antenna azimuth. This configuration is
modelled in Atoll using the following analogies:
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One transmitter and cell per antenna beam (electrical azimuth)
Each antenna beam is modelled using the main antenna of the transmitter
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All beam patterns of a multi-beam antenna are synchronised by means of the definition of a shared antenna. Changes made
to the antenna parameters of one beam are automatically applied to the other beams. This function, called multi-sector
antenna sharing, allows you to create multiple co-located sectors, of the same or different radio access technologies, that
share the same physical antenna. Setting up shared antennas in Atoll ensures automatic synchronisation of antenna
parameters (sector position with respect to the site location, azimuth, height, tilt), and optionally antenna patterns, among
sectors sharing the same antenna. Atoll includes an antenna sharing assistant that enables easy configuration of shared
antennas.
Figure 4.12 Antenna sharing assistant
The figure below shows an example of the definition of the distributed antenna configuration in Atoll.
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Figure 4.13 Multi-beam antenna configuration example in Atoll
The figure below shows the corresponding sector coverage footprints.
Figure 4.14 Schematic representation of a multi-beam antenna sector coverage
4.3.5 C-RAN Configurations
C-RAN configurations employ groups of cells managed by a common baseband unit pool. A common processor allows efficient
resource allocation and sharing between multiple cells. These configurations are modelled in Atoll using the following
analogies:
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One transmitter and cell per sector or small cell
Groups of cells managed by a common BBU assigned to a common cell group
Usually, cells performing joint functions, such as carrier aggregation or coordinated multipoint transmission and reception
are assigned to the same group (CA group or CoMP set). Cells of the same group may correspond to the same or different
eNBs/RRUs including macro, micro, and small cells.
The figure below shows an example of the definition of the C-RAN configuration in Atoll.
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Figure 4.15 C-RAN configuration example in Atoll
The figure below shows the corresponding sector coverage footprints.
Figure 4.16 Schematic representation of a C-RAN sector coverage
Radio Equipment Model
Atoll models radio equipment that is used to create a network, along with the characteristics that have a bearing on network
performance.
4.4.1 Transmitter Equipment
A noise figure value can be specified for each transmitter equipment. This can be used for calculating the actual transmitter
noise figure.
4.4.2 Feeders
A feeder loss per metre and transmission and reception losses due to connectors can be specified for each feeder type. These
values can be used for calculating the actual transmission and reception losses of a transmitter.
4.4.3 Tower Mounted Amplifiers (TMA)
A noise figure, a reception gain, and a transmission loss can be specified for each tower mounted amplifier (TMA). These
values can be used for calculating the actual transmission and reception losses of a transmitter.
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5 5G NR Features
The Atoll 5G NR module provides a comprehensive and accurate modelling of multi-band, sub-6GHz and mmWave 5G NR
networks in both standalone (SA) and non-standalone (NSA) deployment modes. It supports all 5G NR frequency bands and
carrier widths along with detailed frame structure modelling, downlink control signals, and control and traffic channels. Atoll
5G NR supports several advanced features such as intra-band and inter-band carrier aggregation and E-UTRA–NR dual
connectivity. Atoll 5G NR also includes comprehensive modelling of 3D beamforming and massive MIMO antennas.
Atoll supports all 5G NR modulation and coding schemes, voice, data, and broadband services. Atoll provides the means to
set up multi-service traffic maps from multiple sources: vector, raster and live traffic data. Traffic maps are used in 5G NR
Monte Carlo simulations for network capacity analysis including power control, interference control, RRM, scheduling, and
multi-layer traffic balancing. Coverage predictions can be calculated based on Monte Carlo simulation results or on live
network loads from the OAM in order to study coverage and capacity of the network.
Atoll includes automatic neighbour planning features that allow analysing handovers in the network. Atoll can work with
multiple interference matrices from various sources: prediction-based (calculated within Atoll), based on OAM statistics, and
based on drive test measurements. The Atoll 5G NR AFP can automatically allocate physical cell IDs and PRACH RSIs based on
user-definable constraints and cost. Analysis tools enabling auditing of physical cell ID and PRACH RSI plans are also available.
Atoll includes integrated single RAN–multiple RAT network design capabilities for cellular radio access technologies including
5G NR, LTE, NB-IoT, UMTS, GSM, and CDMA. It features a multi-technology network database, a unified traffic model, and a
combined Monte Carlo simulator. The Atoll 5G NR ACP can be used to automatically optimise network parameters to increase
coverage and capacity. It can also carry out site selection for greenfield and site activation for densification scenarios.
An overview of the 5G NR modelling in Atoll is shown in the figure below.
Figure 5.1
5G NR network modelling in Atoll
5G NR Network Model
The 5G NR network model comprises radio network elements such as sites, transmitters, and cells. A 5G NR gNode-B is
equivalent to a site, its transmitters with one or more carriers (cells) each.
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Figure 5.2
5G NR network model
5.1.1 Sites
A site represents the physical location where gNode-Bs can be installed. An example of a site properties window is shown in
the figure below.
Figure 5.3
Site properties window
Site parameters are:
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Geographic coordinates
Altitude (user-defined or automatically extracted from the terrain elevation data)
Any user-defined flags and parameters such as address, owner, deployment phase, etc.
The maximum downlink and uplink backhaul throughputs: The capacity of the backhaul the gNode-B and the serving
gateway imposes a limit on the aggregate throughput served by the cells of the same gNode-B. This also imposes a
limit on the throughput of each individual user served by the gNode-B. The maximum backhaul throughputs that
you enter here can be taken into account in Monte Carlo simulations as backhaul constraints.
5.1.2 Transmitters
Transmitters in Atoll correspond to sectors and antennas installed at a site. The main transmitter parameters are:
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Transmitter name and the name of the site where it is installed
X and Y coordinates
Transmitter type (server and interferer, or interferer only)
Active/inactive (to be included in calculations or not)
Main, secondary, and 3D beamforming antennas
Numbers of transmission and reception antenna ports for MIMO
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other repeaters
Transmission and reception losses
Noise figure in reception
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Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Tower mounted amplifier (TMA)
Feeder type and its transmission and reception lengths
Maximum range
Any user-defined flags and parameters
An example of a transmitter properties window is shown in the figure below.
Figure 5.4
5G NR transmitter properties window
5.1.3 Cells
Atoll supports multi-band, multi-carrier 5G NR network deployments. In Atoll, cells model frequency carriers used at a
transmitter. A transmitter can support cells with scalable carrier widths and different carriers. Each cell has its own radio
resources and parameters, including:
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Cell name and the name of the transmitter to which the cell belongs
Frequency band and carrier
Network layer (macro, small cell, 3.5 GHz, mmWave, etc.) to which the cell belongs (hence also the associated
priority)
Cell selection and handover parameters (cell individual offset used for cell range expansion, cell selection threshold
known as ThresXHighP, and handover margin)
Cell type: whether the cell is a PCell or SCell or both
Physical cell ID, PSS ID, SSS ID
SS/PBCH parameters: numerology, periodicity, OFDM symbols
PDCCH overhead
PRACH preamble format
List of allocated PRACH root sequence indexes
AFP parameters: allocation status (allocated, locked, etc.) for carrier, PSS, SSS, and PRACH RSI, physical cell ID
domain, number of required PRACH root sequence indexes, minimum reuse distance, list of resource block indexes
and subframe numbers used for PRACH
Transmission powers: maximum power, SSS EPRE, and PSS, PBCH, PDCCH, and PDSCH EPRE offsets
Minimum SS-RSRP
Radio equipment
Traffic numerology and TDD DL/UL ratio
Downlink and uplink diversity support (diversity, SU-MIMO, MU-MIMO)
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RRM parameters: scheduler type, maximum number of simultaneous users
Fractional power control and noise rise control parameters: FPC factor, maximum PUSCH C/(I+N)
Resource allocation constraints: maximum uplink and downlink traffic loads
Cell loads and resource allocation results: uplink and downlink traffic loads, uplink noise rise, uplink and downlink
beam usage ratios, numbers of co-scheduled MU-MIMO users, numbers of connected users in downlink and uplink
These parameters can be outputs of Monte Carlo simulations as well as user-defined values.
Inter-technology interference: downlink and uplink noise rise
Neighbour parameters: maximum numbers of neighbours and neighbours lists
Any user-defined flags and parameters
The figure below presents an example of a transmitter with a single cell.
Figure 5.5
5G NR cell parameters
5.1.4 Site Templates
A site template is made up of one or more transmitters and cells located on the same site. Site templates can be created and
edited as needed. Building a network is facilitated by working with site templates rather than single site/transmitter/cell. By
default some 5G NR site templates are available for dense urban, urban, suburban, and rural environments.
5.1.5 Repeaters
A repeater receives, amplifies, and retransmits signals. Repeaters are used to extend the coverage of their donors. Atoll
models selective as well as non-selective RF repeaters, optic fibre repeaters, microwave repeaters, and remote antennas.
Selective RF repeaters only repeat signals from their donor transmitters whereas non-selective RF repeaters receive and
retransmit wanted signals as well as interference.
The main parameters of a repeater are:
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Donor transmitter name
X and Y coordinates
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other repeaters
Total gain
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Amplifier gain
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Feeder type and its transmission and reception lengths
Any user-defined flags and parameters
The figure below presents the repeater properties window while the figure after than gives an example of a best server
prediction plot with a repeater.
Figure 5.6
Repeater properties window
RF repeater
Donor transmitter
Figure 5.7
RF repeater coverage plot
5G NR Network Parameters
Atoll allows setting and modifying network-level configurations and parameters applicable to the entire project.
5.2.1 Frequency Bands and Carriers
Atoll supports all 5G NR frequency bands and carrier widths included in the 3GPP specifications. A frequency band is
characterized by its reference frequency that is used by Atoll for path loss calculations. Each carrier within a frequency band
is characterised by its duplexing mode, its downlink and uplink centre frequencies, its downlink and uplink bandwidths, and
its absolute radio frequency channel numbers (ARFCN).
You can add, modify, and delete frequency bands and carriers in Atoll as required. A number of EUTRA frequency bands are
available by default. An example of a 5G NR carrier definition is shown in the figure below.
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Figure 5.8
5G NR carrier definition
5.2.2 Global Network Settings
5G NR-specific parameters that are applicable to the entire network are modelled in Atoll as global network settings. These
parameters include the downlink transmission power calculation method, best server selection criterion and method,
diversity mode (SU-MIMO, MU-MIMO) selection criteria, the interference calculation method, and the uplink power
adjustment margin. The figure below presents the network level properties dialog box.
Figure 5.9
5G NR network level parameters
5.2.3 Network Layers
A 5G NR network can be deployed in multiple layers of heterogeneous cells, i.e., of different sizes (macro, micro, small cells,
etc.), and possibly using different frequencies. Such networks are referred to as HetNets, or heterogeneous networks. Atoll
enables you to define network layers with different priorities and supported user speed limits. During cell selection, network
layer parameters are taken into account to determine the serving cells.
The figure below gives an example of 5G NR network layers that can be defined and deployed in Atoll.
Figure 5.10 5G NR network layers table
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5.2.4 Schedulers
In Atoll, schedulers perform the allocation and management of radio resources according to the QoS classes of the services
being accessed by the selected users. Various scheduling methods are available in Atoll, including proportional fair, round
robin, maximum C/I, etc., as well as the support for multi-user diversity gains specific to proportional fair schedulers.
Figure 5.11 Default 5G NR schedulers
5.2.5 Radio Equipment
5G NR radio equipment model the transmission and reception characteristics of cells and user terminals. Bearers, bearer
selection thresholds, required thresholds for using SU-MIMO and MU-MIMO, secondary cell activation thresholds, quality
indicator graphs, and MIMO gains are defined in 5G NR radio equipment.
5G NR radio bearers are used to carry user data on the PDSCH and the PUSCH. A bearer refers to a combination modulation
and coding scheme. The radio bearers table lists the available radio bearers in downlink and uplink. You can add, remove,
and modify bearer properties according to your network and equipment.
Figure 5.12 5G NR radio equipment bearers
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Figure 5.13 5G NR bearer selection thresholds
Figure 5.14 5G NR quality indicator graphs
Diversity gains, SU-MIMO throughput gains (as a function of PDSCH or PUSCH C/(I+N)), and MU-MIMO capacity gains (as a
function of the number of co-scheduled users) can be defined for each equipment for different numbers of transmission and
reception antennas, modulation and coding schemes, and user speeds.
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Figure 5.15 PDSCH and PUSCH MIMO gains
Figure 5.16 PBCH and PDCCH diversity gains
Also, interference reduction factors can be defined for each ratio equipment considering the receiver characteristics of the
equipment with respect to various carrier widths.
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Figure 5.17 Interference reduction factors (adjacent channel selectivity)
5G NR 3D Beamforming and Massive MIMO
Massive MIMO comprises 3D beamforming combined with multi-user co-scheduling which results in both improved signal
quality at the user locations as well as increased system capacity. Massive MIMO systems comprise base stations with a large
number of antennas, greater than the number of served users. The system is capable of allocating the same frequency and
time resources to various co-scheduled users by using different beams to serve them simultaneously.
Atoll’s 3D beamforming model enables defining all the possible beam patterns that the beamforming antenna is capable of
forming. During calculations, sectors using 3D beamforming antennas serve their users through beams that provide the
highest gains towards user locations in 3D.
Figure 5.18 Example of 3D beamforming
For multi-user co-scheduling, Atoll allows the definition of MU-MIMO capacity gains as a function of the number of coscheduled MU-MIMO users. Different MU-MIMO throughput gain graphs can be defined for different combinations of the
number of transmission and reception antennas, user speeds, and radio bearers.
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Figure 5.19 Example of 3D beamforming coverage
The following sections describe Atoll’s 3D beamforming and massive MIMO features.
5.3.2 3D Beamforming Models
Atoll’s 3D beamforming models enable beamforming in both horizontal and vertical planes. The Atoll 3D beamforming allows
you to define any 3D beamforming massive MIMO antenna by its physical characteristics:
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M: Number of co-polar or cross-polar elements in a column
N: Number of co-polar or cross-polar elements in a row
P: Co-polar or cross-polar configuration
dV: Vertical inter-element spacing in multiples of wavelength
dH: Horizontal inter-element spacing in multiples of wavelength
Figure 5.20 64T64R 3D beamforming massive MIMO antennas
All radiating elements are usually manufactured using the same materials and with the same physical aspects and
characteristics. Therefore, all radiating elements of a beamforming antenna panel are assumed to have the same radiation
pattern. This radiation pattern is called the single-element pattern.
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P
A
P
A
Figure 5.21 Schematic diagram of a 64T64R 3D beamforming massive MIMO antenna
Figure 5.22 64T64R 3D beamforming massive MIMO antenna properties dialog box in Atoll
A beamforming antenna does not always use all the M x N elements to create beams. If all the elements are used to create a
beam, no multiplexing or co-scheduling of users is possible. Therefore, a M x N beamformer may create beams using a subset
of the vertical and horizontal elements (assumed to always be physically adjacent), referred to as m and n.
Atoll allows you to import measured radiation patterns of multiple beams, each pointing in a different direction and/or
created using a different number of active elements. If you do not have actual radiation patterns available, Atoll can calculate
theoretical beam patterns in different directions for you.
3D beamforming antennas may, and usually, use different beams for control channels than traffic channels. Control channel
beams are usually wider in order to provide coverage to the whole cell and traffic beams are narrower to focus on the served
users. Atoll allows you to define control channel beams (SSS, PSS, PBCH), refinement beams (CSI-RS), and traffic channel
beams (PDSCH, PDCCH, and PUSCH).
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Figure 5.23 3D traffic channel beams created using an 8x8 matrix
5.3.3 3D Beam Pattern Generator
Atoll includes a 3D beam pattern generation tool that allows you to create beams in various directions using different
numbers of antenna elements, hence providing different gains.
Figure 5.24 3D beam pattern generator
Atoll’s 3D beam generator can calculate beam patterns for any uniform linear array (ULA) and uniform planar array (UPA)
beamforming antennas comprising any numbers of horizontal and vertical elements.
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Y
N
φ
M
Z
θ
X
Figure 5.25 Uniform planar array model
Atoll first calculates the steering vector of the planar array towards any given direction (θ, φ) for each combination of m and
n antenna elements:
𝑇
𝑆⃗(𝜃,𝜑) = [1 … 𝑒 𝑗2𝜋(𝑛𝑑𝐻 sin 𝜃 cos 𝜑+𝑚𝑑𝑉 sin 𝜑) … 𝑒 𝑗2𝜋{(𝑁−1)𝑑𝐻 sin 𝜃 cos 𝜑+(𝑀−1)𝑑𝑉 sin 𝜑} ]
Then Atoll calculates the beamforming weights for any (n, m)th antenna element that when multiplied with the steering vector
tend to maximize the array factor in the direction (θ, φ):
𝑇
𝑤
⃗⃗⃗(𝜃,𝜑) = [1 … 𝑒 −𝑗2𝜋(𝑛𝑑𝐻 sin 𝜃 cos 𝜑+𝑚𝑑𝑉 sin 𝜑) … 𝑒 −𝑗2𝜋{(𝑁−1)𝑑𝐻 sin 𝜃 cos 𝜑+(𝑀−1)𝑑𝑉 sin 𝜑} ]
The array factor is calculated as the scalar product between the above two vectors:
𝐴𝐹 = |𝑆⃗(𝜃,𝜑) ∙ 𝑤
⃗⃗⃗(𝜃,𝜑) |
The beam patterns are then calculated by multiplying the array factor with the single element pattern.
5.3.4 3D Beam Usage Calculation
Each beam formed by a 3D beamforming antenna serves a certain number of users, or in other words, a certain amount of
traffic goes through each beam. Atoll models this aspect as a beam usage ratio. The usage ratio of each beam can be userdefined, i.e., imported from an R&D simulation tool, or calculated by Atoll based on the surface areas or traffic covered by
each beam.
The beam usage ratios represent how often each beam is used and hence how much each beam interferes its surrounding
cells and their traffic. Beam usage ratios are therefore used for calculating interference in various directions for interferencebased calculations of the PDSCH and PUSCH C/(I+N), and hence throughputs.
Atoll enables you to calculate beam usage ratios either approximately based on coverage predictions, or more precisely using
Monte Carlo simulations.
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Figure 5.26 Beam usage calculation based on coverage predictions
Figure 5.27 Example of beam usage ratios for uniformly distributed traffic
5.3.5 Massive MIMO
Atoll supports the following transmission modes for MIMO, which can be combined with each other under user-definable
conditions:

Transmit and receive diversity: For transmit or receive diversity, MIMO systems use more than one transmission or
reception antennas to send or receive more than one copy of the same signal. The signals are constructively
combined (using optimum selection or maximum ratio combining) at the receiver to extract the useful signal.
As the receiver gets more than one copy of the useful signal, the signal level at the receiver after combination of all
the copies is more resistant to interference than a single signal would be. Therefore, diversity improves the C/(I+N)
at the receiver. It is often used for the regions of a cell that have insufficient C/(I+N) conditions.
In Atoll, you can set whether a cell supports transmit or receive diversity. Diversity gains on downlink and uplink
can be defined in the radio equipment for different numbers of transmission and reception antenna ports, user
speeds, and radio bearers.

SU-MIMO: For SU-MIMO, MIMO systems use more than one transmission antenna to send different signals (data
streams) on each antenna. The numbers of MIMO data streams are referred to as the MIMO rank. Using SU-MIMO
with a MIMO rank of N theoretically increases the user throughput by N times.
In Atoll, you can set whether a cell supports SU-MIMO. SU-MIMO throughput gains can be defined in the radio
equipment for different radio conditions, numbers of transmission and reception antenna ports, user speeds, and
radio bearers.
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Figure 5.28 Example of SU-MIMO throughput gains as a function of radio conditions

MU-MIMO: MU-MIMO enables co-scheduling of spatially dispersed users in the same frequency-time radio
resources. MU-MIMO can provide considerable capacity gains.
In Atoll, you can set whether a cell supports MU-MIMO, and either enter the average numbers of co-scheduled
users yourself or have Atoll calculate it for you using Monte Carlo simulations. MU-MIMO capacity gains can be
defined in the radio equipment for different numbers of co-scheduled users, numbers of transmission and reception
antenna ports, user speeds, and radio bearers.
Figure 5.29 Example of MU-MIMO capacity gains as a function of the number of co-scheduled users
Massive MIMO is the capability to combine all of the above-mentioned MIMO transmission modes using a very large number
of base station antennas. 3D beamforming enables massive MIMO systems to co-schedule multiple spatially non-correlated
users.
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Figure 5.30 Example of throughput prediction plots without (top-left) and with (bottom-right) massive MIMO
Massive MIMO
Conventional MIMO
Gain
Figure 5.31 Comparison of massive MIMO throughputs with conventional MIMO
5G NR Carrier Aggregation
Atoll supports different modes of carrier aggregation:



Intra-gNode-B carrier aggregation: Only cells that belong to the same site can perform carrier aggregation with each
other.
Multi-gNode-B carrier aggregation: Cells belonging to any site can perform carrier aggregation with each other.
Group-based carrier aggregation: Cells belonging to the same group can perform carrier aggregation with each
other.
Group-based carrier aggregation mode models a C-RAN-based centralised architecture for carrier aggregation where cells
belonging to the same group are managed by the same BBU pool. Cells of the same group can correspond to the same or
different gNBs/RRUs including macro, micro, and small cells.
Atoll enables you to create carrier aggregation cell groups by grouping cells in the Network explorer as well as, geographically,
grouping cells on the map using polygons. It is also possible to import such cell groups from external spread sheets. Atoll
allows you to view cell groups on the map using coverage predictions as well as using the Find on Map tool.
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Figure 5.32 C-RAN architecture with a virtual BBU pool managing multiple RRUs
For each user terminal, Atoll also allows you to define the combinations of frequency bands that can be aggregated with each
other.
Figure 5.33 List of frequency bands allowing carrier aggregation for a user terminal
5G NR/LTE Dual Connectivity (EN-DC)
Atoll supports E-UTRA – NR dual connectivity (EN-DC), where the 5G NR cells’ coverage in downlink and uplink may not be
balanced in which case LTE cells are used as anchor cells in downlink and serving cells in uplink.
Hence, a user within the downlink and uplink coverage range of 5G NR is served by 5G NR, but any other user within the
downlink coverage range of 5G NR is served by 5G NR in the downlink but by LTE in uplink.
Atoll enables creating groups of 5G NR and LTE cells providing dual connectivity and ensuring that users are served by 5G NR
or LTE as defined by the EN-DC approach.
Figure 5.34 Example of a group of EN-DC cells
5G NR Traffic Model
In Atoll, the radio network traffic is modelled using Monte Carlo simulations. According to the definition of the services and
users in the network, and depending on the traffic cartography (traffic data), realistic distributions of users are generated and
used as input to the scheduling and radio resource management algorithms.
Service and user behaviours are modelled in Atoll through different tables that provide information about:


The services available in the network
The terminals compatible with the network
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The mobility types
The user profiles describing the way users access different services
The 5G NR traffic model is shown in the figure below.
Figure 5.35 5G NR traffic model
5.6.1 Services
The services table describes the services that are available in the network (Internet, VoNR, VoIP, etc.). Both voice and data
type services are supported and have specific parameters. The main service parameters are:











Service type
Uplink and downlink activity factors
Supported network layers (macro, small cell, 3.5 GHz, mmWave, etc.)
QoS class identifier (QCI) and its related priority
Intra-QCI priority level
Lowest and highest supported modulations
Uplink and downlink maximum throughput demands (MBR)
Uplink and downlink minimum throughput demands (GBR)
Uplink and downlink average requested throughputs
Throughput conversion parameters from RLC to Application layer
Body loss
An example of a service properties window is presented in the figure below.
Figure 5.36 Service properties window
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5.6.2 Terminals
The terminals table describes the terminals that can be used in the network, cell phones, smartphones, in-car navigation
devices, etc. The following parameters model a terminal:













Minimum and maximum transmission powers
Default noise figure
Transmission and reception loss
radio equipment
UE category
Supported network layers (macro, small cell, 3.5 GHz, mmWave, etc.)
Supported frequency bands and respective losses, noise figures and carrier aggregation support
Carrier aggregation support and the maximum numbers of supported secondary cells in downlink and uplink
Coordinated multipoint transmission and reception (CoMP) support in downlink and uplink
Antenna pattern
Antenna gain
Diversity support
Numbers of antenna ports
Atoll enables you to assign directional antennas to different terminals, and define whether the terminal supports MIMO and
beamforming. The antenna patterns are used in coverage predictions and Monte Carlo simulations. An example of a terminal
properties window is given in the figure below.
Figure 5.37 Terminal properties window
5.6.3 Mobility Types
The mobility type defines different user speeds.
5.6.4 User Profiles
The user profiles table models the behaviour of the different user categories. Every user profile contains a list of services and
their associated parameters describing how these services are accessed by the users.
Parameters for voice services are:



The average number of calls per hour
The average duration of each call
The terminal used when requiring access to this service.
Parameters for data services are:


The average number of sessions per hour
The data volume transferred on the downlink during each session
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The data volume transferred on the uplink during each session
The terminal used when requiring access to this service.
The figure below shows a user profile window.
Figure 5.38 User profile window
5.6.5 Traffic Data
For information on traffic data cartography, see 2.2.7 Traffic Data.
5G NR Monte Carlo Simulations
The radio resource management and scheduling algorithms in a 5G NR network automatically perform the best suitable
resource allocation to users. The objective is to optimise the resource usage within cells according to the C/(I+N) conditions
at user locations. Atoll simulates this resource allocation mechanism. It calculates, for each user distribution (called a random
trial), the different network parameters such as the mobile activity, received power levels, C/(I+N) levels, antenna diversity
modes, best radio bearer available for the calculated C/(I+N), required resources to satisfy the committed and maximum
throughput demands, and aggregated as well as per-server user throughputs (peak RLC, effective RLC, and application-level)
after the allocation of resources by the scheduler. As outputs, Atoll provides the traffic loads which can then be assigned to
the different cells and the C/(I+N) coverage can be performed based on realistic simulation results.
A Monte Carlo simulation in Atoll corresponds to a given distribution of users. It is a snapshot of a 5G NR network.
5G NR Monte Carlo simulations can be analysed, displayed and stored. They can be used in a next step to generate numerous
coverage predictions.
5.7.1 Generation of Realistic User Distributions
Realistic distributions of users on the map are required as inputs to the 5G NR simulation algorithm. A “Realistic User
Distribution” corresponds to a user distribution that complies with the service and user model and the traffic data. Atoll
generates these user distributions using a Monte Carlo (statistical) algorithm.
5.7.2 Scheduling and Radio Resource Management
For each user distribution, Atoll simulates the scheduling and RRM mechanism of 5G NR cells. The simulation ends when the
scheduler has allocated resources to all the users selected for the scheduling process and has determined the traffic loads for
all the cells in the simulation.
The figure below shows an overview of the simulation algorithm.
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Figure 5.39 5G NR simulation overview
The following steps are carried out during each iteration of a 5G NR Monte Carlo simulation for all the generated mobiles:

Best server determination: Atoll determines the best server, one or more aggregated servers for carrier
aggregation, for each mobile.
Users can be rejected at this stage for "No Coverage".

Downlink calculations: The downlink calculations include the calculation of SSS, PSS, PBCH, PDSCH, and PDCCH
C/(I+N), determination of the best available bearer for the PDSCH C/(I+N), allocation of resources (RRM), and
calculation of user throughputs.
Users can be rejected at this stage for "No Service".

Uplink calculations: The uplink calculations include the calculation of PUSCH C/(I+N), determination of the best
available bearer for the PUSCH C/(I+N), uplink power control, uplink noise rise control, uplink bandwidth allocation,
resource allocation (RRM), update of uplink noise rise values for cells, and calculation of user throughputs.
Users can be rejected at this stage for "No Service".

Radio resource management and cell load calculation: Atoll uses an intelligent scheduling algorithm to perform
radio resource management.
Users can be rejected at this stage for "Scheduler Saturation," "Resource Saturation," or “Backhaul Saturation.”
Main simulation outputs are:


The cell loads (i.e., uplink and downlink traffic loads, uplink noise rise, uplink and downlink beam usage ratios), and
User throughputs.
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Note that numerous other parameters are available and stored during the simulation for further analysis. For more
information, see 6.11.5 Simulation Reports.
5.7.3 Monte Carlo Simulation Management
5G NR simulations are managed through the Simulations folder in the Atoll Explorer window. This folder is displayed in the
figure below.
Figure 5.40 5G NR simulations folder
The Simulations folder is made up of several simulation “groups”. Each group corresponds to a network configuration for
which a user-specified number of Monte Carlo simulations have been generated. As an example, different groups may
correspond to different traffic assumptions. The figure below shows the simulation creation dialog box.
When several simulation groups are available, it is possible to automatically display one group after the other, hence
animating the user distribution display on the map, at a user-defined speed using the slideshow function.
The following information is required when creating a new group of Monte Carlo simulations:





The simulation group name
The number of simulations to be run
The load and backhaul constraints to apply during simulations
The traffic maps used
The convergence criteria.
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Figure 5.41 5G NR simulation creation dialog box
Once a simulation (or a group of simulations) has been performed, simulation reports are available and simulation results can
be graphically analysed in Atoll.
5.7.4 Simulation Graphical Analysis
Graphical Display: Mobile Activity Status
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for their activity status. The different possible statuses are:



Active DL + UL: the mobile is active on both downlink and uplink
Active UL: the mobile is active on uplink only
Active DL: the mobile is active on downlink only
An example of a graphical display of a group of simulations is presented in the figure below.
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Figure 5.42 5G NR simulation display by activity status
Graphical Display: Throughput
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for the throughput.
An example of a graphical display of a group of simulations is presented in the figure below.
Figure 5.43 5G NR simulation display by throughput values
Graphical Display: Mobile Connection Status
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for their connection status. The different possible statuses are:






Connected DL + UL: the mobile is connected on both downlink and uplink
Connected UL: the mobile is connected on uplink only
Connected DL: the mobile is connected on downlink only
Scheduler Saturation: the mobile is rejected because the scheduler has reached its maximum limit
Resource Saturation: the mobile is rejected because all the resources have been allocated to other mobiles
No Service: the mobile is rejected because it is outside the coverage area.
An example of a graphical display of a group of simulations is presented in the figure below.
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Figure 5.44 5G NR simulation display by connection status
Individual Mobile Results Graphical Display
Parameters for any user can be displayed either in the results table or directly on the map (as presented in the figure below).
Figure 5.45 Individual mobile results display using the tool tip
5.7.5 Simulation Reports
Atoll provides detailed simulation results in the form of reports.
Reports of a Single Simulation
A report is available for each simulation. This report contains information about the simulation statistics, and calculation
results by sites, cell, and mobile as given in the figure below.
Figure 5.46 5G NR simulation report – Cells tab
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Figure 5.47 5G NR simulation report – Mobiles tab
The simulation results are provided at the following different levels:





Global statistics: total users attempting a connection and the corresponding break-up per service; total users
actually connected and the corresponding break-up per service.
Results per site: sum of user throughputs (peak RLC, effective RLC, and application level throughputs) for all the
cells of a site, globally and per service type, for both uplink and downlink and numbers of rejected mobiles per
rejection cause.
Results per cell: uplink and downlink traffic loads, uplink noise rise, numbers of co-scheduled MU-MIMO users, sum
of user throughputs (peak RLC, effective RLC, and application level throughputs), for both uplink and downlink,
numbers of rejected mobiles per rejection cause.
Results per mobile: geographic location, receiver height, terminal type, service, user profile, mobility, activity status
(DL/UL), serving cells, numbers of aggregated servers in downlink and uplink for carrier aggregation, path loss,
received power levels, uplink transmit power, uplink allocated bandwidth, channel and user throughputs (peak RLC,
effective RLC, and application throughputs), connection status (connected in DL, UL, DL+UL, or rejected due to no
service, scheduler saturation or resource saturation), C/(I+N) and interference levels, antenna diversity modes,
bearer, BLER, etc.
Initial conditions: parameters and traffic maps used to create the simulation.
Reports of a Group of Simulations
Atoll provides detailed simulation results averaged over a group of simulations in the form of reports. The report generated
for a simulation group contains:




Statistics: average statistics obtained from the results of all the simulations in a group
Results per site: average site results obtained from the results of all the simulations in a group
Results per cell: average cell results obtained from the results of all the simulations in a group
Initial conditions: parameters used to create the simulation group.
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Figure 5.48 5G NR simulation group report
5.7.6 Updating Cell Loads
You can store the cell loads calculated by Monte Carlo simulations in the cells data table. This enables you to update the
network cell loads based either on the average results from a simulation group or the results of from a single simulation. Cell
load values for all the cells in the network radio database are then updated with the results generated by the selected
simulation. Cell loads from a simulation, simulation group, or from the cells data table can then be used to generate coverage
prediction plots.
5.7.7 Exporting Results
You can export the simulation results as described in 2.5.1 Network Data Import and Export.
5G NR Coverage Predictions
In Atoll a coverage prediction is a plot displaying calculation results of user-selected parameters on the map and enabling
graphical as well as statistical analysis of the network behaviour. Examples of 5G NR coverage predictions are signal level,
signal quality, radio bearer, throughput plots, etc. For each pixel, Atoll calculates the required information. This data is then
graphically represented by a colour according to a user-defined legend. Different display options are available in Atoll,
depending on the calculated parameter.
Coverage predictions can be calculated for a given layer or the best layer, depending on the best server selection mechanism,
and for one, more, or all frequency carriers. Coverage predictions that depict radio parameters such as signal levels and signal
quality can be calculated for primary cells and any of the possible 4 secondary cells. Throughput coverage predictions can be
calculated for one or many aggregated servers (carrier aggregation) in both downlink and uplink.
5.8.1 Coverage Prediction Calculation and Management
Coverage predictions are performed by assuming a “probe mobile” (non-interfering terminal) on each pixel of the considered
area. The probe mobile characteristics (terminal type, mobility type, service type) are specified as inputs to the coverage
prediction in order to calculate the user-defined prediction parameter. Coverage predictions can be calculated for the best
server, the best server for each layer, and all servers, with and without overlapping.
Predictions are stored as multi-layer geographic objects in the Predictions folder of the Explorer window and can be displayed
in the map window. When several coverage predictions are available, it is possible to automatically display one prediction
after the other, hence animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
Subfolders can be created in the Predictions folder in order to group various coverage prediction objects into categories.
Coverage predictions can be directly created under a subfolder and moved from one subfolder to another using the mouse.
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5.8.2 Coverage Prediction Types
5G NR coverage predictions can be generated either based on the results from Monte Carlo simulations or on user-defined
cell load configurations. All 5G NR coverage predictions can be calculated for standalone (SA) deployment mode as well as
non-standalone (NSA) deployment mode. 5G NR cells in NSA mode only provide coverage under the LTE coverage footprint.
Figure 5.49 5G NR coverage prediction conditions
5G NR coverage prediction types and their display options available in Atoll are listed below.





Coverage by transmitter (DL)
o Transmitter
Coverage by signal level (DL)
o Reference or maximum signal level (dBm, dBµV or dBµV/m)
o RSRP level
o Path loss (dB)
Overlapping zones (DL)
o Number of servers
Downlink coverage
o Coverage by transmitter
o SS-RSRP
o SSS signal level
o PBCH signal level
o PDCCH signal level
o PDSCH signal level
o CSI-RSRP
o SSS C/N
o PBCH C/N
o PDCCH C/N
o PDSCH C/N
o CSI-RS C/N
o Best control channel beams
o Best refinement beams
o Best traffic channel beams
Downlink quality
o SSS C/(I+N)
o PBCH C/(I+N)
o PDCCH C/(I+N)
o PDSCH C/(I+N)
o CSI-RS C/(I+N)
o SS total noise (I+N)
o PBCH total noise (I+N)
o PDCCH total noise (I+N)
o PDSCH total noise (I+N)
o CSI-RS total noise (I+N)
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Downlink service areas
o Bearer
o Modulation
Downlink capacity
o Peak RLC channel throughput
o Effective RLC channel throughput
o Application channel throughput
o Peak RLC cell capacity
o Effective RLC cell capacity
o Application cell capacity
o Effective RLC allocated bandwidth throughput
o Application allocated bandwidth throughput
o Peak RLC throughput per user
o Effective RLC throughput per user
o Application throughput per user
o Number of aggregated servers
o Aggregated frequency bands
o Spectral efficiency
Uplink coverage
o PUSCH signal level
o PUSCH C/N
o Total losses
Uplink quality
o PUSCH C/(I+N)
o PUSCH total noise (I+N)
o Allocated bandwidth
o Transmission power
Uplink service areas
o Bearer
o Modulation
Uplink capacity
o Peak RLC channel throughput
o Effective RLC channel throughput
o Application channel throughput
o Peak RLC cell capacity
o Effective RLC cell capacity
o Application cell capacity
o Effective RLC allocated bandwidth throughput
o Application allocated bandwidth throughput
o Peak RLC throughput per user
o Effective RLC throughput per user
o Application throughput per user
o Number of aggregated servers
o Aggregated frequency bands
o Spectral efficiency
Coverage predictions depend on the network’s behaviour under load. These predictions can be calculated for a service,
mobility type, and user terminal equipment.
Various 5G NR coverage prediction plots are shown in the figures below.
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Figure 5.50 5G NR coverage by transmitter
Figure 5.51 5G NR coverage by SS-RSRP
Figure 5.52 5G NR coverage by PDSCH signal level
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Figure 5.53 5G NR coverage by best serving beam
Figure 5.54 5G NR coverage by SSS C/(I+N)
Figure 5.55 5G NR coverage by PDSCH C/(I+N)
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Figure 5.56 5G NR coverage by downlink bearer
Figure 5.57 5G NR coverage by downlink modulation
Figure 5.58 5G NR coverage by downlink PCell throughput
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Figure 5.59 5G NR coverage by downlink aggregated throughput
Figure 5.60 5G NR coverage by PUSCH signal level
Figure 5.61 5G NR coverage by PUSCH C/(I+N)
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Figure 5.62 5G NR coverage by uplink bearer
Figure 5.63 5G NR coverage by uplink PCell throughput
Figure 5.64 5G NR coverage by uplink aggregated throughput
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5.8.3 Coverage Prediction Reports
Atoll can generate reports for one or more coverage predictions with various detail levels as defined by the user. Reports are
spread sheet-like tables that can be printed directly from Atoll or exported to any desktop tool. An example of such a report
is given in the figure below.
Figure 5.65 5G NR coverage prediction report
5.8.4 Coverage Prediction Comparison
Comparison (difference, intersection, union, or merge) between two coverage predictions can be performed. As examples,
this functionality can be used:



To compare uplink and downlink coverage of a service. This enables you to determine uplink/downlink-limited
zones for that service.
To compare service area coverage plots of two different services. This enables you to assess the areas where one
service (e.g., VoIP) is available while the other (e.g., high speed internet) is not.
To compare service area coverage plots of two networks deployment scenarios (possibly with different
technologies). The figure below illustrates such a case by comparing GSM and LTE coverage. Note that, in this
example, LTE transmitters are installed on only some of the GSM sites.
Figure 5.66 Coverage prediction graphical comparison (GSM versus LTE example)
Atoll also enables you to carry out per-pixel arithmetical operations between coverage predictions. For example, you can
calculate the sum, difference, min, max, and average of similar calculated parameters per pixel from two coverage predictions
of the same or different technologies.
5.8.5 Coverage Prediction Export
Any coverage prediction can be exported in the following formats:
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Atoll format
ArcView SHP
MapInfo MIF and TAB
ArcView Grid TXT and ASC
Vertical Mapper GRD and GRC
BMP
PNG
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TIFF
BIL
JPEG2000
JPEG
When exported in MapInfo format, coverage prediction attributes (e.g., signal levels, transmitter IDs, etc.) are exported along
with the plot. The figure below gives an example of the exported attributes for a C/(I+N) prediction.
Figure 5.67 Coverage prediction attributes export to MapInfo
5.8.6 Point Analysis Tool
A real-time prediction analysis tool is available in Atoll. The point analysis tool is dynamically linked to the map window. The
displayed information is updated as the receiver is moved on the map window. The point analysis tool provides the downlink
signal values numerically and graphically for all cells and for the selected layer or all layers, selected channel or all channels,
terminal type, mobility type, and service type.
Based on user-defined or calculated cell load values, the point analysis tool also provides numeric values of signal levels and
signal quality for the SSS, PSS, PBCH, PDCCH, PDSCH, and PUSCH, downlink and uplink bearers, and downlink and uplink
throughput values.
The figure below shows the point analysis window as well as its link to the map window.
Receiving
Mobile
Received
Signal
Strength
information
Figure 5.68 5G NR point-to-point real-time analysis
5.8.7 Multi-Point Analysis
Atoll enables you to carry out point predictions on multiple point locations and at different heights. Multi-point analyses can
be carried out on imported lists of points, subscriber locations from fixed subscriber traffic maps, as well as points created
on the map using the mouse.
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Multi-point analyses may be useful in verifying network QoS at specific locations in case of reported incidents such as call
drops, low throughputs, etc. Multi-point analysis calculations can be based on user-defined network load conditions in the
Cells table or loads calculated using Monte Carlo simulations. The figure below shows the multi-point analysis creation dialog
box.
Figure 5.69 5G NR multi-point analysis creation dialog box
Two types of multi-point analyses are available. Point analysis results include a number of radio parameters at each point
calculated for all potential servers. These results are the same as available for one point in the Details view of the Point
Analysis tool. Fixed subscriber analysis results include more detailed results for the subscriber’s best server. These results are
similar to the results provided by a Monte Carlo simulation.
Multi-point analysis results are stored in the Multi-Point Analysis folder in the Network explorer. Once calculated, multi-point
analysis results are available in tabular form and visible on the map using symbols and colours based on calculation results.
Figure 5.70 5G NR multi-point analysis results
You can export the multi-point analysis results as described in 2.5.1 Network Data Import and Export.
5G NR Neighbour Planning
Atoll supports the following neighbour types in a 5G NR network configuration:
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Intra-technology neighbours: 5G NR cells defined as neighbours of other 5G NR cells in the same Atoll document.
Inter-technology neighbours: 5G NR cells defined as neighbours of cells which use a technology other than 5G NR.
Neighbour plans can be generated by any of the following means in Atoll:
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Importing an external neighbour plan (e.g., in Excel format)
Automatically producing a neighbour plan as described in 6.13.1 Automatic Neighbour Allocation
Graphically and/or manually creating, editing and deleting a neighbour plan as presented in 6.13.2 Graphical
Neighbour Plan Editing
Various neighbour plans can be compared. The results of an automatic neighbour allocation can be compared with the
existing neighbour plan. As well, neighbour plans from external sources can also be compared with the existing neighbour
plan in Atoll.
5.9.1 Automatic Neighbour Allocation
Neighbour lists can be generated automatically in Atoll. For each cell, potential neighbours are ranked according to their
importance. The neighbour planning algorithm considers the following user-specified parameters:
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Hysteresis zone defined by a handover start and a handover end margin with respect to the best server boundary
defined by the SS-RSRP biased by the cell individual offset and the handover margin
Maximum inter-site distance
Maximum number of neighbours
Minimum area covered (overlapping area between the reference cell and its potential neighbour).
Importance ranges for distance, coverage, adjacency, and co-site factors.
Forcing “neighbour symmetry”, “adjacent cells as neighbours”, “co-site cells as neighbours“ and/or “exceptional neighbour
pairs” is possible with Atoll. The figure below displays the automatic neighbour allocation dialog box.
Figure 5.71 5G NR automatic neighbour list generation
5.9.2 Graphical Neighbour Plan Editing
Neighbour plan can be graphically edited in Atoll. Clicking a transmitter on the map displays all its neighbour relations. All
types of neighbour relations (outwards, inwards or symmetrical) can be created, edited and/or deleted graphically. Such an
example is presented in the figures below.
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Figure 5.72 Graphical neighbour plan editing
Figure 5.73 Neighbour planning using a best server plot
5.9.3 Neighbour Consistency Check Tool
A neighbour relation audit is available in Atoll. This function enables you to determine inconsistencies in the current
neighbour plan. The figure below shows the neighbour relation conditions that can be verified using the audit.
Figure 5.74 Neighbour audit
5G NR Automatic Physical Cell ID and PRACH RSI Planning
The Atoll 5G NR AFP (Automatic Frequency Planning module) enables you to automatically configure network parameters
such as the physical cell IDs and PRACH root sequence indexes.
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The aim of the AFP is to allocate resources in a way that minimises interference following the user‐defined constraints. The
AFP assigns a cost to each constraint and then uses an iterative algorithm to evaluate possible allocation plans and propose
the allocation plan with the lowest costs. The AFP cost function comprises input elements such as interference matrices,
neighbour relations, and allowed ranges of resources for allocation.
The figure below presents the 5G NR AFP window.
Figure 5.75 5G NR AFP
5.10.1 AFP Cost Components
The AFP cost components include relations and constraints. The AFP’s automatic planning algorithm can take the following
relations into account:
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Interference-based relations, i.e., cells that interfere each other
The probability of interference is extracted from interference matrices. One or more interference matrices can be
calculated using Atoll or imported from external files in standard TXT, CSV, and IM2 formats, in order to provide
the AFP with:
o The co-channel interference probability
o The adjacent channel interference probability
Neighbour cells
The importance of each neighbour relation is determined from the neighbour relation definition. The following
neighbour relations can be taken into account:
o First-order neighbours (direct neighbours)
o Second-order neighbours (neighbours of neighbours)
o Inter-neighbours (neighbours of a common cell)
Inter-cell distance
A minimum reuse distance can be defined per cell or globally for all the cells.
The AFP can take into account the following constraints:
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For physical cell ID allocation: physical cell ID collisions and other related collisions (PSS ID and SSS ID), physical cell
ID allocation domain, effect of the frequency plan on physical cell ID allocation, etc.
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For PRACH root sequence index allocation: PRACH RSI collisions, PRACH RSI allocation domain, effect of the
frequency plan on PRACH allocation, etc.
The impact of each relation and constraint can be fine-tuned by the user by defined the associated weights. The figure below
shows the AFP constraint weights dialog box.
Figure 5.76 User-defined AFP constraint weights
5.10.2 Automatic Physical Cell ID Planning
Atoll enables you to assign physical cell IDs manually or automatically to any cell in the network. Atoll facilitates the
management of physical cell IDs by letting you create groups of physical cell IDs and domains, where each domain is a defined
set of groups. Atoll can automatically assign physical cell IDs to cells taking into account the network’s frequency plan, the
selected allocation strategy (same SSS ID per site or co-site PCIs with a regular step), allowed allocation domain, interference
matrices, reuse distance, and any constraints imposed by neighbours. It is also possible to allocate the same physical cell ID
to co-located cells using different frequency bands and whose transmitter azimuths are within 10° from each other.
Furthermore, Atoll can take into account inter-technology neighbour relations in a multi-RAT network planning environment.
Atoll takes into account physical cell ID collisions between 5G NR cells that are neighbours of the same LTE, GSM, UMTS, or
CDMA2000 cell.
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Figure 5.77 5G NR physical cell ID planning
Once the allocation is complete, you can implement the proposed allocation plan, export the results to TXT, CSV, or XML
spread sheet files, audit the physical cell IDs, analyse physical cell ID reuse and collisions on the map, and make an analysis
of physical cell ID distribution.
Figure 5.78 5G NR physical cell ID audit
5.10.3 Automatic PRACH Root Sequence Index Planning
Atoll enables you to assign PRACH root sequence indexes manually or automatically to any cell in the network. Atoll can
automatically assign PRACH root sequence indexes to cells taking into account the network’s frequency plan, allowed
allocation domain, PRACH resource block and subframe collisions between cells, interference matrices, reuse distance, and
any constraints imposed by neighbours.
It is also possible to allocate the same PRACH RSIs to co-site cells that use different resource blocks and/or subframes for
PRACH. Moreover, you can also allocate the same PRACH RSIs to co-located cells using different frequency bands and whose
transmitter azimuths are within 10° from each other.
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Once the allocation is complete, you can implement the proposed allocation plan, export the results to TXT, CSV, or XML
spread sheet files, audit the PRACH root sequence indexes, analyse PRACH root sequence index reuse and collisions on the
map, and make an analysis of PRACH root sequence index distribution.
Figure 5.79 5G NR PRACH root sequence index planning
Figure 5.80 5G NR PRACH root sequence index audit
5.10.1 Physical Cell ID and PRACH Root Sequence Index Plan Analysis
Cell Parameter Search Tool
A search tool is available in Atoll which enables you to search for frequencies, physical cell IDs, PSS IDs, SSS IDs, and PRACH
RSIs. You can display the current allocation plan of the selected parameter on the map and highlight the transmitters and
their coverage areas respectively. The tool window is shown in the figure below.
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Figure 5.81 Physical cell ID search
Cell Parameter Display on Map
You can display the frequency, physical cell ID, and PRACH root sequence index allocation on transmitters by using the
transmitters’ display settings. The figure below shows a physical cell ID plan displayed on the map.
Figure 5.82 Physical cell ID display on map
5G NR Automatic Cell Planning
The Atoll 5G NR ACP (Automatic Cell Planning) module enables you to automatically determine the best 5G NR parameter
settings for your network. The aim of the Atoll ACP is to improve network quality in terms of both coverage and capacity. For
a comprehensive description of the Atoll ACP, see 17 Automatic Cell Planning (ACP) Features.
The Atoll 5G NR ACP is capable of optimising network parameters (antenna types, heights, azimuths, tilts, transmission
powers, etc.) based on the following 5G NR quality indicators:
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SS-RSRP
SSS C/N
SSS CINR
PDSCH CINR
RLC peak throughput
Overlap
Best server distance
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1st-Nth difference
5G NR Co-planning With Other Radio Access Technologies
Atoll supports GSM/UMTS/LTE/NB-IoT/5G NR as well as CDMA2000/LTE/NB-IoT/5G NR co-planning. Other radio access
technologies can also be combined with 5G NR in Atoll. For more information, see 11 Multi-RAT Features.
Additionally, Atoll models the effect of interference from coexisting 5G NR (or OFDM) networks. This feature enables studying
the effect of interference on the 5G NR network from other parts of the same 5G NR network and from the 5G NR (or OFDM)
networks of other operators. The figure below shows the specific “Transmitter Type” parameter (Server and Interferer or
Interferer Only) required as input.
Figure 5.83 Transmitter properties window
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6 LTE/LTE-Advanced Features
The Atoll LTE module provides a comprehensive and accurate modelling of multi-band FDD and TDD heterogeneous LTE
networks. It supports all E-UTRA frequency bands and carrier widths along with detailed OFDMA and SC-FDMA frame
structure modelling. All downlink control signals, and control and traffic channels are fully modelled. Atoll LTE supports
several LTE-Advanced features such as intra-band and inter-band carrier aggregation, coordinated multipoint transmission
and reception (CoMP), and time-domain enhanced ICIC (eICIC). Atoll LTE also includes comprehensive modelling of 3D
beamforming and massive MIMO antennas.
Atoll supports all LTE modulation and coding schemes, voice, VoIP, and data services, and different user equipment. Atoll
provides the means to set up multi-service traffic maps from multiple sources: vector, raster and live traffic data. Traffic maps
are used in LTE Monte Carlo simulations for network capacity analysis including power control, interference control, RRM,
scheduling, multi-layer traffic balancing, and S1 interface backhaul constraints. Inter-cell interference coordination models
are available for analysing the improved quality due to ICIC in co-channel deployments. Coverage predictions can be
calculated based on Monte Carlo simulation results or on live network loads from the OAM in order to study coverage and
capacity of the network.
Atoll includes automatic inter- and intra-frequency neighbour planning features that allow analysing handovers in the
network. Atoll can work with multiple interference matrices from various sources: prediction-based (calculated within Atoll),
based on OAM statistics, and based on drive test measurements. The Atoll LTE AFP can automatically allocate frequencies,
physical cell IDs, and PRACH RSIs based on user-definable constraints and cost. Analysis tools enabling auditing of frequency,
physical cell ID, and PRACH RSI plans are also available.
Atoll includes integrated single RAN–multiple RAT network design capabilities for cellular radio access technologies including
5G NR, LTE, NB-IoT, UMTS, GSM, and CDMA. It features a multi-technology network database, a unified traffic model, and a
combined Monte Carlo simulator. The Atoll LTE ACP can be used to automatically optimise network parameters to increase
coverage and capacity. It can also carry out site selection for greenfield and site activation for densification scenarios.
An overview of the LTE modelling in Atoll is shown in the figure below.
Figure 6.1
LTE network modelling in Atoll
LTE/LTE-Advanced Network Model
The LTE network model comprises radio network elements such as sites, transmitters, and cells. An LTE eNode-B is equivalent
to a site, its transmitters with one or more carriers (cells) each.
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Figure 6.2
LTE network model
6.2.2 Sites
A site represents the physical location where eNode-Bs can be installed. An example of a site properties window is shown in
the figure below.
Figure 6.3
Site properties window
Site parameters are:
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Geographic coordinates
Altitude (user-defined or automatically extracted from the terrain elevation data)
Any user-defined flags and parameters such as address, owner, deployment phase, etc.
The maximum downlink and uplink S1 interface throughputs: The S1 interface connects eNode-Bs to the evolved
packet core (EPC) entities, the mobility management entity (MME) and the serving gateway (S-GW). The capacity
of the S1 interface between the eNode-B and the serving gateway imposes a limit on the aggregate throughput
served by the cells of the same eNode-B. This also imposes a limit on the throughput of each individual user served
by the eNode-B. Here you must enter the capacity of the S1-U interface (S1-U is the user-plane interface between
eNode-Bs and the serving gateways). The maximum S1 interface throughputs that you enter here can be taken into
account in Monte Carlo simulations as backhaul constraints.
6.2.3 Transmitters
Transmitters in Atoll correspond to sectors and antennas installed at a site. The main transmitter parameters are:
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Transmitter name and the name of the site where it is installed
X and Y coordinates
Transmitter type (server and interferer, or interferer only)
Active/inactive (to be included in calculations or not)
Main, secondary, and 3D beamforming antennas
Numbers of transmission and reception antenna ports for MIMO
Antenna heights, azimuths, and tilts
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A flag to indicate antenna sharing with other repeaters
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Tower mounted amplifier (TMA)
Feeder type and its transmission and reception lengths
Maximum range
Any user-defined flags and parameters
An example of a transmitter properties window is shown in the figure below.
Figure 6.4
LTE transmitter properties window
6.2.4 Cells
Atoll supports multi-band, multi-carrier LTE network deployments. In Atoll, cells model frequency carriers used at a
transmitter. A transmitter can support cells with scalable carrier widths and different carriers. Each cell has its own radio
resources and parameters, including:
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Cell name and the name of the transmitter to which the cell belongs
Frequency band and carrier
Network layer (macro, small cell, 800 MHz, 2600 MHz, etc.) to which the cell belongs (hence also the associated
priority)
Cell selection and handover parameters (cell individual offset used for cell range expansion, cell selection threshold
known as ThresXHighP, and handover margin)
Cell type: whether the cell is an LTE (release 8/9) and/or LTE-Advanced (release 10) cell
Physical cell ID, PSS ID, SSS ID
Cyclic prefix
PDCCH overhead, PUCCH overhead
PRACH preamble format
List of allocated PRACH root sequence indexes
AFP parameters: allocation status (allocated, locked, etc.) for carrier, PSS, SSS, and PRACH RSI, physical cell ID
domain, number of required PRACH root sequence indexes, minimum reuse distance, list of resource block indexes
and subframe numbers used for PRACH
Transmission powers: maximum power, RS EPRE, and SS, PBCH, PDCCH, and PDSCH EPRE offsets
Minimum RSRP
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Radio equipment
TDD frame configuration and TDD special subframe configuration
Downlink and uplink diversity support (diversity, SU-MIMO, MU-MIMO)
RRM parameters: scheduler type, maximum number of simultaneous users
eICIC/ICIC parameters: ABS (almost blank subframe) pattern, ICIC support, ICIC mode, cell-edge margin, cell-edge
PRBs
Fractional power control and noise rise control parameters: FPC factor, maximum uplink noise rise, maximum
PUSCH C/(I+N)
Resource allocation constraints: maximum uplink and downlink traffic loads
Cell loads and resource allocation results: uplink and downlink traffic loads, uplink noise rise, cell-edge traffic ratio,
ICIC uplink noise rise, uplink and downlink beam usage ratios,, numbers of co-scheduled MU-MIMO users, numbers
of connected users in downlink and uplink
These parameters can be outputs of Monte Carlo simulations as well as user-defined values.
Inter-technology interference: downlink and uplink noise rise
Neighbour parameters: maximum numbers of neighbours and neighbours lists
Any user-defined flags and parameters
The figure below presents an example of a transmitter with a single cell.
Figure 6.5
LTE cell parameters
6.2.5 Site Templates
A site template is made up of one or more transmitters and cells located on the same site. Site templates can be created and
edited as needed. Building a network is facilitated by working with site templates rather than single site/transmitter/cell. By
default some LTE site templates are available for dense urban, urban, suburban, and rural environments.
6.2.6 Repeaters
A repeater receives, amplifies, and retransmits signals. Repeaters are used to extend the coverage of their donors. Atoll
models selective as well as non-selective RF repeaters, optic fibre repeaters, microwave repeaters, and remote antennas.
Selective RF repeaters only repeat signals from their donor transmitters whereas non-selective RF repeaters receive and
retransmit wanted signals as well as interference.
The main parameters of a repeater are:
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Donor transmitter name
X and Y coordinates
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Active/inactive (to be included in calculations or not)
Main and secondary antennas
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other repeaters
Total gain
Amplifier gain
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Feeder type and its transmission and reception lengths
Any user-defined flags and parameters
The figure below presents the repeater properties window while the figure below that gives an example of a best server
prediction plot with a repeater.
Figure 6.6
Repeater properties window
RF repeater
Donor transmitter
Figure 6.7
RF repeater coverage plot
6.2.7 Relay Nodes
Relay Nodes (RN) are low power base stations that provide enhanced coverage and capacity at cell edges and traffic hotspots.
Relay nodes can also be used to connect to remote areas without a fibre backhaul connection. Relay nodes are connected to
the donor eNB (DeNB) via a radio interface Un which is an extension of the E-UTRAN air interface Uu. The donor cell provides
LTE-based radio backhaul to its relay nodes, which means that the donor cell’s radio resources are shared between its served
users and its relay nodes.
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Atoll allows you to create relay nodes connected to donor cells through the LTE air interface. Apart from the off-air backhaul
link with the donor cell, relay nodes are independent LTE cells. Relay nodes have the same parameters as any standard eNB.
As relay nodes are linked to donor cells through an LTE-based backhaul link, the relay link properties can be defined in Atoll.
The main parameters of a relay link are:
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Donor cell name
Antenna model
Antenna heights, azimuths, and tilts
Propagation model
Feeder type and its transmission and reception lengths
The figure below presents the relay link properties window.
Figure 6.8
Relay link properties window
Atoll can also determine the best donor cells for relay nodes and to calculate the associated backhaul link capacity based on
the donor cell resources dedicated to relay node backhaul. The figure below gives an example of a donor macro cell serving
multiple relay nodes.
Donor cells
Relay nodes
Figure 6.9
Relay nodes
LTE/LTE-Advanced Network Parameters
Atoll allows setting and modifying network-level configurations and parameters applicable to the entire project.
6.3.1 Frequency Bands and Carriers
Atoll supports multi-band FD- and TD-LTE networks. Atoll supports all carrier widths and EUTRA frequency bands included in
the 3GPP specifications.
A frequency band is characterized by its reference frequency that is used by Atoll for path loss calculations. Each carrier within
a frequency band is characterised by its duplexing mode, its downlink and uplink centre frequencies, its downlink and uplink
bandwidths, and its absolute radio frequency channel numbers (ARFCN).
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You can add, modify, and delete frequency bands and carriers in Atoll as required. A number of EUTRA frequency bands are
available by default. An example of an LTE carrier definition is shown in the figure below.
Figure 6.10 LTE carrier definition
6.3.2 Global Network Settings
LTE-specific parameters that are applicable to the entire network are modelled in Atoll as global network settings. These
parameters include the downlink transmission power calculation method, best server selection criterion and method,
diversity mode (SU-MIMO, MU-MIMO) selection criteria, the interference calculation method, and the uplink power
adjustment margin. The figure below presents the network level properties dialog box.
Figure 6.11 LTE network level parameters
6.3.3 Network Layers
An LTE network can be deployed in multiple layers of heterogeneous cells, i.e., of different sizes (macro, micro, small cells,
etc.), and possibly using different frequencies. Such LTE networks are referred to as HetNets, or heterogeneous networks.
Atoll enables you to define network layers with different priorities and supported user speed limits. During cell selection,
network layer parameters are taken into account to determine the serving cells.
The figure below gives an example of LTE heterogeneous network layers that can be defined and deployed in Atoll.
Figure 6.12 LTE network layers table
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6.3.4 Schedulers
In Atoll, schedulers perform the allocation and management of radio resources according to the QoS classes of the services
being accessed by the selected users. Various scheduling methods are available in Atoll, including proportional fair, round
robin, maximum C/I, etc., as well as the support for multi-user diversity gains specific to proportional fair schedulers.
Figure 6.13 Default LTE schedulers
6.3.5 UE Categories
UE categories define combined uplink and downlink capabilities of user equipment. The parameters set by the UE categories
include physical and transport channel parameters in downlink and uplink, and the layer 2 buffer size.
Figure 6.14 Default LTE UE categories
6.3.6 Radio Equipment
LTE radio equipment model the transmission and reception characteristics of cells and user terminals. Bearers, bearer
selection thresholds, required thresholds for using SU-MIMO and MU-MIMO, secondary cell activation thresholds, quality
indicator graphs, and MIMO gains are defined in LTE radio equipment.
LTE radio bearers are used to carry user data on the PDSCH and the PUSCH. A bearer refers to a combination modulation and
coding scheme. The radio bearers table lists the available radio bearers in downlink and uplink. You can add, remove, and
modify bearer properties according to your network and equipment.
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Figure 6.15 LTE radio equipment bearers
Figure 6.16 LTE bearer selection thresholds
Figure 6.17 LTE quality indicator graphs
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Diversity gains, SU-MIMO throughput gains (as a function of PDSCH or PUSCH C/(I+N)), and MU-MIMO capacity gains (as a
function of the number of co-scheduled users) can be defined for each equipment for different numbers of transmission and
reception antennas, modulation and coding schemes, and user speeds.
Figure 6.18 PDSCH and PUSCH MIMO gains
Figure 6.19 PBCH and PDCCH diversity gains
Also, interference reduction factors can be defined for each ratio equipment considering the receiver characteristics of the
equipment with respect to various carrier widths.
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Figure 6.20 Interference reduction factors (adjacent channel selectivity)
LTE/LTE-Advanced 3D Beamforming and Massive MIMO
Massive MIMO comprises 3D beamforming combined with multi-user co-scheduling which results in both improved signal
quality at the user locations as well as increased system capacity. Massive MIMO systems comprise base stations with a large
number of antennas, greater than the number of served users. The system is capable of allocating the same frequency and
time resources to various co-scheduled users by using different beams to serve them simultaneously.
Atoll’s 3D beamforming model enables defining all the possible beam patterns that the beamforming antenna is capable of
forming. During calculations, sectors using 3D beamforming antennas serve their users through beams that provide the
highest gains towards user locations in 3D.
Figure 6.21 Example of 3D beamforming
For multi-user co-scheduling, Atoll allows the definition of MU-MIMO capacity gains as a function of the number of coscheduled MU-MIMO users. Different MU-MIMO throughput gain graphs can be defined for different combinations of the
number of transmission and reception antennas, user speeds, and radio bearers.
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Figure 6.22 Example of 3D beamforming coverage
The following sections describe Atoll’s 3D beamforming and massive MIMO features.
6.4.2 3D Beamforming Models
Atoll’s 3D beamforming models enable beamforming in both horizontal and vertical planes. The Atoll 3D beamforming allows
you to define any 3D beamforming massive MIMO antenna by its physical characteristics:
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M: Number of co-polar or cross-polar elements in a column
N: Number of co-polar or cross-polar elements in a row
P: Co-polar or cross-polar configuration
dV: Vertical inter-element spacing in multiples of wavelength
dH: Horizontal inter-element spacing in multiples of wavelength
Figure 6.23 64T64R 3D beamforming massive MIMO antennas
All radiating elements are usually manufactured using the same materials and with the same physical aspects and
characteristics. Therefore, all radiating elements of a beamforming antenna panel are assumed to have the same radiation
pattern. This radiation pattern is called the single-element pattern.
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P
A
P
A
Figure 6.24 Schematic diagram of a 64T64R 3D beamforming massive MIMO antenna
Figure 6.25 64T64R 3D beamforming massive MIMO antenna properties dialog box in Atoll
A beamforming antenna does not always use all the M x N elements to create beams. If all the elements are used to create a
beam, no multiplexing or co-scheduling of users is possible. Therefore, a M x N beamformer may create beams using a subset
of the vertical and horizontal elements (assumed to always be physically adjacent), referred to as m and n.
Atoll allows you to import measured radiation patterns of multiple beams, each pointing in a different direction and/or
created using a different number of active elements. If you do not have actual radiation patterns available, Atoll can calculate
theoretical beam patterns in different directions for you.
3D beamforming antennas may, and usually, use different beams for control channels than traffic channels. Control channel
beams are usually wider in order to provide coverage to the whole cell and traffic beams are narrower to focus on the served
users. Atoll allows you to define control channel beams (RS, SSS, PSS, PBCH) and traffic channel beams (PDSCH, PDCCH, and
PUSCH).
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Figure 6.26 3D traffic channel beams created using an 8x8 matrix
6.4.3 3D Beam Pattern Generator
Atoll includes a 3D beam pattern generation tool that allows you to create beams in various directions using different
numbers of antenna elements, hence providing different gains.
Figure 6.27 3D beam pattern generator
Atoll’s 3D beam generator can calculate beam patterns for any uniform linear array (ULA) and uniform planar array (UPA)
beamforming antennas comprising any numbers of horizontal and vertical elements.
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Y
N
φ
M
Z
θ
X
Figure 6.28 Uniform planar array model
Atoll first calculates the steering vector of the planar array towards any given direction (θ, φ) for each combination of m and
n antenna elements:
𝑇
𝑆⃗(𝜃,𝜑) = [1 … 𝑒 𝑗2𝜋(𝑛𝑑𝐻 sin 𝜃 cos 𝜑+𝑚𝑑𝑉 sin 𝜑) … 𝑒 𝑗2𝜋{(𝑁−1)𝑑𝐻 sin 𝜃 cos 𝜑+(𝑀−1)𝑑𝑉 sin 𝜑} ]
Then Atoll calculates the beamforming weights for any (n, m)th antenna element that when multiplied with the steering vector
tend to maximize the array factor in the direction (θ, φ):
𝑇
𝑤
⃗⃗⃗(𝜃,𝜑) = [1 … 𝑒 −𝑗2𝜋(𝑛𝑑𝐻 sin 𝜃 cos 𝜑+𝑚𝑑𝑉 sin 𝜑) … 𝑒 −𝑗2𝜋{(𝑁−1)𝑑𝐻 sin 𝜃 cos 𝜑+(𝑀−1)𝑑𝑉 sin 𝜑} ]
The array factor is calculated as the scalar product between the above two vectors:
𝐴𝐹 = |𝑆⃗(𝜃,𝜑) ∙ 𝑤
⃗⃗⃗(𝜃,𝜑) |
The beam patterns are then calculated by multiplying the array factor with the single element pattern.
6.4.4 3D Beam Usage Calculation
Each beam formed by a 3D beamforming antenna serves a certain number of users, or in other words, a certain amount of
traffic goes through each beam. Atoll models this aspect as a beam usage ratio. The usage ratio of each beam can be userdefined, i.e., imported from an R&D simulation tool, or calculated by Atoll based on the surface areas or traffic covered by
each beam.
The beam usage ratios represent how often each beam is used and hence how much each beam interferes its surrounding
cells and their traffic. Beam usage ratios are therefore used for calculating interference in various directions for interferencebased calculations of the PDSCH and PUSCH C/(I+N), and hence throughputs.
Atoll enables you to calculate beam usage ratios either approximately based on coverage predictions, or more precisely using
Monte Carlo simulations.
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Figure 6.29 Beam usage calculation based on coverage predictions
Figure 6.30 Example of beam usage ratios for uniformly distributed traffic
6.4.5 Massive MIMO
Atoll supports the following transmission modes for MIMO, which can be combined with each other under user-definable
conditions:

Transmit and receive diversity: For transmit or receive diversity, MIMO systems use more than one transmission or
reception antennas to send or receive more than one copy of the same signal. The signals are constructively
combined (using optimum selection or maximum ratio combining) at the receiver to extract the useful signal.
As the receiver gets more than one copy of the useful signal, the signal level at the receiver after combination of all
the copies is more resistant to interference than a single signal would be. Therefore, diversity improves the C/(I+N)
at the receiver. It is often used for the regions of a cell that have insufficient C/(I+N) conditions.
In Atoll, you can set whether a cell supports transmit or receive diversity. Diversity gains on downlink and uplink
can be defined in the radio equipment for different numbers of transmission and reception antenna ports, user
speeds, and radio bearers.

SU-MIMO: For SU-MIMO, MIMO systems use more than one transmission antenna to send different signals (data
streams) on each antenna. The numbers of MIMO data streams are referred to as the MIMO rank. Using SU-MIMO
with a MIMO rank of N theoretically increases the user throughput by N times.
In Atoll, you can set whether a cell supports SU-MIMO. SU-MIMO throughput gains can be defined in the radio
equipment for different radio conditions, numbers of transmission and reception antenna ports, user speeds, and
radio bearers.
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Figure 6.31 Example of SU-MIMO throughput gains as a function of radio conditions

MU-MIMO: MU-MIMO enables co-scheduling of spatially dispersed users in the same frequency-time radio
resources. MU-MIMO can provide considerable capacity gains.
In Atoll, you can set whether a cell supports MU-MIMO, and either enter the average numbers of co-scheduled
users yourself or have Atoll calculate it for you using Monte Carlo simulations. MU-MIMO capacity gains can be
defined in the radio equipment for different numbers of co-scheduled users, numbers of transmission and reception
antenna ports, user speeds, and radio bearers.
Figure 6.32 Example of MU-MIMO capacity gains as a function of the number of co-scheduled users
Massive MIMO is the capability to combine all of the above-mentioned MIMO transmission modes using a very large number
of base station antennas. 3D beamforming enables massive MIMO systems to co-schedule multiple spatially non-correlated
users.
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Figure 6.33 Example of throughput prediction plots without (top-left) and with (bottom-right) massive MIMO
Massive MIMO
Conventional MIMO
Gain
Figure 6.34 Comparison of massive MIMO throughputs with conventional MIMO
LTE/LTE-Advanced Carrier Aggregation
Atoll supports different modes of carrier aggregation:



Intra-eNode-B carrier aggregation: Only cells that belong to the same site can perform carrier aggregation with each
other.
Multi-eNode-B carrier aggregation: Cells belonging to any site can perform carrier aggregation with each other.
Group-based carrier aggregation: Cells belonging to the same group can perform carrier aggregation with each
other.
Group-based carrier aggregation mode models a C-RAN-based centralised architecture for carrier aggregation where cells
belonging to the same group are managed by the same BBU pool. Cells of the same group can correspond to the same or
different eNBs/RRUs including macro, micro, and small cells.
Atoll enables you to create carrier aggregation cell groups by grouping cells in the Network explorer as well as, geographically,
grouping cells on the map using polygons. It is also possible to import such cell groups from external spread sheets. Atoll
allows you to view cell groups on the map using coverage predictions as well as using the Find on Map tool.
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Figure 6.35 C-RAN architecture with a virtual BBU pool managing multiple RRUs
For each user terminal, Atoll also allows you to define the combinations of frequency bands that can be aggregated with each
other.
Figure 6.36 List of frequency bands allowing carrier aggregation for a user terminal
Carrier aggregation also enables inter-cell interference coordination on the PDCCH; also known as cross-carrier scheduling.
PDCCH signal quality must be maintained such that it is properly received by cell-edge users. A BLER (block-error rate) of 1%
on the PDCCH may result in a BLER as high as 10% on the PDSCH. For this purpose, the PDCCH may be transmitted with a
higher power than the traffic channel causing inter-cell interference on the PDCCH. Cross-carrier scheduling enables UEs to
receive the PDCCH on different carriers and hence reduce inter-cell interference on the PDCCH.
Without cross-carrier scheduling, the downlink scheduling assignments on PDCCH are valid for the component carrier (CC)
on which they were transmitted. With cross-carrier scheduling, the PDSCH is received on a component carrier other than the
one on which PDCCH is received. Cross-carrier scheduling only applies to secondary cells (SCells) and does not apply to
primary cells (PCells). PCells are always scheduled via their own PDCCH.
Atoll models the interference reduction on the PDCCH due to cross-carrier scheduling by eliminating the PDCCH of SCells that
are being scheduled through the PDCCH of a PCell.
LTE/LTE-Advanced Coordinated Multipoint Operation (CoMP)
Atoll supports different modes of coordinated multipoint transmission and reception (CoMP):



Downlink coordinated scheduling
Downlink dynamic point selection
Downlink joint transmission (coherent)
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Downlink joint transmission (non-coherent)
Uplink coordinated scheduling
Uplink joint reception
In Atoll, CoMP is based on a C-RAN-based centralised architecture where cells belonging to the same CoMP set are managed
by the same BBU pool. Cells of the same CoMP set can correspond to the same or different eNBs/RRUs including macro,
micro, and small cells.
Atoll enables you to create CoMP sets by grouping cells in the Network explorer as well as, geographically, grouping cells on
the map using polygons. It is also possible to import such cell groups from external spread sheets. Atoll allows you to view
cell groups on the map using coverage predictions as well as using the Find on Map tool.
LTE/LTE-Advanced Inter-Cell Interference Coordination (ICIC)
Atoll supports different ICIC methods based on fractional frequency reuse (FFR) as shown in the figures below. Without
fractional frequency reuse, cells transmit at constant power over the entire duration of the frame and across all the resource
blocks. The fact that neighbouring cells use the same resource blocks leads to high interference and poor signal quality at cell
edges.




Time-switched FFR: All the power is concentrated on some of the resource blocks during a part of the frame while
others are not transmitted at all. During the rest of the frame, the same power is transmitted over all the resource
blocks. Cell edges of neighbouring cells are covered by different resource blocks to avoid interference.
Hard FFR: All the power is concentrated on some of the resource blocks, while others are not transmitted at all.
Neighbouring cells use different resource blocks to avoid interference throughout the coverage area.
Soft FFR: Some resource blocks are transmitted at higher power than others. Cell edges of neighbouring cells are
covered by different resource blocks to avoid interference.
Partial soft FFR: Some resource blocks are transmitted at higher power than others, and some are not transmitted
at all. Cell edges of neighbouring cells are covered by different resource blocks to avoid interference.
Figure 6.37 No ICIC
Figure 6.38 ICIC using time-switched fractional frequency reuse
Figure 6.39 ICIC using hard fractional frequency reuse
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Figure 6.40 ICIC using soft fractional frequency reuse
Figure 6.41 ICIC using partial soft fractional frequency reuse
LTE/LTE-Advanced Enhanced ICIC (eICIC)
Enhanced inter-cell interference coordination (eICIC), also known as time-domain inter-cell interference coordination, is a
means to enable traffic offloading from macro cells to small cells in a heterogeneous networks (HetNets) using cell range
expansion.
eICIC is performed by defining Almost Blank Subframe (ABS) patterns coordinated across different cells over the X2 interface.
ABS, or almost blank subframes, are subframes with reduced transmit power (or no transmission) on some physical channels,
hence the interference reduction.
In heterogeneous networks using eICIC, macro cells use almost blank subframes (ABS) to identify the subframes on which
they will not issue any scheduling grants (UL or DL), which creates opportunities for coordinated small cells to schedule their
cell-edge users under good radio conditions thus created. Usually, the same ABS pattern is used within a region. A region may
be a macro cell and small cells covered/interfered by this macro cell or a larger region with more than one macro cells and
small cells.
Macro Cell
Protected
resources
Small Cell UE
Protected
resources
Macro Cell UE
Small Cell
Figure 6.42 Enhanced inter-cell interference coordination (eICIC)
In Atoll, eICIC is modelled by defining the per-cell ABS (almost blank subframe) patterns. Exact collision between subframes
is calculated according to the patterns used by different cells for the calculation of interference. The available cell resources
are also affected by the number of almost blank subframes in the cell.
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Figure 6.43 Downlink service areas with and without eICIC and cell range expansion
LTE/LTE-Advanced License-Assisted Access (LAA)
LTE cells may be deployed using unlicensed frequency bands, i.e., in frequency bands usually used for Wi-Fi. Such a
deployment is often called LTE-U, meaning LTE-Advanced in unlicensed spectrum.
LTE-U cells must respect the duty cycle constraints imposed by the regulations governing unlicensed frequency bands, and
are not allowed to create interference by continuously transmitting control signals and channels. Therefore, LTE-U cells are
not discoverable by LTE user terminals, as they only transmit and receive traffic channels. These LTE-U phantom cells require
a license-assisted access through LTE cells operating in licensed spectrum. Once discovered, the LTE-U cells may carry all the
user-plane data and leave only the control-plane communications for the licensed LTE cell.
Atoll enables creating groups of cells operating in different frequency bands and defining that all the user-plane data is to be
carried by the LTE-U cells.
Figure 6.44 Example of a group of LAA cells
LTE/LTE-Advanced Traffic Model
In Atoll, the radio network traffic is modelled using Monte Carlo simulations. According to the definition of the services and
users in the network, and depending on the traffic cartography (traffic data), realistic distributions of users are generated and
used as input to the scheduling and radio resource management algorithms.
Service and user behaviours are modelled in Atoll through different tables that provide information about:

The services available in the network
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The terminals compatible with the network
The mobility types
The user profiles describing the way users access different services
The LTE traffic model is shown in the figure below.
Figure 6.45 LTE traffic model
6.10.2 Services
The services table describes the services that are available in the network (Internet, VoLTE, VoIP, etc.). Both voice and data
type services are supported and have specific parameters. The main service parameters are:











Service type
Uplink and downlink activity factors
Supported network layers (macro, small cell, 800 MHz, 2600 MHz, etc.)
QoS class identifier (QCI) and its related priority
Intra-QCI priority level
Lowest and highest supported modulations
Uplink and downlink maximum throughput demands (MBR)
Uplink and downlink minimum throughput demands (GBR)
Uplink and downlink average requested throughputs
Throughput conversion parameters from RLC to Application layer
Body loss
An example of a service properties window is presented in the figure below.
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Figure 6.46 Service properties window
Voice over LTE (VoLTE) Service
Voice over LTE (VoLTE) is based on the IP Multimedia Subsystem (IMS), with specific profiles for control and user planes of
voice service on LTE. In other words, VoLTE is a voice service delivered as data flows within the LTE data bearer. VoLTE does
not depend on legacy circuit-switched voice services and networks, which was the case for CS fallback. VoLTE has up to three
times more voice and data capacity than UMTS and up to six times more than GSM.
VoLTE uses the Adaptive Multi-Rate Wideband (AMR-WB) speech audio coding standard. AMR-WB provides better speech
quality using a speech bandwidth of 50–7000 Hz compared to narrowband speech codecs which are optimized for wireline
quality of 300–3400 Hz. AMR-WB is codified as G.722.2, an ITU-T standard speech codec.
In Atoll, VoLTE is modelled by defining a voice service with the minimum throughput demands as the same as the maximum
throughput demands, and scaling factor between the RLC and application throughputs for modelling the codec overheads.
The following figure shows an example of the VoLTE service using the AMR 12.65 kbps codec.
Figure 6.47 Example of VoLTE service modelling in Atoll
6.10.3 Terminals
The terminals table describes the terminals that can be used in the network, cell phones, smartphones, in-car navigation
devices, etc. The following parameters model a terminal:
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











Atoll 3.4.0 Technical Overview
Minimum and maximum transmission powers
Default noise figure
Transmission and reception loss
radio equipment
UE category
Supported network layers (macro, small cell, 800 MHz, 2600 MHz, etc.)
Supported frequency bands and respective losses, noise figures and carrier aggregation support
Carrier aggregation support and the maximum numbers of supported secondary cells in downlink and uplink
Coordinated multipoint transmission and reception (CoMP) support in downlink and uplink
Antenna pattern
Antenna gain
Diversity support: MIMO and beamforming
Numbers of antenna ports
Atoll enables you to assign directional antennas to different terminals, and define whether the terminal supports MIMO and
beamforming. The antenna patterns are used in coverage predictions and Monte Carlo simulations. An example of a terminal
properties window is given in the figure below.
Figure 6.48 Terminal properties window
6.10.4 Mobility Types
The mobility type defines different user speeds.
6.10.5 User Profiles
The user profiles table models the behaviour of the different user categories. Every user profile contains a list of services and
their associated parameters describing how these services are accessed by the users.
Parameters for voice services are:



The average number of calls per hour
The average duration of each call
The terminal used when requiring access to this service.
Parameters for data services are:




The average number of sessions per hour
The data volume transferred on the downlink during each session
The data volume transferred on the uplink during each session
The terminal used when requiring access to this service.
The figure below shows a user profile window.
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Figure 6.49 User profile window
6.10.6 Traffic Data
For information on traffic data cartography, see 2.2.7 Traffic Data.
LTE/LTE-Advanced Monte Carlo Simulations
The radio resource management and scheduling algorithms in an LTE network automatically perform the best suitable
resource allocation to users. The objective is to optimise the resource usage within cells according to the C/(I+N) conditions
at user locations. Atoll simulates this resource allocation mechanism. It calculates, for each user distribution (called a random
trial), the different network parameters such as the mobile activity, received power levels, C/(I+N) levels, antenna diversity
modes, best radio bearer available for the calculated C/(I+N), required resources to satisfy the committed and maximum
throughput demands, and aggregated as well as per-server user throughputs (peak RLC, effective RLC, and application-level)
after the allocation of resources by the scheduler. As outputs, Atoll provides the traffic loads which can then be assigned to
the different cells and the C/(I+N) coverage can be performed based on realistic simulation results.
A Monte Carlo simulation in Atoll corresponds to a given distribution of users. It is a snapshot of an LTE network.
LTE Monte Carlo simulations can be analysed, displayed and stored. They can be used in a next step to generate numerous
coverage predictions.
6.11.1 Generation of Realistic User Distributions
Realistic distributions of users on the map are required as inputs to the LTE simulation algorithm. A “Realistic User
Distribution” corresponds to a user distribution that complies with the service and user model and the traffic data. Atoll
generates these user distributions using a Monte Carlo (statistical) algorithm.
6.11.2 Scheduling and Radio Resource Management
For each user distribution, Atoll simulates the scheduling and RRM mechanism of LTE cells. The simulation ends when the
scheduler has allocated resources to all the users selected for the scheduling process and has determined the traffic loads for
all the cells in the simulation.
The figure below shows an overview of the simulation algorithm.
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Figure 6.50 LTE simulation overview
The following steps are carried out during each iteration of an LTE Monte Carlo simulation for all the generated mobiles:

Best server determination: Atoll determines the best server, one or more aggregated servers for carrier
aggregation, and one or more coordinated servers for CoMP, for each mobile.
Users can be rejected at this stage for "No Coverage".

Downlink calculations: The downlink calculations include the calculation of RS, SS, PBCH, PDSCH, and PDCCH
C/(I+N), determination of the best available bearer for the PDSCH C/(I+N), allocation of resources (RRM), and
calculation of user throughputs.
Enhanced inter‐cell interference coordination (eICIC or time‐domain ICIC) is performed on the downlink if ABS
patterns have been defined for cells. Interference calculation is based on the collisions between normal and blank
subframes used by the different cells. Frequency‐domain inter‐cell interference coordination is performed on the
downlink if the cell supports ICIC. Interference calculation is based on the probabilities of collision between the cell‐
centre and cell‐edge resources used by the different cells.
Users can be rejected at this stage for "No Service".

Uplink calculations: The uplink calculations include the calculation of PUSCH & PUCCH C/(I+N), determination of the
best available bearer for the PUSCH & PUCCH C/(I+N), uplink power control, uplink noise rise control, uplink
bandwidth allocation, resource allocation (RRM), update of uplink noise rise values for cells, and calculation of user
throughputs.
Enhanced inter‐cell interference coordination (eICIC or time‐domain ICIC) is performed on the uplink if ABS patterns
have been defined for cells. Interference calculation is based on the collisions between normal and blank subframes
used by the different cells. Frequency‐domain inter‐cell interference coordination is performed on the uplink if the
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cell supports ICIC. Interference calculation is based on the probabilities of collision between the cell‐centre and cell‐
edge resources used by the different cells.
During uplink noise rise control, if the maximum uplink noise rise is higher than the actual noise rise for a cell, the
maximum PUSCH C/(I+N) of its neighbour cells is increased by the difference. This allows the users served by the
neighbour cells to transmit at higher powers, i.e., they are allowed to create more interference. If the maximum
uplink noise rise is less than the actual noise rise for a cell, the maximum PUSCH C/(I+N) of its neighbour cells is
decreased by the difference. This causes the users served by the neighbour cells to transmit at lower powers, i.e.,
they are forced to create less interference. This can also lead to an increase or decrease in the number of users
served by the neighbouring cells in the uplink.
Users can be rejected at this stage for "No Service".

Radio resource management and cell load calculation: Atoll uses an intelligent scheduling algorithm to perform
radio resource management.
Users can be rejected at this stage for "Scheduler Saturation," "Resource Saturation," or “Backhaul Saturation.”
Main simulation outputs are:


The cell loads (i.e., uplink and downlink traffic loads, uplink noise rise, uplink and downlink beam usage ratios), and
User throughputs.
Note that numerous other parameters are available and stored during the simulation for further analysis. For more
information, see 6.11.5 Simulation Reports.
6.11.3 Monte Carlo Simulation Management
LTE simulations are managed through the Simulations folder in the Atoll Explorer window. This folder is displayed in the figure
below.
Figure 6.51 LTE simulations folder
The Simulations folder is made up of several simulation “groups”. Each group corresponds to a network configuration for
which a user-specified number of Monte Carlo simulations have been generated. As an example, different groups may
correspond to different traffic assumptions. The figure below shows the simulation creation dialog box.
When several simulation groups are available, it is possible to automatically display one group after the other, hence
animating the user distribution display on the map, at a user-defined speed using the slideshow function.
The following information is required when creating a new group of Monte Carlo simulations:





The simulation group name
The number of simulations to be run
The load and S1 interface backhaul constraints to apply during simulations
The traffic maps used
The convergence criteria.
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Figure 6.52 LTE simulation creation dialog box
Once a simulation (or a group of simulations) has been performed, simulation reports are available and simulation results can
be graphically analysed in Atoll.
6.11.4 Simulation Graphical Analysis
Graphical Display: Mobile Activity Status
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for their activity status. The different possible statuses are:



Active DL + UL: the mobile is active on both downlink and uplink
Active UL: the mobile is active on uplink only
Active DL: the mobile is active on downlink only
An example of a graphical display of a group of simulations is presented in the figure below.
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Figure 6.53 LTE simulation display by activity status
Graphical Display: Throughput
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for the throughput.
An example of a graphical display of a group of simulations is presented in the figure below.
Figure 6.54 LTE simulation display by throughput values
Graphical Display: Mobile Connection Status
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for their connection status. The different possible statuses are:






Connected DL + UL: the mobile is connected on both downlink and uplink
Connected UL: the mobile is connected on uplink only
Connected DL: the mobile is connected on downlink only
Scheduler Saturation: the mobile is rejected because the scheduler has reached its maximum limit
Resource Saturation: the mobile is rejected because all the resources have been allocated to other mobiles
No Service: the mobile is rejected because it is outside the coverage area.
An example of a graphical display of a group of simulations is presented in the figure below.
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Figure 6.55 LTE simulation display by connection status
Individual Mobile Results Graphical Display
Parameters for any user can be displayed either in the results table or directly on the map (as presented in the figure below).
Figure 6.56 Individual mobile results display using the tool tip
6.11.5 Simulation Reports
Atoll provides detailed simulation results in the form of reports.
Reports of a Single Simulation
A report is available for each simulation. This report contains information about the simulation statistics, and calculation
results by sites, cell, and mobile as given in the figure below.
Figure 6.57 LTE simulation report – Cells tab
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Figure 6.58 LTE simulation report – Mobiles tab
The simulation results are provided at the following different levels:





Global statistics: total users attempting a connection and the corresponding break-up per service; total users
actually connected and the corresponding break-up per service.
Results per site: sum of user throughputs (peak RLC, effective RLC, and application level throughputs) for all the
cells of a site, globally and per service type, for both uplink and downlink and numbers of rejected mobiles per
rejection cause.
Results per cell: uplink and downlink traffic loads, uplink noise rise, numbers of co-scheduled MU-MIMO users, sum
of user throughputs (peak RLC, effective RLC, and application level throughputs), for both uplink and downlink,
numbers of rejected mobiles per rejection cause.
Results per mobile: geographic location, receiver height, terminal type, service, user profile, mobility, activity status
(DL/UL), serving cells, numbers of aggregated servers in downlink and uplink for carrier aggregation, numbers of
coordinated servers for CoMP, path loss, received power levels, uplink transmit power, uplink allocated bandwidth,
channel and user throughputs (peak RLC, effective RLC, and application throughputs), connection status (connected
in DL, UL, DL+UL, or rejected due to no service, scheduler saturation or resource saturation), C/(I+N) and
interference levels, antenna diversity modes, bearer, BLER, etc.
Initial conditions: parameters and traffic maps used to create the simulation.
Reports of a Group of Simulations
Atoll provides detailed simulation results averaged over a group of simulations in the form of reports. The report generated
for a simulation group contains:
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Statistics: average statistics obtained from the results of all the simulations in a group
Results per site: average site results obtained from the results of all the simulations in a group
Results per cell: average cell results obtained from the results of all the simulations in a group
Initial conditions: parameters used to create the simulation group.
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Figure 6.59 LTE simulation group report
6.11.6 Updating Cell Loads
You can store the cell loads calculated by Monte Carlo simulations in the cells data table. This enables you to update the
network cell loads based either on the average results from a simulation group or the results of from a single simulation. Cell
load values for all the cells in the network radio database are then updated with the results generated by the selected
simulation. Cell loads from a simulation, simulation group, or from the cells data table can then be used to generate coverage
prediction plots.
6.11.7 Exporting Results
You can export the simulation results as described in 2.5.1 Network Data Import and Export.
LTE/LTE-Advanced Coverage Predictions
In Atoll a coverage prediction is a plot displaying calculation results of user-selected parameters on the map and enabling
graphical as well as statistical analysis of the network behaviour. Examples of LTE coverage predictions are signal level, signal
quality, radio bearer, throughput plots, etc. For each pixel, Atoll calculates the required information. This data is then
graphically represented by a colour according to a user-defined legend. Different display options are available in Atoll,
depending on the calculated parameter.
Coverage predictions can be calculated for a given layer or the best layer, depending on the best server selection mechanism,
and for one, more, or all frequency carriers. Coverage predictions that depict radio parameters such as signal levels and signal
quality can be calculated for LTE release 8 cells, LTE-Advanced primary cells, and any of the possible 4 secondary cells.
Throughput coverage predictions can be calculated for one or many aggregated servers (carrier aggregation) in both downlink
and uplink. All coverage predictions also take coordinated multipoint transmission and reception (CoMP) into account.
6.12.1 Coverage Prediction Calculation and Management
Coverage predictions are performed by assuming a “probe mobile” (non-interfering terminal) on each pixel of the considered
area. The probe mobile characteristics (terminal type, mobility type, service type) are specified as inputs to the coverage
prediction in order to calculate the user-defined prediction parameter. Coverage predictions can be calculated for the best
server, the best server for each layer, and all servers, with and without overlapping.
Predictions are stored as multi-layer geographic objects in the Predictions folder of the Explorer window and can be displayed
in the map window. When several coverage predictions are available, it is possible to automatically display one prediction
after the other, hence animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
Subfolders can be created in the Predictions folder in order to group various coverage prediction objects into categories.
Coverage predictions can be directly created under a subfolder and moved from one subfolder to another using the mouse.
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6.12.2 Coverage Prediction Types
LTE coverage predictions can be generated either based on the results from Monte Carlo simulations or on user-defined cell
load configurations.
LTE coverage prediction types and their display options available in Atoll are listed below.
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Coverage by transmitter (DL)
o Transmitter
Coverage by signal level (DL)
o Reference or maximum signal level (dBm, dBµV or dBµV/m)
o RSRP level
o Path loss (dB)
Overlapping zones (DL)
o Number of servers
Downlink coverage
o Coverage by transmitter
o RSRP
o RS signal level
o SS signal level
o PBCH signal level
o PDCCH signal level
o PDSCH signal level
o RS C/N
o SS C/N
o PBCH C/N
o PDCCH C/N
o PDSCH C/N
o Cell-edge margin
o Cell-edge areas
o CoMP sets
o Number of CoMP servers
o Best control channel beams
o Best traffic channel beams
Downlink quality
o RSSI
o RSRQ
o RS C/(I+N)
o SS C/(I+N)
o PBCH C/(I+N)
o PDCCH C/(I+N)
o PDSCH C/(I+N)
o RS total noise (I+N)
o SS total noise (I+N)
o PBCH total noise (I+N)
o PDCCH total noise (I+N)
o PDSCH total noise (I+N)
o BER
o BLER
Downlink service areas
o Bearer
o Modulation
Downlink capacity
o Peak RLC channel throughput
o Effective RLC channel throughput
o Application channel throughput
o Peak RLC cell capacity
o Effective RLC cell capacity
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o Application cell capacity
o Aggregate peak RLC cell throughput
o Aggregate effective RLC cell throughput
o Aggregate application cell throughput
o Peak RLC throughput per user
o Effective RLC throughput per user
o Application throughput per user
o Number of aggregated servers
o Aggregated frequency bands
o Spectral efficiency
Uplink coverage
o PUSCH signal level
o PUCCH signal level
o PUSCH C/N
o PUCCH C/N
o CoMP sets
o Number of CoMP servers
Uplink quality
o PUSCH C/(I+N)
o PUSCH total noise (I+N)
o PUCCH C/(I+N)
o PUCCH total noise (I+N)
o Allocated bandwidth
o Transmission power
o BER
o BLER
Uplink service areas
o Bearer
o Modulation
Uplink capacity
o Peak RLC channel throughput
o Effective RLC channel throughput
o Application channel throughput
o Peak RLC cell capacity
o Effective RLC cell capacity
o Application cell capacity
o Peak RLC allocated bandwidth throughput
o Effective RLC allocated bandwidth throughput
o Application allocated bandwidth throughput
o Aggregate peak RLC cell throughput
o Aggregate effective RLC cell throughput
o Aggregate application cell throughput
o Peak RLC throughput per user
o Effective RLC throughput per user
o Application throughput per user
o Number of aggregated servers
o Aggregated frequency bands
o Spectral efficiency
Cell identifier collision zones (DL): Displays collisions between physical cell IDs, SSS IDs, PSS IDs, cell-specific RS, UL
DMRS sequence groups, and PRACH root sequence indexes
o Interferer
o Number of interferers
o Number of interferers per cell
Coverage predictions depend on the network’s behaviour under load. These predictions can be calculated for a service,
mobility type, and user terminal equipment.
Various LTE coverage prediction plots are shown in the figures below.
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Figure 6.60 LTE coverage by transmitter
Figure 6.61 LTE coverage by RSRP
Figure 6.62 LTE coverage by RS signal level
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Figure 6.63 LTE coverage by SS signal level
Figure 6.64 LTE coverage by PBCH signal level
Figure 6.65 LTE coverage by PDCCH signal level
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Figure 6.66 LTE coverage by PDSCH signal level
Figure 6.67 LTE coverage by cell-edge margin
Figure 6.68 LTE coverage by cell-edge areas
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Figure 6.69 LTE coverage by RSSI
Figure 6.70 LTE coverage by RSRQ
Figure 6.71 LTE coverage by RS C/(I+N)
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Figure 6.72 LTE coverage by SS C/(I+N)
Figure 6.73 LTE coverage by PBCH C/(I+N)
Figure 6.74 LTE coverage by PDCCH C/(I+N)
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Figure 6.75 LTE coverage by PDSCH C/(I+N)
Figure 6.76 LTE coverage by PDSCH BLER
Figure 6.77 LTE coverage by downlink bearers
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Figure 6.78 LTE coverage by downlink modulations
Figure 6.79 LTE coverage by downlink PCell throughput
Figure 6.80 LTE coverage by downlink aggregated throughput
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Figure 6.81 LTE coverage by downlink spectral efficiency
Figure 6.82 LTE coverage by number of aggregated servers
Figure 6.83 LTE coverage by aggregated frequency bands
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Figure 6.84 LTE coverage by CoMP sets
Figure 6.85 LTE coverage by number of CoMP servers
Figure 6.86 LTE coverage by PUSCH signal level
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Figure 6.87 LTE coverage by uplink total losses
Figure 6.88 LTE coverage by uplink allocated bandwidth
Figure 6.89 LTE coverage by uplink transmission power
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Figure 6.90 LTE coverage by PUSCH BLER
Figure 6.91 LTE coverage by uplink PCell throughput
Figure 6.92 LTE coverage by uplink aggregated throughput
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Figure 6.93 LTE coverage by uplink spectral efficiency
6.12.3 Coverage Prediction Reports
Atoll can generate reports for one or more coverage predictions with various detail levels as defined by the user. Reports are
spread sheet-like tables that can be printed directly from Atoll or exported to any desktop tool. An example of such a report
is given in the figure below.
Figure 6.94 LTE coverage prediction report
6.12.4 Coverage Prediction Comparison
Comparison (difference, intersection, union, or merge) between two coverage predictions can be performed. As examples,
this functionality can be used:
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To compare uplink and downlink coverage of a service. This enables you to determine uplink/downlink-limited
zones for that service.
To compare service area coverage plots of two different services. This enables you to assess the areas where one
service (e.g., VoIP) is available while the other (e.g., high speed internet) is not.
To compare service area coverage plots of two networks deployment scenarios (possibly with different
technologies). The figure below illustrates such a case by comparing GSM and LTE coverage. Note that, in this
example, LTE transmitters are installed on only some of the GSM sites.
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Figure 6.95 Coverage prediction graphical comparison (GSM versus LTE example)
Atoll also enables you to carry out per-pixel arithmetical operations between coverage predictions. For example, you can
calculate the sum, difference, min, max, and average of similar calculated parameters per pixel from two coverage predictions
of the same or different technologies.
6.12.5 Coverage Prediction Export
Any coverage prediction can be exported in the following formats:
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Atoll format
ArcView SHP
MapInfo MIF and TAB
ArcView Grid TXT and ASC
Vertical Mapper GRD and GRC
BMP
PNG
TIFF
BIL
JPEG2000
JPEG
When exported in MapInfo format, coverage prediction attributes (e.g., signal levels, transmitter IDs, etc.) are exported along
with the plot. The figure below gives an example of the exported attributes for a C/(I+N) prediction.
Figure 6.96 LTE coverage prediction attributes export to MapInfo
6.12.6 Point Analysis Tool
A real-time prediction analysis tool is available in Atoll. The point analysis tool is dynamically linked to the map window. The
displayed information is updated as the receiver is moved on the map window. The point analysis tool provides the downlink
signal values numerically and graphically for all cells and for the selected layer or all layers, selected channel or all channels,
terminal type, mobility type, and service type.
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Based on user-defined or calculated cell load values, the point analysis tool also provides numeric values of signal levels and
signal quality for the RS, SS, PBCH, PDCCH, PDSCH, and PUSCH, downlink and uplink bearers, and downlink and uplink
throughput values.
The figure below shows the point analysis window as well as its link to the map window.
Receiving
Mobile
Received
Signal
Strength
information
Figure 6.97 LTE point-to-point real-time analysis
6.12.7 Multi-Point Analysis
Atoll enables you to carry out point predictions on multiple point locations and at different heights. Multi-point analyses can
be carried out on imported lists of points, subscriber locations from fixed subscriber traffic maps, as well as points created
on the map using the mouse.
Multi-point analyses may be useful in verifying network QoS at specific locations in case of reported incidents such as call
drops, low throughputs, etc. Multi-point analysis calculations can be based on user-defined network load conditions in the
Cells table or loads calculated using Monte Carlo simulations. The figure below shows the multi-point analysis creation dialog
box.
Figure 6.98 LTE multi-point analysis creation dialog box
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Two types of multi-point analyses are available. Point analysis results include a number of radio parameters at each point
calculated for all potential servers. These results are the same as available for one point in the Details view of the Point
Analysis tool. Fixed subscriber analysis results include more detailed results for the subscriber’s best server. These results are
similar to the results provided by a Monte Carlo simulation.
Multi-point analysis results are stored in the Multi-Point Analysis folder in the Network explorer. Once calculated, multi-point
analysis results are available in tabular form and visible on the map using symbols and colours based on calculation results.
Figure 6.99 LTE multi-point analysis results
You can export the multi-point analysis results as described in 2.5.1 Network Data Import and Export.
LTE/LTE-Advanced Neighbour Planning
Atoll supports the following neighbour types in an LTE network configuration:
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Intra-technology neighbours: LTE cells defined as neighbours of other LTE cells in the same Atoll document.
Inter-technology neighbours: LTE cells defined as neighbours of cells which use a technology other than LTE.
Neighbour plans can be generated by any of the following means in Atoll:
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Importing an external neighbour plan (e.g., in Excel format)
Automatically producing a neighbour plan as described in 6.13.1 Automatic Neighbour Allocation
Graphically and/or manually creating, editing and deleting a neighbour plan as presented in 6.13.2 Graphical
Neighbour Plan Editing
Various neighbour plans can be compared. The results of an automatic neighbour allocation can be compared with the
existing neighbour plan. As well, neighbour plans from external sources can also be compared with the existing neighbour
plan in Atoll.
6.13.1 Automatic Neighbour Allocation
Neighbour lists can be generated automatically in Atoll. For each cell, potential neighbours are ranked according to their
importance. The neighbour planning algorithm considers the following user-specified parameters:
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Hysteresis zone defined by a handover start and a handover end margin with respect to the best server boundary
defined by the RSRP biased by the cell individual offset and the handover margin
Maximum inter-site distance
Maximum number of neighbours
Minimum area covered (overlapping area between the reference cell and its potential neighbour).
Importance ranges for distance, coverage, adjacency, and co-site factors.
Forcing “neighbour symmetry”, “adjacent cells as neighbours”, “co-site cells as neighbours“ and/or “exceptional neighbour
pairs” is possible with Atoll. The figure below displays the automatic neighbour allocation dialog box.
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Figure 6.100 LTE automatic neighbour list generation
6.13.2 Graphical Neighbour Plan Editing
Neighbour plan can be graphically edited in Atoll. Clicking a transmitter on the map displays all its neighbour relations. All
types of neighbour relations (outwards, inwards or symmetrical) can be created, edited and/or deleted graphically. Such an
example is presented in the figures below.
Figure 6.101 Graphical neighbour plan editing
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Figure 6.102 Neighbour planning using a best server plot
6.13.3 Neighbour Consistency Check Tool
A neighbour relation audit is available in Atoll. This function enables you to determine inconsistencies in the current
neighbour plan. The figure below shows the neighbour relation conditions that can be verified using the audit.
Figure 6.103 Neighbour audit
LTE/LTE-Advanced Automatic Frequency, Physical Cell ID, and PRACH RSI Planning
The Atoll LTE AFP (Automatic Frequency Planning module) enables you to automatically configure network parameters such
as the frequency carriers, physical cell IDs, and PRACH root sequence indexes. The AFP can also perform fractional frequency
planning through automatic configuration of the PSS ID during physical cell ID planning. The aim of the AFP is to allocate
resources in a way that minimises interference following the user‐defined constraints. The AFP assigns a cost to each
constraint and then uses an iterative algorithm to evaluate possible allocation plans and propose the allocation plan with the
lowest costs. The AFP cost function comprises input elements such as interference matrices, neighbour relations, and allowed
ranges of resources for allocation.
The figure below presents the LTE AFP window.
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Figure 6.104 LTE AFP
6.14.2 AFP Cost Components
The AFP cost components include relations and constraints. The AFP’s automatic planning algorithm can take the following
relations into account:
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Interference-based relations, i.e., cells that interfere each other
The probability of interference is extracted from interference matrices. One or more interference matrices can be
calculated using Atoll or imported from external files in standard TXT, CSV, and IM2 formats, in order to provide
the AFP with:
o The co-channel interference probability
o The adjacent channel interference probability
Neighbour cells
The importance of each neighbour relation is determined from the neighbour relation definition. The following
neighbour relations can be taken into account:
o First-order neighbours (direct neighbours)
o Second-order neighbours (neighbours of neighbours)
o Inter-neighbours (neighbours of a common cell)
Inter-cell distance
A minimum reuse distance can be defined per cell or globally for all the cells.
The AFP can take into account the following constraints:
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For automatic frequency allocation: Frequency carrier collision and overlap
For physical cell ID allocation: physical cell ID collisions and other related collisions (PSS ID, SSS ID, cell-specific
reference signals, UL DMRS, PCFICH REGs, etc.), physical cell ID allocation domain, effect of the frequency plan on
physical cell ID allocation, etc.
For PRACH root sequence index allocation: PRACH RSI collisions, PRACH RSI allocation domain, effect of the
frequency plan on PRACH allocation, etc.
The impact of each relation and constraint can be fine-tuned by the user by defined the associated weights. The figure below
shows the AFP constraint weights dialog box.
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Figure 6.105 User-defined AFP constraint weights
6.14.3 Automatic Physical Cell ID Planning
Atoll enables you to assign physical cell IDs manually or automatically to any cell in the network. Atoll facilitates the
management of physical cell IDs by letting you create groups of physical cell IDs and domains, where each domain is a defined
set of groups. Atoll can automatically assign physical cell IDs to cells taking into account the network’s frequency plan, the
selected allocation strategy (same SSS ID per site or co-site PCIs with a regular step), allowed allocation domain, interference
matrices, reuse distance, and any constraints imposed by neighbours. It is also possible to allocate the same physical cell ID
to co-located cells using different frequency bands and whose transmitter azimuths are within 10° from each other.
Furthermore, Atoll can take into account inter-technology neighbour relations in a multi-RAT network planning environment.
Atoll takes into account physical cell ID collisions between LTE cells that are neighbours of the same 5G NR, GSM, UMTS, or
CDMA2000 cell.
Figure 6.106 LTE physical cell ID planning
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Once the allocation is complete, you can implement the proposed allocation plan, export the results to TXT, CSV, or XML
spread sheet files, audit the physical cell IDs, analyse physical cell ID reuse and collisions on the map, and make an analysis
of physical cell ID distribution.
Figure 6.107 LTE physical cell ID audit
6.14.4 Automatic PRACH Root Sequence Index Planning
Atoll enables you to assign PRACH root sequence indexes manually or automatically to any cell in the network. Atoll can
automatically assign PRACH root sequence indexes to cells taking into account the network’s frequency plan, allowed
allocation domain, PRACH resource block and subframe collisions between cells, interference matrices, reuse distance, and
any constraints imposed by neighbours.
It is also possible to allocate the same PRACH RSIs to co-site cells that use different resource blocks and/or subframes for
PRACH. Moreover, you can also allocate the same PRACH RSIs to co-located cells using different frequency bands and whose
transmitter azimuths are within 10° from each other.
Once the allocation is complete, you can implement the proposed allocation plan, export the results to TXT, CSV, or XML
spread sheet files, audit the PRACH root sequence indexes, analyse PRACH root sequence index reuse and collisions on the
map, and make an analysis of PRACH root sequence index distribution.
Figure 6.108 LTE PRACH root sequence index planning
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Figure 6.109 LTE PRACH root sequence index audit
6.14.5 Automatic Frequency Planning
Atoll enables you to assign frequency carriers manually or automatically to any cell in the network. Atoll facilitates the
management of frequency bands and carriers by letting you define frequency bands and EUARFCNs as needed. Atoll can
automatically assign frequency carriers to cells taking into account the allowed frequency carriers, interference matrices,
reuse distance, and any constraints imposed by neighbours.
Once the allocation is complete, you can implement the proposed allocation plan, export the results to TXT, CSV, or XML
spread sheet files, audit the frequencies, analyse frequency reuse and interference on the map, and make an analysis of
frequency distribution.
Figure 6.110 LTE frequency planning
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Figure 6.111 LTE frequency audit
6.14.6 Frequency, Physical Cell ID, and PRACH Root Sequence Index Plan Analysis
Cell Parameter Search Tool
A search tool is available in Atoll which enables you to search for frequencies, physical cell IDs, PSS IDs, SSS IDs, and PRACH
RSIs. You can display the current allocation plan of the selected parameter on the map and highlight the transmitters and
their coverage areas respectively. The tool window is shown in the figure below.
Figure 6.112 Physical cell ID search
Cell Parameter Display on Map
You can display the frequency, physical cell ID, and PRACH root sequence index allocation on transmitters by using the
transmitters’ display settings. The figure below shows a physical cell ID plan displayed on the map.
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Figure 6.113 Physical cell ID display on map
Cell Identifier Collision Zones Prediction
You can display the physical cell ID, PSS ID, SSS ID, PCI Mod 6, PCI Mod 30, and PRACH root sequence index collisions on the
map using the cell identifier coverage prediction. The figure below shows a physical cell ID collisions study displayed on the
map.
Figure 6.114 Physical cell ID collisions displayed on map
LTE/LTE-Advanced Automatic Cell Planning
The Atoll LTE ACP (Automatic Cell Planning) module enables you to automatically determine the best LTE parameter settings
for your network. The aim of the Atoll ACP is to improve network quality in terms of both coverage and capacity. For a
comprehensive description of the Atoll ACP, see 17 Automatic Cell Planning (ACP) Features.
The Atoll LTE ACP is capable of optimising network parameters (antenna types, heights, azimuths, tilts, transmission powers,
etc.) based on the following LTE quality indicators:
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Signal level
RS Coverage
RS C/N
RSRP
RS CINR
RSRQ
RSSI
PDSCH CINR
RLC peak rate
Overlap
Best server distance
1st-Nth difference
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PUSCH Coverage
LTE/LTE-Advanced Co-planning With Other Radio Access Technologies
Atoll supports GSM/UMTS/LTE/NB-IoT/5G NR as well as CDMA2000/LTE/NB-IoT/5G NR co-planning. Other radio access
technologies can also be combined with LTE in Atoll. For more information, see 11 Multi-RAT Features.
Additionally, Atoll models the effect of interference from coexisting LTE (or OFDM) networks. This feature enables studying
the effect of interference on the LTE network from other parts of the same LTE network and from the LTE (or OFDM) networks
of other operators. The figure below shows the specific “Transmitter Type” parameter (Server and Interferer or Interferer
Only) required as input.
Figure 6.115 Transmitter properties window
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7 NB-IoT Features
The Atoll NB-IoT technology module enables planning and optimising NB-IoT networks as independent deployments as well
as on top of existing LTE networks. According to the 3GPP, NB-IoT is a new radio standard based on the LTE platform. For
Atoll, NB-IoT is also a new radio access technology within the Atoll LTE architecture. Therefore, Atoll NB-IoT requires both the
Atoll LTE and NB-IoT module licences. However, in the presence of the NB-IoT module licence, Atoll NB-IoT adds IoT-oriented
features to Atoll LTE, the LTE ACP, AFP, and Live.
Figure 7.1
LTE to LTE/NB-IoT upgrade
Atoll NB-IoT supports NB-IoT frequency bands and carriers (200 kHz occupied, 180 kHz used), all deployment configurations
(standalone, guardband, inband, and inband with same PCI/NPCI), various NB-IoT signals and logical channels (NRS, NSSS,
NPSS, NDMRS, NPBCH, NPDCCH, NPDSCH, NPUSCH), the NB-IoT frames, slots, subcarriers, and resource units, single-tone as
well as multi-tone NPUSCH operation (3.75 kHz tone width in addition to 15 kHz), and multi-carrier operation with definition
of anchor and slave cells.
The Atoll NB-IoT offers prediction, planning, and analysis tools for both downlink and uplink NB-IoT coverage and capacity
evaluation. Atoll NB-IoT precisely models interference calculations in downlink and uplink between NB-IoT signals and
channels, as well as with LTE and other radio access technologies.
Atoll includes integrated single RAN–multiple RAT network design capabilities for cellular radio access technologies including
5G NR, LTE, NB-IoT, UMTS, GSM, and CDMA. It features a multi-technology network database, a unified traffic model, and a
combined Monte Carlo simulator. The Atoll LTE ACP can be used to automatically optimise network parameters to increase
coverage and capacity. It can also carry out site selection for greenfield and site activation for densification scenarios.
The Atoll LTE/NB-IoT AFP can automatically allocate frequencies and narrowband physical cell IDs based on user-definable
constraints and cost. It also allows joint PCI/NPCI allocation for inband deployments. Analysis tools enabling auditing of
frequency and narrowband physical cell ID plans are also available.
NB-IoT Network Model
The LTE/NB-IoT network model comprises radio network elements such as sites, transmitters, and cells. An eNode-B is
equivalent to a site, its transmitters with one or more carriers (cells) each.
Figure 7.2
LTE/NB-IoT network model
7.2.2 Sites
A site represents the physical location where eNode-Bs can be installed. An example of a site properties window is shown in
0.
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Figure 7.3
Site properties window
Site parameters are:
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Geographic coordinates
Altitude (user-defined or automatically extracted from the terrain elevation data)
Any user-defined flags and parameters such as address, owner, deployment phase, etc.
The maximum downlink and uplink S1 interface throughputs: The S1 interface connects eNode-Bs to the evolved
packet core (EPC) entities, the mobility management entity (MME) and the serving gateway (S-GW). The capacity
of the S1 interface between the eNode-B and the serving gateway imposes a limit on the aggregate throughput
served by the cells of the same eNode-B. This also imposes a limit on the throughput of each individual user served
by the eNode-B. Here you must enter the capacity of the S1-U interface (S1-U is the user-plane interface between
eNode-Bs and the serving gateways). The maximum S1 interface throughputs that you enter here can be taken into
account in Monte Carlo simulations as backhaul constraints.
7.2.3 Transmitters
Transmitters in Atoll correspond to sectors and antennas installed at a site. The main transmitter parameters are:
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Transmitter name and the name of the site where it is installed
X and Y coordinates
Transmitter type (server and interferer, or interferer only)
Active/inactive (to be included in calculations or not)
Main, secondary, and 3D beamforming antennas
Numbers of transmission and reception antenna ports for MIMO
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other repeaters
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Tower mounted amplifier (TMA)
Feeder type and its transmission and reception lengths
Maximum range
Any user-defined flags and parameters
An example of a transmitter properties window is shown in the figure below.
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Figure 7.4
LTE/NB-IoT transmitter properties window
7.2.4 Cells
Atoll supports multi-band, multi-carrier NB-IoT network deployments. In Atoll, cells model frequency carriers used at a
transmitter. A transmitter can support LTE as well as NB-IoT cells. Each NB-IoT cell has its own radio resources and parameters,
including:
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Cell name and the name of the transmitter to which the cell belongs
Frequency band and carrier
Network layer (macro, small cell, 800 MHz, 2600 MHz, etc.) to which the cell belongs (hence also the associated
priority)
Cell selection and handover parameters (cell individual offset used for cell range expansion, cell selection threshold
known as ThresXHighP, and handover margin)
Cell type: whether the cell is a standard (non-multicarrier) cell, a multicarrier anchor, and/or a multicarrier slave
Narrowband physical cell ID, NPSS ID, NSSS ID
AFP parameters: carriers, NPSS, and NSSS status (allocated, locked, etc.), narrowband physical cell ID domain,
minimum reuse distance, and the NPCI allocation strategy
Transmission powers: maximum power, NRS EPRE, and NSS, NPBCH, NPDCCH, and NPDSCH EPRE offsets
Minimum NRSRP
Radio equipment
Downlink and uplink diversity support
Maximum number of simultaneous users
NPRACH preamble format
Fractional power control and noise rise control parameters: FPC factor, maximum uplink noise rise, maximum
NPUSCH C/(I+N)
Resource allocation constraints: maximum uplink and downlink traffic loads
Cell loads and resource allocation results: uplink and downlink traffic loads, uplink noise rise, numbers of connected
users in downlink and uplink
Inter-technology interference: downlink and uplink noise rise
Deployment configuration: automatically calculated field showing the deployment configuration of the NB-IoT cell
with respect to LTE cells in the network
Any user-defined flags and parameters
The figure below presents an example of a transmitter with a single cell.
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Figure 7.5
Figure 7.6
NB-IoT cell parameters
Supported and automatically determined NB-IoT deployment configurations
7.2.5 Site Templates
A site template is made up of one or more transmitters and cells located on the same site. Site templates can be created and
edited as needed. Building a network is facilitated by working with site templates rather than single site/transmitter/cell. By
default some NB-IoT site templates are available for dense urban, urban, suburban, and rural environments.
7.2.6 Repeaters
A repeater receives, amplifies, and retransmits signals. Repeaters are used to extend the coverage of their donors. Atoll
models selective as well as non-selective RF repeaters, optic fibre repeaters, microwave repeaters, and remote antennas.
Selective RF repeaters only repeat signals from their donor transmitters whereas non-selective RF repeaters receive and
retransmit wanted signals as well as interference.
The main parameters of a repeater are:
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Donor transmitter name
X and Y coordinates
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other repeaters
Total gain
Amplifier gain
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Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Feeder type and its transmission and reception lengths
Any user-defined flags and parameters
The figure below presents the repeater properties window while the figure below that gives an example of a best server
prediction plot with a repeater.
Figure 7.7
Repeater properties window
RF repeater
Donor transmitter
Figure 7.8
RF repeater coverage plot
NB-IoT Network Parameters
Atoll allows setting and modifying network-level configurations and parameters applicable to the entire project.
7.3.1 Frequency Bands and Carriers
Atoll supports multi-band NB-IoT networks. A frequency band is characterized by its reference frequency that is used by Atoll
for path loss calculations. Each carrier within a frequency band is characterised by its duplexing mode, its downlink and uplink
centre frequencies, its downlink and uplink bandwidths, and its absolute radio frequency channel numbers (ARFCN).
You can add, modify, and delete frequency bands and carriers in Atoll as required. A number of EUTRA frequency bands are
available by default. An example of an NB-IoT carrier definition is shown in the figure below.
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Figure 7.9
NB-IoT carrier definition
The figure below shows the EARFCN to PRB mapping tool that can help assess the exact mapping between LTE and NB-IoT
PRBs.
Figure 7.10 EARFCN to PRB mapping tool
7.3.2 Global Network Settings
NB-IoT-specific parameters that are applicable to the entire network are modelled in Atoll as global network settings. These
parameters include the interference calculation method and the uplink power adjustment margin. The figure below presents
the network level properties dialog box.
Figure 7.11 LTE network level parameters
7.3.3 Network Layers
An NB-IoT network can be deployed in multiple layers of heterogeneous cells, i.e., of different sizes (macro, micro, small cells,
etc.), and possibly using different frequencies. Atoll enables you to define network layers with different priorities and
supported user speed limits. During cell selection, network layer parameters are taken into account to determine the serving
cells.
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The figure below gives an example of network layers that can be defined and deployed in Atoll.
Figure 7.12 NB-IoT network layers table
7.3.4 UE categories
UE categories define combined uplink and downlink capabilities of user equipment. The parameters set by the UE categories
include physical and transport channel parameters in downlink and uplink, and the layer 2 buffer size.
Figure 7.13 Default LTE UE categories (extract)
7.3.5 Radio Equipment
NB-IoT radio equipment model the transmission and reception characteristics of cells and user terminals. Bearers, bearer
selection thresholds, repetition gains, quality indicator graphs, and diversity gains are defined in NB-IoT radio equipment.
NB-IoT radio bearers are used to carry user data on the PDSCH and the PUSCH. A bearer refers to a combination modulation
and coding scheme. The radio bearers table lists the available radio bearers in downlink and uplink. You can add, remove,
and modify bearer properties according to your network and equipment.
Figure 7.14 NB-IoT radio equipment bearers
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Figure 7.15 NB-IoT bearer selection thresholds
Figure 7.16 NB-IoT repetition gains
Figure 7.17 NB-IoT quality indicator graphs
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Diversity gains can be defined for each equipment for different numbers of transmission and reception antennas, modulation
and coding schemes, and user speeds.
Figure 7.18 NPDSCH and NPUSCH diversity gains
Figure 7.19 NPBCH and NPDCCH diversity gains
Also, interference reduction factors can be defined for each ratio equipment considering the receiver characteristics of the
equipment with respect to various carrier widths.
Figure 7.20 Interference reduction factors (adjacent channel selectivity)
NB-IoT Multicarrier Operation
Atoll supports different modes of multicarrier operation:
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Intra-eNode-B aggregation: Only cells that belong to the same site can perform aggregation with each other.
Multi-eNode-B aggregation: Cells belonging to any site can perform aggregation with each other.
Group-based aggregation: Cells belonging to the same group can perform aggregation with each other.
Group-based aggregation mode models a C-RAN-based centralised architecture for multicarrier NB-IoT. Cells belonging to
the same group are managed by the same BBU pool. Cells of the same group can correspond to the same or different
eNBs/RRUs including macro, micro, and small cells.
Atoll enables you to create multicarrier cell groups by grouping cells in the Network explorer as well as, geographically,
grouping cells on the map using polygons. It is also possible to import such cell groups from external spread sheets. Atoll
allows you to view cell groups on the map using coverage predictions as well as using the Find on Map tool.
Figure 7.21 C-RAN architecture with a virtual BBU pool managing multiple RRUs
NB-IoT Traffic Model
Service and user behaviours are modelled in Atoll through different tables that provide information about:
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The services available in the network
The terminals compatible with the network
The mobility types
The user profiles describing the way users access different services
The NB-IoT traffic model is shown in the figure below.
Figure 7.22 NB-IoT traffic model
7.5.2 Services
The services table describes the services that are available in the network. IoT services are supported and have specific
parameters. The main service parameters are:
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Service type
Uplink and downlink activity factors
Supported network layers (macro, small cell, 800 MHz, 2600 MHz, etc.)
QoS class identifier (QCI) and its related priority
Intra-QCI priority level
Lowest and highest supported modulations
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Uplink and downlink average numbers of messages per day
Uplink and downlink minimum and maximum payloads per message
Payload distribution: Low, average, or high
Number of supported tones in uplink
Variable and fixed overheads
Losses
An example of a service properties window is presented in the figure below.
Figure 7.23 Service properties window
7.5.3 Terminals
The terminals table describes the devices that can be used in the network. The following parameters model a terminal:
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Minimum and maximum transmission powers
Default noise figure
Transmission and reception loss
Radio equipment
UE category
Supported network layers (macro, small cell, 800 MHz, 2600 MHz, etc.)
Supported frequency bands and noise figures
Multicarrier support and the maximum numbers of supported slave cells in downlink and uplink
Antenna pattern
Antenna gain
Diversity support
Numbers of antenna ports
An example of a terminal properties window is given in the figure below.
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Figure 7.24 Terminal properties window
7.5.4 Mobility Types
The mobility type defines different user speeds.
7.5.5 User Profiles
The user profiles table models the behaviour of the different user categories. Every user profile contains a list of services and
their associated parameters describing how these services are accessed by the users.
Parameters for voice services are:
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The average number of calls per hour
The average duration of each call
The terminal used when requiring access to this service.
Parameters for data services are:
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The average number of sessions per hour
The data volume transferred on the downlink during each session
The data volume transferred on the uplink during each session
The terminal used when requiring access to this service.
The figure below shows a user profile window.
Figure 7.25 User profile window
7.5.6 Traffic Data
For information on traffic data cartography, see 2.2.7 Traffic Data.
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NB-IoT Monte Carlo Simulations
The NB-IoT Monte Carlo simulations calculate, for each user distribution (called a random trial), the different network
parameters such as the activity, received power levels, C/(I+N) levels, best radio bearer available for the calculated C/(I+N),
and the cell throughputs (peak RLC, effective RLC, and application-level).
A Monte Carlo simulation in Atoll corresponds to a given distribution of users. It is a snapshot of an NB-IoT network. NB-IoT
Monte Carlo simulations can be analysed, displayed and stored.
7.6.1 Generation of Realistic User Distributions
Realistic distributions of users on the map are required as inputs to the NB-IoT simulation algorithm. A “Realistic User
Distribution” corresponds to a user distribution that complies with the service and user model and the traffic data. Atoll
generates these user distributions using a Monte Carlo (statistical) algorithm.
7.6.2 Monte Carlo Simulation Management
NB-IoT simulations are managed through the Simulations folder in the Atoll Explorer window. The Simulations folder is made
up of several simulation “groups”. Each group corresponds to a network configuration for which a user-specified number of
Monte Carlo simulations have been generated. As an example, different groups may correspond to different traffic
assumptions. The figure below shows the simulation creation dialog box.
When several simulation groups are available, it is possible to automatically display one group after the other, hence
animating the user distribution display on the map, at a user-defined speed using the slideshow function.
The following information is required when creating a new group of Monte Carlo simulations:
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The simulation group name
The number of simulations to be run
The load and S1 interface backhaul constraints to apply during simulations
The traffic maps used
The convergence criteria.
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Figure 7.26 Simulation creation dialog box
Once a simulation (or a group of simulations) has been performed, simulation reports are available and simulation results can
be graphically analysed in Atoll.
7.6.3 Simulation Graphical Analysis
Graphical Display: Mobile Activity Status
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for their activity status. The different possible statuses are:
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Active DL + UL: the mobile is active on both downlink and uplink
Active UL: the mobile is active on uplink only
Active DL: the mobile is active on downlink only
An example of a graphical display of a group of simulations is presented in the figure below.
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Figure 7.27 Simulation display by activity status
Graphical Display: Mobile Connection Status
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for their connection status. The different possible statuses are:
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Connected DL + UL: the mobile is connected on both downlink and uplink
Connected UL: the mobile is connected on uplink only
Connected DL: the mobile is connected on downlink only
Scheduler Saturation: the mobile is rejected because the scheduler has reached its maximum limit
Resource Saturation: the mobile is rejected because all the resources have been allocated to other mobiles
No Service: the mobile is rejected because it is outside the coverage area.
An example of a graphical display of a group of simulations is presented in the figure below.
Figure 7.28 Simulation display by connection status
Individual Mobile Results Graphical Display
Parameters for any user can be displayed either in the results table or directly on the map using the tool tip.
7.6.4 Simulation Reports
Atoll provides detailed simulation results in the form of reports.
Reports of a Single Simulation
A report is available for each simulation. This report contains information about the simulation statistics, and calculation
results by sites, cell, and mobile as given in the figure below.
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Figure 7.29 Simulation report – Cells tab
The simulation results are provided at the following different levels:
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Global statistics: total users attempting a connection and the corresponding break-up per service; total users
actually connected and the corresponding break-up per service.
Results per site: numbers of rejected users per rejection cause.
Results per cell: uplink and downlink traffic loads, uplink noise rise, numbers of rejected users per rejection cause.
Results per mobile: geographic location, receiver height, terminal type, service, user profile, mobility, activity status
(DL/UL), serving cells, numbers of servers in downlink and uplink for multicarrier operation, path loss, received
power levels, uplink transmit power, uplink allocated tones, channel throughputs (peak RLC, effective RLC, and
application throughputs), connection status (connected in DL, UL, DL+UL, or rejected due to no service, scheduler
saturation or resource saturation), C/(I+N) and interference levels, antenna diversity modes, bearer, BLER, etc.
Initial conditions: parameters and traffic maps used to create the simulation.
Reports of a Group of Simulations
Atoll provides detailed simulation results averaged over a group of simulations in the form of reports. The report generated
for a simulation group contains:
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Statistics: average statistics obtained from the results of all the simulations in a group
Results per site: average site results obtained from the results of all the simulations in a group
Results per cell: average cell results obtained from the results of all the simulations in a group
Initial conditions: parameters used to create the simulation group.
Figure 7.30 Simulation group report
7.6.5 Exporting Results
You can export the simulation results as described in 2.5.1 Network Data Import and Export.
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NB-IoT Coverage Predictions
In Atoll a coverage prediction is a plot displaying calculation results of user-selected parameters on the map and enabling
graphical as well as statistical analysis of the network behaviour. Examples of NB-IoT coverage predictions are signal level,
signal quality, radio bearer, throughput plots, etc. For each pixel, Atoll calculates the required information. This data is then
graphically represented by a colour according to a user-defined legend. Different display options are available in Atoll,
depending on the calculated parameter.
Coverage predictions can be calculated for a given layer or the best layer, depending on the best server selection mechanism,
and for one, more, or all frequency carriers. Coverage predictions that depict radio parameters such as signal levels and signal
quality can be calculated for standard as well as for multicarrier anchor and slave cells. Throughput coverage predictions can
be calculated for one or many servers (multicarrier operation) in both downlink and uplink.
7.7.1 Coverage Prediction Calculation and Management
Coverage predictions are performed by assuming a “probe mobile” (non-interfering terminal) on each pixel of the considered
area. The probe mobile characteristics (terminal type, mobility type, service type) are specified as inputs to the coverage
prediction in order to calculate the user-defined prediction parameter. Coverage predictions can be calculated for the best
server, the best server for each layer, and all servers, with and without overlapping.
Predictions are stored as multi-layer geographic objects in the Predictions folder of the Explorer window and can be displayed
in the map window. When several coverage predictions are available, it is possible to automatically display one prediction
after the other, hence animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
Subfolders can be created in the Predictions folder in order to group various coverage prediction objects into categories.
Coverage predictions can be directly created under a subfolder and moved from one subfolder to another using the mouse.
7.7.2 Coverage Prediction Types
NB-IoT coverage predictions can be generated either based on the results from Monte Carlo simulations or on user-defined
cell load configurations.
NB-IoT coverage prediction types and their display options available in Atoll are listed below.
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Coverage by transmitter (DL)
o Transmitter
Coverage by signal level (DL)
o Reference or maximum signal level (dBm, dBµV or dBµV/m)
o NRSRP level
o Path loss (dB)
Overlapping zones (DL)
o Number of servers
Downlink coverage
o Coverage by transmitter
o NRSRP
o NRS signal level
o NSS signal level
o NPBCH signal level
o NPDCCH signal level
o NPDSCH signal level
o NRS C/N
o NSS C/N
o NPBCH C/N
o NPDCCH C/N
o NPDSCH C/N
Downlink quality
o NRSSI
o NRSRQ
o NRS C/(I+N)
o NSS C/(I+N)
o NPBCH C/(I+N)
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o NPDCCH C/(I+N)
o NPDSCH C/(I+N)
o NRS total noise (I+N)
o NSS total noise (I+N)
o NPBCH total noise (I+N)
o NPDCCH total noise (I+N)
o NPDSCH total noise (I+N)
o BER
o BLER
Downlink service areas
o Bearer
o Modulation
o Number of repetitions
o Repetition gain
Downlink capacity
o Peak RLC channel throughput
o Effective RLC channel throughput
o Application channel throughput
o Peak RLC cell capacity
o Effective RLC cell capacity
o Application cell capacity
o Number of aggregated servers
o Aggregated frequency bands
o Spectral efficiency
Uplink coverage
o NPUSCH signal level
o NPUCCH signal level
o NPUSCH C/N
o NPUCCH C/N
Uplink quality
o NPUSCH C/(I+N)
o NPUSCH total noise (I+N)
o NPUCCH C/(I+N)
o NPUCCH total noise (I+N)
o Allocated bandwidth
o Transmission power
o BER
o BLER
Uplink service areas
o Bearer
o Modulation
o Number of repetitions
o Repetition gain
Uplink capacity
o Peak RLC channel throughput
o Effective RLC channel throughput
o Application channel throughput
o Peak RLC cell capacity
o Effective RLC cell capacity
o Application cell capacity
o Peak RLC allocated bandwidth throughput
o Effective RLC allocated bandwidth throughput
o Application allocated bandwidth throughput
o Number of aggregated servers
o Aggregated frequency bands
o Spectral efficiency
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Cell identifier collision zones (DL): Displays collisions between narrowband physical cell IDs, NSSS IDs, NPSS IDs, and
NRS
o Interferer
o Number of interferers
o Number of interferers per cell
Coverage predictions depend on the network’s behaviour under load. These predictions can be calculated for a service,
mobility type, and user terminal equipment.
Various NB-IoT coverage prediction plots are shown in the figures below.
Figure 7.31 NB-IoT coverage by transmitter
Figure 7.32 NB-IoT coverage by NRSRP
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Figure 7.33 NB-IoT coverage by NRS signal level
Figure 7.34 NB-IoT coverage by NSS signal level
Figure 7.35 NB-IoT coverage by NPBCH signal level
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Figure 7.36 NB-IoT coverage by NPDCCH signal level
Figure 7.37 NB-IoT coverage by NPDSCH signal level
Figure 7.38 NB-IoT coverage by NRSSI
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Figure 7.39 NB-IoT coverage by NRSRQ
Figure 7.40 NB-IoT coverage by NRS C/(I+N)
Figure 7.41 NB-IoT coverage by NSS C/(I+N)
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Figure 7.42 NB-IoT coverage by NPBCH C/(I+N)
Figure 7.43 NB-IoT coverage by NPDCCH C/(I+N)
Figure 7.44 NB-IoT coverage by NPDSCH C/(I+N)
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Figure 7.45 NB-IoT coverage by NPDSCH BLER
Figure 7.46 NB-IoT coverage by downlink bearer
Figure 7.47 NB-IoT coverage by number of downlink repetitions
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Figure 7.48 NB-IoT coverage by downlink repetition gains
Figure 7.49 NB-IoT coverage by NPUSCH signal level
Figure 7.50 NB-IoT coverage by uplink total losses
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Figure 7.51 NB-IoT coverage by NPUSCH C/(I+N)
Figure 7.52 NB-IoT coverage by uplink transmission power
Figure 7.53 NB-IoT coverage by number of uplink repetitions
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Figure 7.54 NB-IoT coverage by downlink repetition gains
7.7.3 Coverage Prediction Reports
Atoll can generate reports for one or more coverage predictions with various detail levels as defined by the user. Reports are
spread sheet-like tables that can be printed directly from Atoll or exported to any desktop tool. An example of such a report
is given in the figure below.
Figure 7.55 NB-IoT coverage prediction report
7.7.4 Coverage Prediction Comparison
Comparison (difference, intersection, union, or merge) between two coverage predictions can be performed. As examples,
this functionality can be used:
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To compare uplink and downlink coverage of a service. This enables you to determine uplink/downlink-limited
zones for that service.
To compare service area coverage plots of two different services. This enables you to assess the areas where one
service (e.g., VoIP) is available while the other (e.g., high speed internet) is not.
To compare service area coverage plots of two networks deployment scenarios (possibly with different
technologies). The figure below illustrates such a case by comparing GSM and LTE coverage. Note that, in this
example, LTE transmitters are installed on only some of the GSM sites.
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Figure 7.56 Coverage prediction graphical comparison (GSM versus LTE example)
Atoll also enables you to carry out per-pixel arithmetical operations between coverage predictions. For example, you can
calculate the sum, difference, min, max, and average of similar calculated parameters per pixel from two coverage predictions
of the same or different technologies.
7.7.5 Coverage Prediction Export
Any coverage prediction can be exported in the following formats:
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Atoll format
ArcView SHP
MapInfo MIF and TAB
ArcView Grid TXT and ASC
Vertical Mapper GRD and GRC
BMP
PNG
TIFF
BIL
JPEG2000
JPEG
When exported in MapInfo format, coverage prediction attributes (e.g., signal levels, transmitter IDs, etc.) are exported along
with the plot. The figure below gives an example of the exported attributes for a C/(I+N) prediction.
Figure 7.57 Coverage prediction attributes export to MapInfo
7.7.6 Point Analysis Tool
A real-time prediction analysis tool is available in Atoll. The point analysis tool is dynamically linked to the map window. The
displayed information is updated as the receiver is moved on the map window. The point analysis tool provides the downlink
signal values numerically and graphically for all cells and for the selected layer or all layers, selected channel or all channels,
terminal type, mobility type, and service type.
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Based on user-defined or calculated cell load values, the point analysis tool also provides numeric values of signal levels and
signal quality for the NRS, NSS, NPBCH, NPDCCH, NPDSCH, and NPUSCH, downlink and uplink bearers, and downlink and
uplink throughput values. The figure below shows the point analysis window as well as its link to the map window.
Receiving
Mobile
Received
Signal
Strength
information
Figure 7.58 Point-to-point real-time analysis
7.7.7 Multi-Point Analysis
Atoll enables you to carry out point predictions on multiple point locations and at different heights. Multi-point analyses can
be carried out on imported lists of points, subscriber locations from fixed subscriber traffic maps, as well as points created
on the map using the mouse.
Multi-point analyses may be useful in verifying network QoS at specific locations in case of reported incidents such as call
drops, low throughputs, etc. Multi-point analysis calculations can be based on user-defined network load conditions in the
Cells table or loads calculated using Monte Carlo simulations. The figure below shows the multi-point analysis creation dialog
box.
Figure 7.59 Multi-point analysis creation dialog box
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Two types of multi-point analyses are available. Point analysis results include a number of radio parameters at each point
calculated for all potential servers. These results are the same as available for one point in the Details view of the Point
Analysis tool. Fixed subscriber analysis results include more detailed results for the subscriber’s best server. These results are
similar to the results provided by a Monte Carlo simulation.
Multi-point analysis results are stored in the Multi-Point Analysis folder in the Network explorer. Once calculated, multi-point
analysis results are available in tabular form and visible on the map using symbols and colours based on calculation results.
Figure 7.60 Multi-point analysis results
You can export the multi-point analysis results as described in 2.5.1 Network Data Import and Export.
NB-IoT Automatic Frequency and Narrowband Physical Cell ID Planning
The Atoll LTE/NB-IoT AFP (Automatic Frequency Planning module) enables you to automatically configure network
parameters such as the frequency carriers and narrowband physical cell IDs. The aim of the AFP is to allocate resources in a
way that minimises interference following the user‐defined constraints. The AFP assigns a cost to each constraint and then
uses an iterative algorithm to evaluate possible allocation plans and propose the allocation plan with the lowest costs. The
AFP cost function comprises input elements such as interference matrices and allowed ranges of resources for allocation.
The figure below presents the LTE/NB-IoT AFP window.
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Figure 7.61 LTE/NB-IoT AFP
7.8.2 AFP Cost Components
The AFP cost components include relations and constraints. The AFP’s automatic planning algorithm can take the following
relations into account:
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Interference-based relations, i.e., cells that interfere each other
The probability of interference is extracted from interference matrices. One or more interference matrices can be
calculated using Atoll or imported from external files in standard TXT, CSV, and IM2 formats, in order to provide
the AFP with:
o The co-channel interference probability
o The adjacent channel interference probability
Inter-cell distance
A minimum reuse distance can be defined per cell or globally for all the cells.
The AFP can take into account the following constraints:
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For automatic frequency allocation: Frequency carrier collision and overlap
For narrowband physical cell ID allocation: narrowband physical cell ID collisions and other related collisions (NPSS
ID, NSSS ID, NRS, etc.), narrowband physical cell ID allocation domain, effect of the frequency plan on narrowband
physical cell ID allocation, etc.
The impact of each relation and constraint can be fine-tuned by the user by defined the associated weights. The figure below
shows the AFP constraint weights dialog box.
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Figure 7.62 User-defined AFP constraint weights
7.8.3 Automatic Narrowband Physical Cell ID Planning
Atoll enables you to assign physical cell IDs manually or automatically to any cell in the network. Atoll facilitates the
management of physical cell IDs by letting you create groups of physical cell IDs and domains, where each domain is a defined
set of groups. Atoll can automatically assign physical cell IDs to cells taking into account the network’s frequency plan, the
selected SSS ID allocation strategy (free or same per site), allowed allocation domain, interference matrices, reuse distance,
and any constraints imposed by neighbours.
Furthermore, Atoll can take into account inter-technology neighbour relations in a multi-RAT network planning environment.
Atoll takes into account physical cell ID collisions between LTE cells that are neighbours of the same GSM, UMTS, or
CDMA2000 cell.
Figure 7.63 LTE/NB-IoT physical cell ID planning
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Once the allocation is complete, you can implement the proposed allocation plan, export the results to TXT, CSV, or XML
spread sheet files, audit the physical cell IDs, analyse physical cell ID reuse and collisions on the map, and make an analysis
of physical cell ID distribution.
Figure 7.64 LTE/NB-IoT physical cell ID audit
7.8.4 Automatic Frequency Planning
Atoll enables you to assign frequency carriers manually or automatically to any cell in the network. Atoll facilitates the
management of frequency bands and carriers by letting you define frequency bands and EARFCNs as needed. Atoll can
automatically assign frequency carriers to cells taking into account the allowed frequency carriers, interference matrices, and
reuse distance.
Once the allocation is complete, you can implement the proposed allocation plan, export the results to TXT, CSV, or XML
spread sheet files, audit the frequencies, analyse frequency reuse and interference on the map, and make an analysis of
frequency distribution.
Figure 7.65 NB-IoT frequency planning
7.8.5 Frequency and Narrowband Physical Cell ID Plan Analysis
Cell Parameter Search Tool
A search tool is available in Atoll which enables you to search for frequencies, narrowband physical cell IDs, NPSS IDs, and
NSSS IDs. You can display the current allocation plan of the selected parameter on the map and highlight the transmitters
and their coverage areas respectively. The tool window is shown in the figure below.
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Figure 7.66 Narrowband physical cell ID search
Cell Parameter Display on Map
You can display the frequency and narrowband physical cell ID allocation on transmitters by using the transmitters’ display
settings. The figure below shows a narrowband physical cell ID plan displayed on the map.
Figure 7.67 Narrowband physical cell ID display on map
Cell Identifier Collision Zones Prediction
You can display the narrowband physical cell ID, NPSS ID, NSSS ID, etc., collisions on the map using the cell identifier coverage
prediction. The figure below shows a narrowband physical cell ID collisions study displayed on the map.
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Figure 7.68 Narrowband physical cell ID collisions displayed on map
NB-IoT Automatic Cell Planning
The Atoll LTE/NB-IoT ACP (Automatic Cell Planning) module enables you to automatically determine the best NB-IoT
parameter settings for your network. The aim of the Atoll ACP is to improve network quality in terms of both coverage and
capacity. For a comprehensive description of the Atoll ACP, see 17 Automatic Cell Planning (ACP) Features.
The Atoll LTE/NB-IoT ACP is capable of optimising network parameters (antenna types, heights, azimuths, tilts, transmission
powers, etc.) based on the following NB-IoT quality indicators:
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NRS C
NRSRP
NRS CINR
NRSRQ
NPUSCH C
1st-Nth difference
NB-IoT Co-planning With Other Radio Access Technologies
Atoll supports GSM/UMTS/LTE/NB-IoT as well as CDMA2000/LTE/NB-IoT co-planning. Other radio access technologies can
also be combined with LTE in Atoll. For more information, see 11 Multi-RAT Features.
Additionally, Atoll precisely models the effect of interference between NB-IoT and LTE as well as PDSCH and PUSCH blanking
for inband NB-IoT. This enables studying the effect of interference on the NB-IoT network from the underlying LTE network
and from the LTE networks of other operators.
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8 UMTS/HSPA Features
The Atoll UMTS module provides a comprehensive and accurate modelling of multi-cell and multi-band UMTS/HSPA
networks. It supports all UMTS/HSPA frequency bands (e.g., UMTS 900/1800/1900/2100). It also includes detailed modelling
of Release 99, HSDPA, and HSUPA bearers and services including VoIP, MIMO for HSPA+, multi-cell and dual-band HSPA, and
MBMS (Multimedia Broadcast and Multicast Services).
Atoll provides the means to set up multi-service traffic maps from multiple sources: vector, raster and live traffic data. Traffic
maps are used in UMTS/HSPA Monte Carlo simulations for network capacity analysis including DL and UL power control, RRM,
HSPA to R99 downgrading and carrier allocation. Coverage predictions can be calculated based on Monte Carlo simulation
results or on live network loads from the OAM in order to study coverage and capacity of the network.
In terms of HSPA and HSPA+ Atoll takes into account transport and physical channels, fast link adaptation, higher order
modulation schemes, different modes of power allocation, H-ARQ retransmission mechanisms, and MIMO. HSPA/HSPA+ can
be analysed as separate layers or combined with R99 traffic, thus allowing to estimate the impact of HSPA/HSPA+ users on
R99 users and vice versa. Atoll supports single-band dual-cell, single-band multi-cell, dual-band dual-cell, and dual-band multicell HSDPA (i.e., DC-HSDPA, MC-HSDPA, DB-DC-HSDPA, DB-MC-HSDPA), as well as dual-cell HSUPA (DC-HSUPA).
Atoll includes automatic multi-carrier neighbour planning features that allow analysing handovers in the network. Automatic
scrambling code planning can be performed using various allocation strategies, with analysis tools enabling auditing of
scrambling code allocations.
Atoll includes integrated single RAN–multiple RAT network design capabilities for cellular radio access technologies including
5G NR, LTE, NB-IoT, UMTS, GSM, and CDMA. It features a multi-technology network database, a unified traffic model, and a
combined Monte Carlo simulator. The Atoll LTE ACP can be used to automatically optimise network parameters to increase
coverage and capacity. It can also carry out site selection for greenfield and site activation for densification scenarios.
An overview of the UMTS modelling in Atoll is shown in the figure below.
Figure 8.1
UMTS network modelling in Atoll
UMTS Network Model
The UMTS network model comprises radio network elements such as sites, transmitters, and cells. A UMTS Node-B is
equivalent to a site, its transmitters with one or more radio channels (cells) each.
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Figure 8.2
UMTS network model
8.1.1 Sites
A site represents the physical location where Node-Bs can be installed. An example of a site properties window is shown in
the figure below.
Figure 8.3
Site properties window
Site parameters are:
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Geographic coordinates
Altitude (user-defined or automatically extracted from the terrain elevation data)
Any user-defined flags and parameters such as address, owner, deployment phase, etc.
8.1.2 Transmitters
Transmitters in Atoll correspond to sectors and antennas installed at a site. The main transmitter parameters are:
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Transmitter name and the name of the site where it is installed
X and Y coordinates
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Numbers of transmission and reception antenna ports for diversity
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other transmitters
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Tower mounted amplifier (TMA)
Feeder type and its transmission and reception lengths
Maximum coverage range
Any user-defined flags and parameters
An example of a transmitter properties window is shown in the figure below.
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Figure 8.4
UMTS transmitter properties window
8.1.3 Cells (R99, HSDPA, HSPA, and HSPA+)
Atoll supports multi-band, multi-carrier UMTS networks. In Atoll, cells model the carriers used at a transmitter. A transmitter
can support different carriers. Each cell has its own radio resources and parameters, including:
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Cell name and the name of the transmitter to which the cell belongs
Carrier number
Network layer (macro, small cell, 800 MHz, 2600 MHz, etc.) to which the cell belongs (hence also the associated
priority)
Cell selection and handover parameters (cell individual offset used for cell range expansion and handover margin)
Primary scrambling code, SC locked/unlocked, SC domain, and SC reuse distance
Transmission powers: pilot, SCH, other CCH, total
Inter-carrier power sharing
AS threshold
Minimum RSCP
Resource allocation constraints: maximum downlink load and uplink load factor
HSPA support: None, HSDPA, HSPA, HSPA+
Multi-cell HSDPA support
For multi-cell HSPA, site-level (node-B-level) scheduling methods are defined in site equipment. For more
information, see 8.3.1 Site Equipment.
MIMO support: None, transmit diversity, spatial multiplexing
HSDPA parameters: HSDPA and HS‐SCCH power allocation modes, available HSDPA and HS‐SCCH powers, power
headroom, number of HS‐SCCH channels, minimum and maximum numbers of HS‐PDSCH codes, maximum and
actual numbers of HSDPA users, HSDPA scheduler algorithm, MUG gains
HSUPA parameters: Downlink HSUPA power, maximum and actual numbers of HSUPA users, uplink load factor due
to HSUPA,
Cell loads and resource allocation results: uplink load factor and downlink load
These parameters can be outputs of Monte Carlo simulations as well as user-defined values.
Inter-technology interference: downlink and uplink noise rise
Neighbour parameters: maximum numbers of neighbours and neighbours lists
Any user-defined flags and parameters
The figure below presents an example of a transmitter with one cell.
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Figure 8.5
UMTS cell parameters
8.1.4 Site Templates
A site template is made up of one or more transmitters and cells located on the same site. Site templates can be created and
edited as needed. Building a network is facilitated by working with site templates rather than single site/transmitter/cell. By
default some UMTS site templates are available for dense urban, urban, suburban, and rural environments.
8.1.5 Repeaters
A repeater receives, amplifies, and retransmits signals. Repeaters are used to extend the coverage of their donors. Atoll
models selective as well as non-selective RF repeaters, optic fibre repeaters, microwave repeaters, and remote antennas.
Selective RF repeaters only repeat signals from their donor transmitters whereas non-selective RF repeaters receive and
retransmit wanted signals as well as interference.
The main parameters of a repeater are:
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Donor transmitter name
X and Y coordinates
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other repeaters
Total gain
Amplifier gain
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Feeder type and its transmission and reception lengths
Any user-defined flags and parameters
The figure below presents the repeater properties window while the figure below that gives an example of a best server
prediction plot with a repeater.
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Figure 8.6
Repeater properties window
RF repeater
Donor transmitter
Figure 8.7
RF repeater coverage plot
UMTS Network Configuration Parameters
Atoll allows setting and modifying network-level configurations and parameters applicable to the entire project.
8.2.1 Frequency Bands and Carriers
Atoll enables you to model multi-band, multi-carrier UMTS networks. A frequency band is characterized by its operating
frequency and carriers (UARFCN). You can add, modify, and delete frequency bands in Atoll as required. The default UTRA
frequency bands available in Atoll are shown in the figure below.
Figure 8.8
UMTS frequency bands table
Atoll can also calculate inter-carrier interference based on inter-carrier interference IRFs.
8.2.2 Global Network Settings
UMTS- and HSPA-specific parameters that are applicable to the entire network are modelled in Atoll as global network
settings. These parameters include the downlink power calculation method, the definition of the downlink load, the
interference calculation method, the soft handover calculation method, parameters related to compressed mode, and HSDPA
interference and CQI calculation methods. The figure below presents the network level properties dialog box.
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Figure 8.9
UMTS network level parameters
8.2.3 Network Layers
A UMTS network can be deployed in multiple layers of heterogeneous cells, i.e., of different sizes (macro, micro, small cells,
etc.), and possibly using different carriers. Such UMTS networks are referred to as HetNets, or heterogeneous networks. Atoll
enables you to define network layers with different priorities and supported user speed limits. During cell selection, network
layer parameters are taken into account to determine the serving cells.
The figure below gives an example of UMTS heterogeneous network layers that can be defined and deployed in Atoll.
Figure 8.10 UMTS network layers table
8.2.4 Radio Bearers (R99, HSDPA, and HSUPA)
Radio bearers define the data transport format. Atoll manages R99, HSDPA, and HSUPA bearers. The R99 radio bearer
parameters are:
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Type
Nominal uplink and downlink rates
Uplink and downlink spreading factors
Uplink and downlink DPCCH/DPCH power ratios
Minimum and maximum downlink traffic channel powers
An example of an R99 bearer properties window is presented in the figure below.
Figure 8.11 R99 radio bearer properties
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The HSDPA radio bearer parameters are:
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Transport block size
Number of used HS-PDSCH channels
RLC peat rate
Highest supported modulation
The HSUPA radio bearer parameters are:
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TTI duration
Transport block size
Number of used E-DPDCH channels
Minimum spreading factor
RLC peat rate
Highest supported modulation
8.2.5 Schedulers
In Atoll, schedulers perform the allocation and management of radio resources for HSDPA mobiles. HSDPA mobiles can be
single-cell HSDPA mobiles or DC-HSDPA, MC-HSDPA, DB-DC-HSDPA, DB-MC-HSDPA mobiles. Various scheduling methods are
available in Atoll, including proportional fair, round robin, maximum C/I, etc., as well as the support for multi-user diversity
gains specific to proportional fair schedulers.
8.2.6 UE categories (HSDPA and HSUPA)
UE categories define the HSDPA and HSUPA capabilities of user equipment. The HSDPA UE category parameters include:
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Maximum number of HS-PDSCH channels
Minimum number of TTIs between two used TTIs
Maximum transport block size
Highest supported modulation
MIMO support
Multi-cell support: 2-cell (dual-cell), 3-cell, 4-cell, 6-cell, 8-cell
The HSUPA UE category parameters are:
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TTI duration
Maximum transport block sizes for 2ms and 10ms TTIs
Maximum number of E-DPDCH codes
Minimum spreading factor
Highest supported modulation
8.2.7 Quality Indicators (R99, HSDPA, HSUPA)
In Atoll, quality indicators (BER, DCH BLER, HSDPA BLER, HSUPA BLER, etc.) represent the coverage quality at different
locations. The quality indicators table lists the available quality indicators which you can add, remove, and modify as required.
Figure 8.12 UMTS quality indicators table
UMTS Radio Equipment
Atoll provides the option to define various pieces of radio equipment such as antennas, transmitter equipment, feeders,
tower mounted amplifiers, reception equipment, etc. For more information on common antenna and radio equipment
features, see 4 Antenna and Radio Equipment Features.
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8.3.1 Site Equipment
Site equipment model the Node-B level parameters that are applicable to all the transmitters and cells located at a site. The
following parameters define the equipment for each site:
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Manufacturer name
Multi-user detection factor
Rake factor (used in the uplink rake receiver modelling)
Carrier selection method
Four options are available when assigning a carrier to a requesting user: the least loaded carrier in downlink, the
least loaded carrier in uplink, a random carrier, or sequential allocation of carriers to users.
Overhead channel elements used in both uplink and downlink
Option to restrict the active set to the neighbours only
Compressed mode option (generally used to prepare hard-handover of users with single receiver terminals)
Overhead Iub throughput per cell
Iub backhaul overhead due to HSDPA
Size of the backhaul link (E1, T1, Ethernet)
Dual-band HSDPA support
Multi-cell HSDPA scheduler
Figure 8.13 UMTS site equipment definition
For each site equipment type, the channel element consumption can be defined per radio bearer. The figure below gives the
example of such a definition table.
Figure 8.14 Channel element consumption definition per radio bearer
8.3.2 Reception Equipment (R99, HSDPA, HSPA, HSPA+)
UMTS reception equipment model the reception characteristics of user terminals. R99, HSDPA, and HSUPA bearer selection
thresholds, quality indicator graphs, and MIMO gains are defined in UMTS reception equipment. The figures below give
examples of such an equipment definition.
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Figure 8.15 UMTS reception equipment – R99 bearer selection thresholds
Figure 8.16 UMTS reception equipment – R99 quality indicator graphs
Figure 8.17 UMTS reception equipment – HSDPA bearer selection thresholds
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Figure 8.18 UMTS reception equipment – HSDPA quality indicator graphs
Figure 8.19 UMTS reception equipment – HSUPA bearer selection thresholds
Figure 8.20 UMTS reception equipment – HSUPA quality indicator graphs
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Figure 8.21 UMTS reception equipment – MIMO gain graphs
UMTS Traffic Model
In Atoll, the radio network traffic is modelled using Monte Carlo simulations. According to the definition of the services and
users in the network, and depending on the traffic cartography (traffic data), realistic distributions of users are generated and
used as input to the power control and radio resource management algorithms.
Service and user behaviours are modelled in Atoll through different tables that provide information about:
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The services available in the network
The terminals compatible with the network
The mobility types
The user profiles describing the way users access different services
The UMTS traffic model is shown in the figure below.
Figure 8.22 UMTS traffic model
8.4.1 Services
The services table describes the services that are available in the network. Various types of services (circuit, packet, etc.) are
supported and have specific parameters. The main service parameters are:
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R99 radio bearer
Type (circuit R99, packet R99, HSDPA best effort, HSDPA variable bit rate, HSPA best effort, HSPA variable bit rate,
HSPA constant bit rate)
Preferred carrier
Priority level
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Atoll 3.4.0 Technical Overview
Bearer downgrading
Soft handover support
Supported network layers (macro, small cell, 800 MHz, 2600 MHz, etc.)
HSPA support
Uplink and downlink activity factors (for circuit services)
Uplink and downlink efficiency factors (for packet services, the percentage of data volume increase due to
retransmissions)
Uplink and downlink minimum, maximum, and average requested rates
Packet session parameters (packet sizes, packet call durations, etc.)
Body loss
An example of the service properties window is presented in the figure below.
Figure 8.23 Service properties window
8.4.2 Terminals
The terminals table describes the terminals that can be used in the network, cell phones, smartphones, in-car navigation
devices, etc. The following parameters model a terminal:
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Minimum and maximum transmission powers
Transmission and reception losses
Antenna gain
Reception equipment
Active set size
Downlink rake factor
Rho factor
Default noise figure
Supported network layers (macro, small cell, 800 MHz, 2600 MHz, etc.)
Supported frequency bands and respective losses and noise figures
Compressed mode
HSPA support: None, HSDPA, HSPA, DB-HSDPA, DB-HSPA
HSPA parameters
o UE categories
o MUD factor
o Number of reception antenna ports
An example of a terminal properties window is given in the figure below.
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Figure 8.24 Terminal properties window
8.4.3 Mobility Types
The mobility type defines the minimum required pilot Ec/Io and HS-SCCH Ec/Nt for different user speeds.
An example of a mobility type properties window is given in the figure below.
Figure 8.25 Mobility type properties window
8.4.4 User Profiles
The user profiles table models the behaviour of the different user categories. Every user profile contains a list of services and
their associated parameters describing how these services are accessed by the users.
Parameters for circuit-switched services are:
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The average number of calls per hour
The average duration of each call
The terminal used when requiring access to this service
Parameters for packet-switched services are:
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The average number of sessions per hour
The data volume transferred on the downlink during each session
The data volume transferred on the uplink during each session
The terminal used when requiring access to this service
The figure below shows a user profile window.
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Figure 8.26 User profile window
8.4.5 Traffic Data
For information on traffic data cartography, see 2.2.7 Traffic Data.
UMTS Monte Carlo Simulations
UMTS networks automatically regulate transmission powers and interference using power control in both downlink and
uplink. HSPA networks perform fast link adaptation for HSDPA users and noise rise scheduling for HSUPA users. The overall
objective is to minimise interference and maximise network capacity. Atoll simulates UMTS/HSPA network regulation
mechanisms by calculating, for each user distribution (called a random trial), different network parameters such as active set
for each mobile, required power, soft handover gains, HSPA throughputs, etc. As outputs, Atoll provides the following
parameters characterizing the stabilized network:
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The total downlink cell power
The cell throughput
The uplink cell load
The HSDPA power (if allocated dynamically)
The number of HSDPA and HSUPA users
The uplink cell load due to HSUPA
The uplink reuse factor
A Monte Carlo simulation in Atoll corresponds to a given distribution of users. It is a snapshot of a UMTS network.
UMTS Monte Carlo simulations can be analysed, displayed and stored. They can be used in a next step to generate numerous
coverage predictions.
8.5.1 Generation of Realistic User Distributions
Realistic distributions of users on the map are required as inputs to the UMTS simulation algorithm. A “Realistic User
Distribution” corresponds to a user distribution that complies with the service and user model and the traffic data. Atoll
generates these user distributions using a Monte Carlo (statistical) algorithm.
8.5.2 Power Control and Radio Resource Management
For each user distribution, Atoll simulates the power control and RRM mechanism of UMTS cells. The simulation uses an
iterative algorithm that models power control on both downlink and uplink for R99 bearers, link adaptation for HSDPA users,
and noise rise scheduling for HSUPA users. This iterative process ends when the network is balanced, i.e., when the
convergence criteria are satisfied.
The figure below shows an overview of the simulation algorithm.
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Figure 8.27 UMTS simulation overview
The R99 part of the UMTS Monte Carlo simulations applies to all the generated mobiles regardless of their service and
terminal HSPA capabilities. This phase of calculations includes the following steps:
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Initialisation: The network is initialised as “empty”. There is no mobile connected to any transmitter when starting
a simulation. The following steps are repeated for each mobile (R99, HSDPA, and HSUPA) of the generated user
distribution.
Best server determination: The best server is determined for each mobile based on the Ec/Io. A mobile is rejected
if the Ec/Io condition is not satisfied or the uplink load factor is higher than the specified limit.
Active set determination: The active set is determined for each mobile.
Uplink power control: The mobile transmit power is calculated. It corresponds to the power required to satisfy the
uplink Eb/Nt requirement. The mobile is rejected if the calculated required transmit power is higher than the
maximum mobile transmit power.
Downlink power control: The transmitter traffic channel power is calculated. It corresponds to the power required
to satisfy the downlink Eb/Nt requirement. “No handover” and “handover” situations are handled in different ways.
The mobile is rejected if the calculated traffic channel power is higher than the maximum traffic channel power
allowed.
Uplink and downlink interference update: The uplink load factor and total downlink transmit power are updated
with these results.
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Congestion and radio resource control (R99 bearers): R99 and HSDPA go through bearer downgrading. R99 to R99
bearer downgrading is triggered for different reasons: when cell resources are not sufficient at the admission or
during the congestion control and when the user maximum connection power is exceeded during the power
control. The HSDPA to R99 bearer downgrading occurs at the admission when the best serving cell does not support
HSDPA. HSDPA users are allocated R99 bearers instead. Mobiles are rejected if any of the following situations occur:
o Uplink load factor higher than the specified limit
o Total downlink transmit power higher than the maximum allowed
o Number of OVSF codes insufficient
o Number of available channel elements insufficient
The HSDPA part of the UMTS Monte Carlo simulations applies to HSDPA mobiles. HSDPA mobiles can be single-cell HSDPA
mobiles or DC-HSDPA, MC-HSDPA, DB-DC-HSDPA, DB-MC-HSDPA mobiles. This phase of calculations includes the following
steps:
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Fast link adaptation: Circuit quality indicators (CQI) are calculated for each user. Based on the CQI, mobile and cell
capability Atoll selects the appropriate HSDPA Bearer.
Scheduling: The scheduler shares cell radio resources according to the policy of the scheduler (max C/I, round robin
or proportional fair).
Radio resource control: Mobiles are rejected if any of the following situations occur:
o HSDPA user saturation
o Lower HSDPA bearer cannot be obtained
o Insufficient number of OVSF codes
o Bad quality of HS-SCCH
The HSUPA part of the UMTS Monte Carlo simulations applies to HSUPA mobiles. This phase of calculations includes the
following steps:
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Admission control: During admission control, Atoll selects a list of HSUPA bearers that are compatible with the user
equipment capabilities for each HSUPA user taking into account the max power of the terminals.
Noise rise scheduling: The noise rise scheduling algorithm attempts to evenly share the cell load between the users
admitted in admission control; in terms of HSUPA, each user is allocated a right to produce interference.
Radio recourse control: Mobiles are rejected if any of the following situations occur:
o HSUPA user saturation
o The required terminal power exceeds the maximum allowed power
The above calculations are carried out during each successive iteration until the simulation converges, i.e., both uplink and
downlink convergence criteria are satisfied.
Main simulation outputs are:
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Cell loads
HSDPA and HSUPA throughputs
Note that numerous other parameters are available and stored during the simulation for further analysis. For more
information, see 8.5.5 Simulation Reports.
8.5.3 Monte Carlo Simulation Management
UMTS simulations are managed through the Simulations folder in the Atoll Explorer window. This folder is displayed in the
figure below.
Figure 8.28 UMTS simulations folder
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The Simulations folder is made up of several simulation “groups”. Each group corresponds to a network configuration for
which a user-specified number of Monte Carlo simulations have been generated. As an example, different groups may
correspond to different traffic assumptions.
When several simulation groups are available, it is possible to automatically display one group after the other, hence
animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
The figure below shows the simulation creation dialog box. The following information is required when creating a new group
of Monte Carlo simulations:
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The simulation group name
The number of simulations to be run
The load constraints to apply during simulations
The traffic maps used
The convergence criteria.
Figure 8.29 UMTS simulation creation dialog box
Once a simulation (or a group of simulations) has been performed, simulation reports are available and simulation results can
be graphically analysed in Atoll.
8.5.4 Simulation Graphical Analysis
Graphical Display: Mobile Connection Status
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for their connection status. The different possible statuses are:
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Connect DL + UL: the mobile is connected on both downlink and uplink
Connect UL: the mobile is connected on uplink only
Connect DL: the mobile is connected on downlink only
Inactive: the mobile is inactive
Pmob > PmobMax: the mobile is rejected during uplink power control as its required uplink transmitter power is
higher than the maximum mobile transmit power
Ptch > PtchMax: the mobile is rejected during downlink power control as the required downlink traffic channel
power is higher than the maximum downlink traffic channel power
Ec/Io < (Ec/Io)min: the mobile is rejected during best server determination as the Best Server Ec/Io is less than the
minimum required
Admission Rejection: the mobile is rejected during best server determination as the uplink cell load would be higher
than the maximum allowed
UL Load Saturation: the mobile is rejected during congestion and radio resource control as the uplink cell load would
be higher than the maximum allowed
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Channel Elements Saturation: the mobile is rejected during congestion and radio resource control as there are not
enough channel elements available
DL Load Saturation: the mobile is rejected during congestion and radio resource control as the downlink total power
is higher than the maximum allowed
OVSF Code Saturation: the mobile is rejected during the “Congestion and Radio Resource Control Step” as there
are not enough OVSF codes available
HSDPA Delayed, HSDPA Delayed (No Compatible Bearer), HSDPA Delayed (HS-SCCH Channel Saturation), HSDPA
Delayed (HSDPA Power Saturation), HSDPA Delayed (OVSF Code Saturation), HSDPA Delayed (Iub Throughput
Saturation): the mobile cannot obtain lower HSDPA bearer or HS-SCCH signal quality is not sufficient
HSDPA Scheduler Saturation: the maximum HSDPA users per cell or max number of HS-SCCH channel are exceeded
HSDPA Resource Saturation
HSUPA Scheduler Saturation: the maximum number of HSUPA users per cell is exceeded
HSUPA Admission Rejection: the terminal power required to obtain the lowest compatible HSUPA bearer exceeds
the maximum terminal power in the admission control
Iub Throughputs Saturation
An example of a graphical display of a group of simulations is presented in the figure below.
Figure 8.30 UMTS simulation graphical display
Individual Mobile Result Graphical Display
Parameters for any user can be displayed either in the results table or directly on the map (as presented in the figure below).
Figure 8.31 Individual mobile results display using the tool tip
8.5.5 Simulation Reports
Atoll provides detailed simulation results in the form of reports.
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Reports of a Single Simulation
A report is available for each simulation. This report contains information about the simulation statistics, and calculation
results by sites, cell, and mobile as given in the figure below.
Figure 8.32 UMTS simulation report
The simulation results are provided at the following different levels:
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Global statistics: total users attempting a connection and the corresponding break-up per service; total users
actually connected and the corresponding break-up per service.
Results per site: channel elements consumed (total, due to soft handover and due to overhead channels) and the
throughput allocated per service type. All these parameters are given for both uplink and downlink.
Results per cell: downlink transmit power related information (total power, load factor, percentage of power used,
average traffic channel power), uplink mobile power related information (total noise, load factor, noise rise, reuse
factor), number of radio links for uplink and downlink, number of OVSF codes used, percentage of areas in handover
(distinction made between soft, softer and other handover types), throughput allocated to downlink and uplink,
number of mobile rejections split per rejection reason.
Results per mobile: geographic location, terminal type, user type, mobility, connection status, carrier, requested
and allocated throughputs for uplink and downlink, best server, active set information.
Initial conditions: parameters and traffic maps used to create the simulation.
An option is available to display more detailed results. This extra information includes for each mobile:
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The detailed parameters values for each member of the active set (noise values, interference values, etc.),
The shadowing loss values for each path from a mobile to its first 10 potential servers.
Reports of a Group of Simulations
Atoll provides detailed simulation results averaged over a group of simulations in the form of reports. The report generated
for a simulation group contains:
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Statistics: average statistics obtained from the results of all the simulations in a group
Results per site: average site results obtained from the results of all the simulations in a group
Results per cell: average cell results obtained from the results of all the simulations in a group
Initial conditions: parameters used to create the simulation group.
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Figure 8.33 UMTS simulation group report
8.5.6 Updating Cell Loads
You can store the cell loads calculated by Monte Carlo simulations in the cells data table. This enables you to update the
network cell loads based either on the average results from a simulation group or the results of from a single simulation. Cell
load values for all the cells in the network radio database are then updated with the results generated by the selected
simulation. Cell loads from a simulation, simulation group, or from the cells data table can then be used to generate coverage
prediction plots.
8.5.7 Exporting Results
You can export the simulation results as described in 2.5.1 Network Data Import and Export.
UMTS Coverage Predictions
In Atoll a coverage prediction is a plot displaying calculation results of user-selected parameters on the map and enabling
graphical as well as statistical analysis of the network behaviour. Examples of UMTS coverage predictions are Ec/Io plots,
handover plots, etc. For each pixel, Atoll calculates the required information. This data is then graphically represented by a
colour according to a user-defined legend. Different display options are available in Atoll, depending on the calculated
parameter.
8.6.1 Coverage Prediction Calculation and Management
Coverage predictions are performed by assuming a “probe mobile” (non-interfering terminal) on each pixel of the considered
area. The probe mobile characteristics (terminal type, mobility type, service type) are specified as inputs to the coverage
prediction in order to calculate the user-defined prediction parameter.
Predictions are stored as multi-layer geographic objects in the Predictions folder of the Explorer window and can be displayed
in the map window. When several coverage predictions are available, it is possible to automatically display one prediction
after the other, hence animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
Subfolders can be created in the Predictions folder in order to group various coverage prediction objects into categories.
Coverage predictions can be directly created under a subfolder and moved from one subfolder to another using the mouse.
8.6.2 Coverage Prediction Types
UMTS coverage predictions can be generated either based on the results from Monte Carlo simulations or on user-defined
cell load configurations.
UMTS coverage prediction types and their display options available in Atoll are listed below.
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Coverage by transmitter (DL)
o Transmitter
Coverage by signal level (DL)
o Pilot and maximum signal level (dBm, dBµV or dBµV/m)
o Path loss (dB)
Overlapping zones (DL)
o Number of servers
Total noise level analysis (DL)
o Minimum, average, and maximum noise level
o Minimum, average, and maximum noise rise
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Pilot quality analysis (DL)
o Ec/Io
o Ec/Io margin
o Ec
o Quality indicator
o Reliability level
Service area analysis (Eb/Nt) (DL)
o Eb/Nt margin
o Effective Eb/Nt
o Maximum Eb/Nt
o Required power
o Required power margin
o Quality indicator
o Reliability level
Service area analysis (Eb/Nt) (UL)
o Eb/Nt margin
o Effective Eb/Nt
o Maximum Eb/Nt
o Required power
o Required power margin
o Soft handover gain
o Quality indicator
o Reliability level
Effective service area analysis (Eb/Nt) (DL+UL)
o Reliability Level
Handover zones (DL)
o Number of potential active transmitters
Pilot pollution analysis (DL)
o Number of polluters
Scrambling code collision zones (DL)
o Number of interferers
o Number of interferers per transmitter
Inter-technology interference level analysis (DL)
o Noise level
o Noise rise
HSDPA quality and throughput analysis (DL)
o Maximum DL A-DPCH Eb/Nt
o Maximum UL A-DPCH Eb/Nt
o HS-SCCH power
o Required HS-SCCH power
o HS-PDSCH Ec/Nt
o CQI
o Peak and effective MAC throughputs
o Effective MAC throughput per user
o Peak, effective, and average effective RLC throughputs
o Effective RLC throughput per user
o Application throughput
o Application throughput per user
o HSDPA BLER
HSUPA quality and throughput analysis (UL)
o Required E-DPDCH Ec/Nt
o Required terminal power
o Peak MAC throughput
o Peak, minimum, and average effective RLC throughputs
o Application throughput
o Average application throughput
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The first three coverage predictions (coverage by transmitter, coverage by signal level, and overlapping zones) are not based
on interference, hence neither require cell load information nor Monte Carlo simulations. The remaining coverage predictions
depend on the network’s behaviour under load. These predictions can be calculated for a service, mobility type, and user
terminal equipment. HSDPA and HSUPA coverage predictions enable analysing HSPA service availability and quality in the
network.
Various UMTS/HSPA coverage prediction plots are shown in the figures below.
Figure 8.34 UMTS coverage by transmitter
Figure 8.35 UMTS pilot Ec/Io coverage
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Figure 8.36 UMTS handover zones
Figure 8.37 UMTS downlink total noise
Figure 8.38 UMTS downlink Eb/Nt
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Figure 8.39 UMTS pilot pollution
Figure 8.40 HSDPA peak rate
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Figure 8.41 HSDPA CQI coverage prediction
Figure 8.42 HSUPA RLC peak rate
8.6.3 Coverage Prediction Reports
Atoll can generate reports for one or more coverage predictions with various detail levels as defined by the user. Reports are
spread sheet-like tables that can be printed directly from Atoll or exported to any desktop tool. An example of such a report
is given in the figure below.
Figure 8.43 UMTS coverage prediction report
8.6.4 Coverage Prediction Comparison
Comparison (difference, intersection, union, or merge) between two coverage predictions can be performed. As examples,
this functionality can be used:
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To compare uplink and downlink coverage of a service. This enables you to determine uplink/downlink-limited
zones for that service.
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To compare service area coverage plots of two different services. This enables you to assess the areas where one
service (e.g., Mobile Internet Access) is available while the other (e.g., Video Conferencing) is not.
To compare service area coverage plots of two networks deployment scenarios (possibly with different
technologies). The figure below illustrates such a case by comparing GSM and UMTS coverage. Note that, in this
example, UMTS transmitters are installed on only some of the GSM sites.
Figure 8.44 Coverage prediction graphical comparison (GSM versus UMTS example)
Atoll also enables you to carry out per-pixel arithmetical operations between coverage predictions. For example, you can
calculate the sum, difference, min, max, and average of similar calculated parameters per pixel from two coverage predictions
of the same or different technologies.
8.6.5 Coverage Prediction Export
Any coverage prediction can be exported in the following formats:
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Atoll format
ArcView SHP
MapInfo MIF and TAB
ArcView Grid TXT and ASC
Vertical Mapper GRD and GRC
BMP
PNG
TIFF
BIL
JPEG2000
JPEG
When exported in MapInfo format, coverage prediction attributes (e.g., signal levels, transmitter IDs, etc.) are exported along
with the plot. The figure below gives an example of the exported attributes for a HS-PDSCH Ec/Nt prediction.
Figure 8.45 UMTS coverage prediction attributes export to MapInfo
8.6.6 Point Analysis Tool
A real-time prediction analysis tool is available in Atoll. The point analysis tool is dynamically linked to the map window. The
displayed information is updated as the receiver is moved on the map window. The point analysis tool provides the downlink
signal values numerically and graphically for all cells and for the selected terminal type, mobility type, and service type.
The figure below shows the point analysis window as well as its link to the map window.
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Real-time active set
display
Active set analysis
window
Pilot Ec/Io
Figure 8.46 UMTS point-to-point real-time analysis
8.6.7 Multi-Point Analysis
Atoll enables you to carry out point predictions on multiple point locations and at different heights. Multi-point analyses can
be carried out on imported lists of points, subscriber locations from fixed subscriber traffic maps, as well as points created
on the map using the mouse.
Multi-point analyses may be useful in verifying network QoS at specific locations in case of reported incidents such as call
drops, low throughputs, etc. Multi-point analysis calculations can be based on user-defined network load conditions in the
Cells table or loads calculated using Monte Carlo simulations. The figure below shows the multi-point analysis creation dialog
box.
Figure 8.47 UMTS multi-point analysis creation dialog box
Multi-point analysis results include a number of radio parameters at each point calculated for all potential servers. The results
provided by this analysis are the same as available for one point in the Details view of the Point Analysis tool. Multi-point
analysis results are stored in the Multi-Point Analysis folder in the Network explorer. Once calculated, multi-point analysis
results are available in tabular form and visible on the map using symbols and colours based on calculation results.
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Figure 8.48 UMTS multi-point analysis results
You can export the multi-point analysis results as described in 2.5.1 Network Data Import and Export.
UMTS Neighbour Planning
Atoll supports the following neighbour types in a UMTS network configuration:
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Intra-technology neighbours: UMTS cells defined as neighbours of other UMTS cells in the same Atoll document.
Intra-technology neighbours can be divided into:
o Intra-carrier neighbours: UMTS cells defined as neighbours to which a call is handed over using the same
carrier.
o Inter-carrier neighbours: UMTS cells defined as neighbours to which a call is handed over using a different
carrier.
Inter-technology neighbours: UMTS cells defined as neighbours of cells which use a technology other than UMTS.
Neighbour plans can be generated by any of the following means in Atoll:
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Importing an external neighbour plan (e.g., in Excel format)
Automatically producing a neighbour plan as described in 8.7.1 Automatic Neighbour Allocation
Graphically and/or manually creating, editing and deleting a neighbour plan as presented in 8.7.2 Graphical
Neighbour Plan Editing
Various neighbour plans can be compared. The results of an automatic neighbour allocation can be compared with the
existing neighbour plan. As well, neighbour plans from external sources can also be compared with the existing neighbour
plan in Atoll.
8.7.1 Automatic Neighbour Allocation
Neighbour lists can be generated automatically in Atoll. For each cell, potential neighbours are ranked according to their
importance. The neighbour planning algorithm considers the following user-specified parameters:
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Minimum received pilot signal strength
Minimum pilot Ec/Io
Pilot Ec/Io margin with respect to the best server boundary defined by the Ec/Io biased by the cell individual offset
and the handover margin
Maximum inter-site distance
Maximum number of neighbours
Minimum area covered (overlapping area between the studied cell and its potential neighbour)
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Importance ranges for distance, coverage, adjacency, and co-site factors
Forcing “neighbour symmetry”, “adjacent cells as neighbour”, “co-site cells as neighbours“ and/or “exceptional neighbour
pairs” is possible with Atoll. Inter-carrier neighbour allocation can be carried out for user-defined source and destination
carrier numbers. The figure below displays the automatic neighbour allocation dialog box.
Figure 8.49 UMTS automatic neighbour list generation
8.7.2 Graphical Neighbour Plan Editing
Neighbour plan can be graphically edited in Atoll. Clicking a transmitter on the map displays all its neighbour relations. All
types of neighbour relations (outwards, inwards or symmetrical) can be created, edited and/or deleted graphically. Such an
example is presented in the figures below.
Figure 8.50 Graphical neighbour plan editing
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Figure 8.51 Neighbour planning using a best server plot
8.7.3 Neighbour Consistency Check Tool
A neighbour relation audit is available in Atoll. This function enables you to determine inconsistencies in the current
neighbour plan. The figure below shows the neighbour relation conditions that can be verified using the audit.
Figure 8.52 Neighbour audit
UMTS Primary Scrambling Code Planning
Primary scrambling code plans can be generated by any of the following means in Atoll:
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Importing an external scrambling code plan (e.g., in Excel format),
Manually creating, editing and/or deleting a scrambling code plan,
Automatically producing a scrambling code plan as described in 8.8.1 Automatic Scrambling Code Planning Tool.
Once created, scrambling code plan consistency can be verified in Atoll.
8.8.1 Automatic Scrambling Code Planning Tool
Atoll’s automatic scrambling code planning tool is based on a cost-based algorithm. The cost function takes into account
several criteria. The following constraints are applied when running the automatic planning algorithm:
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Domain constraint: required to distinguish different zones
Groups: it is possible to define scrambling code groups
Exceptional pairs: it is possible to define cell pairs that cannot have the same scrambling code
Reuse distance: a minimum reuse distance is defined (globally or per cell)
Additional constraints such as minimum Ec/Io
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Four code allocation strategies are available:
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Clustered: Scrambling codes are chosen among a minimum number of clusters, Atoll preferentially allocates all the
codes from same cluster.
Distributed per cell: Scrambling codes are chosen among as many clusters as possible. Atoll preferentially allocates
codes from different clusters.
One cluster per site: Allocates one cluster to each site, then one code of the cluster to each cell of each site.
Distributed per site: Allocates a group of adjacent clusters to each site, then one cluster to each transmitter of the
site according to its azimuth and finally one code of the cluster to each cell of each transmitter.
Atoll facilitates the management of primary scrambling codes by letting you create groups of primary scrambling codes and
domains, where each domain is a defined set of groups. Primary scrambling code domains can then be assigned to cells in
order to provide a list of possible primary scrambling codes for each cell.
Furthermore, Atoll can take into account inter-technology neighbour relations in a multi-RAT network planning environment.
Atoll takes into account primary scrambling code collisions between UMTS cells that are neighbours of the same GSM or LTE
cell.
The figures below presents the automatic scrambling code allocation tool and an example of a scrambling code allocation.
Figure 8.53 Automatic scrambling code planning
Figure 8.54 Scrambling code display on map
8.8.2 Scrambling Code Consistency Check Tool
A scrambling code consistency check tool is available in Atoll. This function enables you to detect any inconsistency due to
potential manual code changes. The figure below shows the conditions that can be verified using the audit.
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Figure 8.55 Scrambling code audit
Atoll can also display distribution histograms of scrambling codes and clusters.
8.8.3 Scrambling Code Interference Analysis
The point analysis tool enables analysing primary scrambling code interference. You can study the received pilot Ec/Io and
find interfering cells using this tool.
Figure 8.56 Scrambling code interference analysis
UMTS Automatic Cell Planning
The Atoll UMTS ACP (Automatic Cell Planning) module enables you to automatically determine the best UMTS parameter
settings for your network. The aim of the Atoll ACP is to improve network quality in terms of both coverage and capacity. For
a comprehensive description of the Atoll ACP, see 17 Automatic Cell Planning (ACP) Features.
The Atoll UMTS ACP is capable of optimising network parameters (antenna types, heights, azimuths, tilts, transmission
powers, etc.) based on the following UMTS quality indicators:
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RSCP
Ec/Io
RSSI
Overlap
Best server distance
1st-Nth difference
UMTS Co-planning With Other Radio Access Technologies
Atoll supports integrated GSM/UMTS/LTE/NB-IoT co-planning. Other radio access technologies can also be combined with
UMTS in Atoll. For more information, see 11 Multi-RAT Features.
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9 GSM/GPRS/EDGE Features
The Atoll GSM module provides a comprehensive and accurate modelling of GSM voice and GPRS/EDGE/EDGE-Evolution data
services. It includes full support for dual-band HCS (Hierarchical Cell Structure) deployment scenarios, baseband and
synthesised frequency hopping, DTX (discontinuous transmission), etc. Detailed network coverage, interference, QoS,
capacity, and handover analyses can be carried out in Atoll.
The Atoll GSM/GPRS/EDGE service model supports all FR, HR, and AMR codecs, GPRS/EDGE MCS families, multiple voice and
data services, and multi-band user equipment. Atoll provides the means to set up multi-service traffic maps from multiple
sources: vector, raster and live traffic data.
The GSM traffic analysis and dimensioning features are capable of spreading traffic between HCS layers with traffic overflow
modelling in order to carry out cell dimensioning for mixed voice/data traffic based on user-definable timeslot configurations.
Network KPIs, such as packet delay, blocking rate, etc., are also calculated.
Atoll can work with multiple interference matrices from various sources: prediction-based (calculated within Atoll), based on
OAM statistics, and based on drive test measurements. The Atoll GSM AFP is able to intelligently combine interference
matrices from different sources in order to improve the overall input quality for frequency planning. The AFP can
automatically allocate frequencies and frequency hopping parameters (HSN, MAIO, and MAL) based on user-definable
constraints and costs. Atoll also provides interactive frequency planning for fine tuning the AFP results.
Atoll includes integrated single RAN–multiple RAT network design capabilities for cellular radio access technologies including
5G NR, LTE, NB-IoT, UMTS, GSM, and CDMA. It features a multi-technology network database, a unified traffic model, and a
combined Monte Carlo simulator. The Atoll LTE ACP can be used to automatically optimise network parameters to increase
coverage and capacity. It can also carry out site selection for greenfield and site activation for densification scenarios.
An overview of the GSM/GPRS/EDGE modelling in Atoll is shown in the figure below.
Figure 9.1
GSM/GPRS/EDGE network modelling in Atoll
GSM/GPRS/EDGE Network Model
The GSM network model comprises radio network elements such as sites, transmitters, and subcells. A GSM base station is
equivalent to a site, its transmitters with one or more TRXs each.
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Figure 9.2
GSM network model
9.1.1 Sites
A site represents the physical location where base stations can be installed. An example of a site properties window is shown
in the figure below.
Figure 9.3
Site properties window
Site parameters are:
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Geographic coordinates
Altitude (user-defined or automatically extracted from the terrain elevation data)
Any user-defined flags and parameters such as address, owner, deployment phase, etc.
9.1.2 Transmitters
Transmitters in Atoll correspond to sectors and antennas installed at a site. The main transmitter parameters are:
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Transmitter name and the name of the site where it is installed
X and Y coordinates
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other transmitters
HCS layer
Frequency band
BCCH and BSIC
Frequency hopping mode
Supported TRX types
Maximum, required, and actual number of TRXs
Transmission power and EIRP
Coverage range
Transmission and reception losses
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Noise figure
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Tower mounted amplifier (TMA)
Feeder type and its transmission and reception lengths
Supported voice codecs
Supported GRPS/EGPRS/EGPRS2 coding schemes
Circuit/packet timeslot configurations
EDGE power backoff
Neighbour parameters: maximum numbers of neighbours and neighbours lists
Any user-defined flags and parameters
An example of a transmitter properties window is shown in the figure below.
Figure 9.4
GSM transmitter properties window
9.1.3 Subcells and TRXs (Transceivers)
Atoll supports multi-band GSM networks. A subcell is a group of TRXs sharing the same radio characteristics. A subcell is
defined by a transmitter-TRX pair. The figure below gives an example of multiple subcells per transmitter: the first subcell
contains one BCCH TRX while the other subcells contain TCH TRXs.
Figure 9.5
Subcells table
A subcell is characterized by the following parameters in Atoll:
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TRX type
Frequency domain
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Downlink traffic load
Downlink power reduction
Reception threshold
C/I threshold
Power control gain
Timeslot configuration
o Number of shared (circuit-switched and packet-switched) time slots
o Number of circuit-switched time slots
o Number of packet-switched time slots
DTX support
Half rate traffic ratio
Diversity mode
AFP parameters: frequency hopping mode, allocation strategy, max MAL length, weight, HSN, HSN domain,
locked/unlocked, HSN synchronisation, preferred frequency group, excluded channels, required TRXs
Accepted interference percentage
TRX configuration
The following three TRX types are available in Atoll:
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BCCH TRXs carry the Broadcast Control Channel (BCCH). At least one time slot must be assigned to the BCCH.
TCH TRXs carry traffic by default. All time slots can be used for traffic.
TCH_INNER TRXs can be used in concentric cells to carry traffic. All time slots can be used for traffic.
TRXs can be created and modified as needed.
9.1.4 Site Templates
A site template is made up of one or more transmitters and cells located on the same site. Site templates can be created and
edited as needed. Building a network is facilitated by working with site templates rather than single site/transmitter. By
default some GSM site templates are available for dense urban, urban, suburban, and rural environments.
9.1.5 Repeaters
A repeater receives, amplifies, and retransmits signals. Repeaters are used to extend the coverage of their donors. Atoll
models selective as well as non-selective RF repeaters, optic fibre repeaters, microwave repeaters, and remote antennas.
Selective RF repeaters only repeat signals from their donor transmitters whereas non-selective RF repeaters receive and
retransmit wanted signals as well as interference.
The main parameters of a repeater are:
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Donor transmitter name
X and Y coordinates
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other repeaters
EIRP
Amplifier gain
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Feeder type and its transmission and reception lengths
Any user-defined flags and parameters
The figure below presents the repeater properties window while the figure below that gives an example of a best server
prediction plot with a repeater.
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Figure 9.6
Repeater properties window
RF repeater
Donor transmitter
Figure 9.7
RF repeater coverage plot
GSM/GPRS/EDGE Network Configuration Parameters
Atoll allows setting and modifying network-level configurations and parameters applicable to the entire project.
9.2.1 Frequency Bands and Carriers
Atoll supports multi-band GSM networks deployed on different HCS layers or in concentric cells using frequency hopping
(baseband or synthesised). Atoll supports frequency hopping at subcell level. Mobile allocation list (MAL), hopping sequence
number (HSN) and mobile allocation index offset (MAIO) can be defined for each SFH transmitter.
In Atoll, a frequency band is characterized by its operating frequency and carriers. You can add, modify, and delete frequency
bands in Atoll as required. Atoll also models inter-carrier interference based on carrier frequency collisions.
The figure below presents the GSM frequency bands table.
Figure 9.8
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Frequency bands can be divided into domains dedicated to BCCH or to different layers of the network. Frequency domains
can be split into frequency groups. This allows for enhanced management of frequency-reuse pattern (3x9, 4x12, etc.). The
figure below gives an example of a domain/group allocation.
Figure 9.9
Frequency domains and groups
9.2.2 Global Network Settings
GSM-specific parameters that are applicable to the entire network are modelled in Atoll as global network settings. These
parameters include the interferer reception threshold, receiver height, antenna, losses, and the adjacent channel protection
level. The figure below presents the network level properties dialog box.
Figure 9.10 GSM network level parameters
9.2.3 HCS (Hierarchical Cell Structure) Layers
Multi-layer networks can be modelled in Atoll. Different layers with different priority levels can be assigned to each
transmitter. The figure below illustrates the multi-layer concept.
Layer 1 (Micro)
Layer 2 (Macro)
Layer 3 (Umbrella)
Figure 9.11 Hierarchical cell structure deployment
The main HCS layer parameters are:
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Priority
Reception threshold
Maximum user speed
Based on HCS layer priorities, Atoll can spread traffic between different layers and dimension the network, i.e., calculate the
numbers of required TRXs per transmitter, by taking into account the traffic absorbed by each layer.
Using Atoll, you can also calculate the service area of each layer, generate reports for each layer separately or for all the
layers combined, and carry out automatic frequency planning including different layers.
9.2.4 Voice Codec Configuration
Codec configurations enable the management of different voice codecs used in GSM. Codec configurations define codec
adaptation/selection thresholds in terms of required signal level and quality, and quality indicators such as BER, FER, and
MOS for ideal and non-ideal link adaptation.
You can create different codec configurations for different Active Codec mode Sets (ACS). For example, a certain codec
configuration might have full-rate and half-rate codec modes defined for 12.2 Kbps, 7.4 Kbps, 5.9 Kbps, and 4.75 Kbps. This
configuration would then only be compatible with the defined modes.
Figure 9.12 Codec configuration properties
9.2.5 GPRS/EGPRS/EGPRS2 Coding Scheme Configuration
Coding scheme configurations enable the management of different GPRS/EGPRS/EGPRS2 coding schemes in EDGE networks.
Coding scheme configurations define coding scheme selection thresholds in terms of required signal level and quality, the
throughputs provided by each coding scheme at different C and C/I levels.
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Figure 9.13 Coding scheme configuration properties
9.2.6 Timeslot Configuration
Timeslot configurations can be used to allocate different timeslot types to TRXs. A timeslot configuration describes how
circuit, packet, and shared timeslots are distributed in a subcell depending on the number of TRXs. Shared timeslots are used
for both circuit-switched and packet-switched calls.
The distribution and definition of timeslot configurations have an influence on the network dimensioning results and the
calculation of Key Performance Indicators (KPIs). The figure below gives an example of such a configuration.
Figure 9.14 Timeslot configuration properties
9.2.7 TRX Configuration
TRX configurations allow you to manage hardware capabilities in term of coding schemes. For each TRX, it is possible to
impose a maximum coding scheme for GPRS and EDGE each. The figure below gives an example of such a configuration.
Figure 9.15 TRX configuration properties
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9.2.8 Quality Indicators
In Atoll, quality indicators (BER, BLER, FER, MOS, etc.) represent the coverage quality at different locations. The quality
indicators table lists the available quality indicators which you can add, remove, and modify as required.
Figure 9.16 GSM quality indicators table
GSM/GPRS/EDGE Radio Equipment
Atoll provides the option to define various pieces of radio equipment such as antennas, transmitter equipment, feeders,
tower mounted amplifiers, reception equipment, etc. For more information on common antenna and radio equipment
features, see 4 Antenna and Radio Equipment Features.
GSM/GPRS/EDGE Traffic Model
In Atoll, the radio network dimensioning is based on a traffic analysis. According to the definition of the services and users in
the network, and depending on the traffic cartography (traffic data), Atoll determines the amount of traffic on each
transmitter of each HCS layer in the network. Network dimensioning, i.e., the calculation of the numbers of required timeslots
and TRXs, is carried out based on the traffic spread and balanced among transmitters.
Service and user behaviours are modelled in Atoll through different tables that provide information about:
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The services available in the network
The terminals compatible with the network
The mobility types
The user profiles describing the way users access different services
The GSM/GPRS/EDGE traffic model is shown in the figure below.
Figure 9.17 GSM/GPRS/EDGE traffic model
9.4.1 Services
The services table describes the services that are available in the network. Both voice and data type services are supported
and have specific parameters. The main service parameters are:
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Service type (circuit, packet with maximum bit rate, or packet with guaranteed bit rate)
Maximum blocking probability
Maximum packet delay (for packet services)
Minimum or guaranteed throughput (for packet services)
Required availability (for packet services)
Maximum number of timeslots per carrier (for packet services)
Throughput conversion parameters from RLC to Application layer
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An example of a service properties window is presented in the figure below.
Figure 9.18 Service properties window
9.4.2 Terminals
The terminals table describes the terminals that can be used in the network, cell phones, smartphones, in-car navigation
devices, etc. The following parameters model a terminal:
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Frequency bands
Noise figure
Supported codec configuration
GPRS/EDGE support
Supported GPRS/EGPRS/EGPRS2 coding scheme configuration
Highest GPRS/EDGE coding schemes
Number of downlink timeslots per carrier
Number of simultaneous carriers
An example of a terminal properties window is given in the figure below.
Figure 9.19 Terminal properties window
9.4.3 Mobility Types
The mobility type defines different user speeds.
9.4.4 User Profiles
The user profiles table models the behaviour of the different user categories. Every user profile contains a list of services and
their associated parameters describing how these services are accessed by the users.
Parameters for circuit-switched services are:
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The average number of calls per hour
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The average duration of each call
The terminal used when requiring access to this service.
Parameters for packet-switched services are:
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The average number of sessions per hour
The data volume transferred on the downlink during each session
The terminal used when requiring access to this service.
The figure below shows a user profile window.
Figure 9.20 User profile window
9.4.5 Traffic Data
For information on traffic data cartography, see 2.2.7 Traffic Data.
GMS/GPRS/EDGE Network Capacity Analysis and Dimensioning
GSM/GPRS/EDGE network capacity analysis comprises transforming traffic data from traffic maps to per-subcell traffic
demands. The distribution of traffic to each subcell in Atoll takes into account the GSM/GPRS/EDGE traffic model as well as
network parameters including HCS layer priorities, transmitter service areas, HR/FR ratios, etc.
The traffic demand calculated for and assigned to each subcell is defined in terms of Erlangs for circuit switched services and
as kbps for packet-switched services. This traffic demand, once assigned to each cell, it used by Atoll in the next step: network
capacity analysis and dimensioning.
The network dimensioning process determines the number of TRXs that would be necessary to carry the traffic assigned to
each subcell according to the user-defined QoS criteria. In addition to the numbers of required TRXs and the assignment of
suitable timeslot configurations to subcells, outputs of the network dimensioning process include subcell traffic loads and
key performance indicators (KPIs) such as the blocking rate and delay.
The figure below presents an overview of network capacity analysis and dimensioning in Atoll.
Figure 9.21 Network capacity analysis and dimensioning
During the traffic analysis phase, traffic from selected traffic maps is spread over the service areas of transmitters (calculated
per cell layer: micro, macro, umbrella, etc.) according to mobility types (e.g., slow moving mobiles are usually allocated to
microcells rather than umbrella cells), frequency bands (e.g., 900 MHz, 1800 MHz, dual band mobiles, etc.), and technology
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(i.e., GSM, GPRS, EDGE). The amount of traffic (Erlangs and kbps) assigned to each subcell also depends on the
GSM/GPRS/EDGE traffic model.
The figure below provides an example of traffic analysis results.
Figure 9.22 Traffic analysis results
During network dimensioning, Atoll calculates the numbers of required TRXs per sector according to the traffic analysis results
and user-defined quality of service requirements. Dimensioning takes into account:
The network dimensioning feature in Atoll allows you to set the following parameters for dimensioning:
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Maximum number of TRXs per transmitter
Circuit traffic queue model: Erlang B or Erlang C
Minimum number of dedicated packet-switched timeslots
Maximum number of additional packet-switched TRXs
Key performance indicators (KPI): Minimum data rate, blocking probability, and delay (or any combination of these
three KPIs)
The preferred timeslot configuration
For packet-switched data, the transmitter load influence on the network performance (data throughput, delay, and
blocking rate) is modelled through user-defined graphs.
The corresponding network dimensioning directives are shown in the figure below.
Figure 9.23 GSM/GPRS/EDGE network dimensioning directives
Dimensioning results are presented in a table and contain the following information per transmitter and per TRX type (e.g.,
BCCH, TCH, TCH_INNER, etc.):
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The required number of TRXs
The required number of shared timeslots
The required number of dedicated packet-switched timeslots
The required number of dedicated circuit-switched timeslots
The traffic load
The maximum number of TRXs supported
The traffic overflow target rate
The packet-switched traffic demand
The average number of timeslots used for packet-switched
The circuit-switched traffic demand
The average number of timeslots used for circuit-switched usage
The actual blocking rate
The figure below gives an example of dimensioning outputs.
Figure 9.24 GSM/GPRS/EDGE network dimensioning results
Atoll can also calculate the performance (KPI) of an existing configuration. A similar table as above provides the performance
details.
GSM/GPRS/EDGE Monte Carlo Simulations
Atoll simulates GSM/GPRS/EDGE radio resource management mechanisms. It calculates, for each user distribution (called a
random trial), the different network parameters such as the mobile activity, received signal levels, C/I levels, codec modes,
and coding schemes. As outputs, Atoll provides the traffic loads which can then be assigned to the different cells and the C/I
coverage can be performed based on realistic simulation results.
A Monte Carlo simulation in Atoll corresponds to a given distribution of users. It is a snapshot of a GSM/GPRS/EDGE network.
GSM/GPRS/EDGE Monte Carlo simulations can be analysed, displayed and stored. They can be used in a next step to generate
numerous coverage predictions.
9.6.1 Generation of Realistic User Distributions
Realistic distributions of users on the map are required as inputs to the GSM/GPRS/EDGE simulation algorithm. A “Realistic
User Distribution” corresponds to a user distribution that complies with the service and user model and the traffic data. Atoll
generates these user distributions using a Monte Carlo (statistical) algorithm.
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9.6.2 Scheduling and Radio Resource Management
For each user distribution, Atoll simulates the RRM mechanism of GSM/GPRS/EDGE cells. The simulation ends when the
scheduler has allocated resources to all the users and has determined the traffic loads for all the cells in the simulation.
The figure below shows an overview of the simulation algorithm.
Figure 9.25 GSM/GPRS/EDGE simulation overview
The following steps are carried out during each iteration of a GSM/GPRS/EDGE Monte Carlo simulation for all the generated
mobiles:
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Best server determination: Atoll determines the best server for each mobile and the mobile allocation table
according to the frequency hopping parameters.
Users can be rejected at this stage for "No Coverage".
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Downlink calculations: The downlink calculations include the calculation of downlink C/I, determination of the best
available codec modes and coding schemes, and the downlink power control.
Users can be rejected at this stage for "No Service".
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Uplink calculations: The uplink calculations include the calculation of uplink C/I, determination of the best available
codec modes and coding schemes, evaluation of the number of required timeslots, and power control.
Users can be rejected at this stage for "No Service".
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Radio resource management and cell load calculation: Atoll uses an intelligent scheduling algorithm to perform
radio resource allocation to packet service users.
Users can be rejected at this stage for "Resource Saturation".
Main simulation outputs are:
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The cell loads (i.e., uplink and downlink traffic loads, uplink noise rise, power control gain, DTX gain, half-rate traffic
ratio), and
User throughputs.
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Note that numerous other parameters are available and stored during the simulation for further analysis. For more
information, see 9.6.5 Simulation Reports.
9.6.3 Monte Carlo Simulation Management
GSM/GPRS/EDGE simulations are managed through the Simulations folder in the Atoll Explorer window. This folder is
displayed in the figure below.
Figure 9.26 GSM/GPRS/EDGE simulations folder
The Simulations folder is made up of several simulation “groups”. Each group corresponds to a network configuration for
which a user-specified number of Monte Carlo simulations have been generated. As an example, different groups may
correspond to different traffic assumptions. The figure below shows the simulation creation dialog box.
When several simulation groups are available, it is possible to automatically display one group after the other, hence
animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
The following information is required when creating a new group of Monte Carlo simulations:
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The simulation group name
The number of simulations to be run
The traffic maps used
The convergence criteria.
Figure 9.27 GSM/GPRS/EDGE simulation creation dialog box
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Once a simulation (or a group of simulations) has been performed, simulation reports are available and simulation results can
be graphically analysed in Atoll.
9.6.4 Simulation Graphical Analysis
Graphical Display: Mobile Connection Status
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for their connection status. The different possible statuses are:
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Connected DL + UL: the mobile is connected on both downlink and uplink
Connected UL: the mobile is connected on uplink only
Connected DL: the mobile is connected on downlink only
Resource Saturation: the mobile is rejected because all the resources have been allocated to other mobiles
No Service: the mobile is rejected because it is outside the coverage area.
An example of a graphical display of a group of simulations is presented in the figure below.
Figure 9.28 GSM/GPRS/EDGE simulation display by connection status
Graphical Display: Codec Modes and Coding Schemes
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for codec modes and coding schemes.
An example of a graphical display of a group of simulations is presented in the figure below.
Figure 9.29 GSM/GPRS/EDGE simulation display by codec modes and coding schemes
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Individual Mobile Results Graphical Display
Parameters for any user can be displayed either in the results table or directly on the map (as presented in the figure below).
Figure 9.30 Individual mobile results display using the tool tip
9.6.5 Simulation Reports
Atoll provides detailed simulation results in the form of reports.
Reports of a Single Simulation
A report is available for each simulation. This report contains information about the simulation statistics, and calculation
results by sites, cell, and mobile as given in the figure below.
Figure 9.31 GSM/GPRS/EDGE simulation report
The simulation results are provided at the following different levels:
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Global statistics: total users attempting a connection and the corresponding break-up per service; total users
actually connected and the corresponding break-up per service.
Results per site: sum of user throughputs for all the subcells of a site, globally and per service type, for both uplink
and downlink.
Results per subcell: uplink and downlink traffic loads, power control gain, half-rate traffic ratio, DTX gain.
Results per TRX: uplink noise rise.
Results per mobile: geographic location, receiver height, terminal type, service, user profile, mobility, activity status
(DL/UL), serving cell, frequency band, TRX type, uplink and downlink requested and obtained throughputs, uplink
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and downlink timeslots, uplink and downlink C/I, mobile allocation table (channels and MAIO), uplink and downlink
codec modes, uplink and downlink coding schemes, etc.
Initial conditions: parameters and traffic maps used to create the simulation.
Reports of a Group of Simulations
Atoll provides detailed simulation results averaged over a group of simulations in the form of reports. The report generated
for a simulation group contains:
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Statistics: average statistics obtained from the results of all the simulations in a group
Results per site: average site results obtained from the results of all the simulations in a group
Results per subcell: average subcell results obtained from the results of all the simulations in a group
Results per TRX: average TRX results obtained from the results of all the simulations in a group
Initial conditions: parameters used to create the simulation group.
Figure 9.32 GSM/GPRS/EDGE simulation group report
9.6.6 Updating Cell Loads
You can store the cell loads calculated by Monte Carlo simulations in the cells data table. This enables you to update the
network cell loads based either on the average results from a simulation group or the results of from a single simulation. Cell
load values for all the cells in the network radio database are then updated with the results generated by the selected
simulation. Cell loads from a simulation, simulation group, or from the cells data table can then be used to generate coverage
prediction plots.
9.6.7 Exporting Results
You can export the simulation results as described in 2.5.1 Network Data Import and Export.
GSM/GPRS/EDGE Coverage Predictions
In Atoll a coverage prediction is a plot displaying calculation results of user-selected parameters on the map and enabling
graphical as well as statistical analysis of the network behaviour. Examples of GSM/GPRS/EDGE coverage predictions are
coverage by transmitter, coverage by C/I levels, EDGE coding schemes, etc. For each pixel, Atoll calculates the required
information. This data is then graphically represented by a colour according to a user-defined legend. Different display options
are available in Atoll, depending on the calculated parameter.
Atoll models the effect of downlink power control on interference. An average power control gain can be defined for each
subcell defining the reduction in interference due to power control in downlink.
9.7.1 Coverage Prediction Calculation and Management
Coverage predictions are performed by assuming a “probe mobile” (non-interfering terminal) on each pixel of the considered
area. The probe mobile characteristics are specified as inputs to the coverage prediction in order to calculate the user-defined
prediction parameter.
Predictions are stored as multi-layer geographic objects in the Predictions folder of the Explorer window and can be displayed
in the map window. When several coverage predictions are available, it is possible to automatically display one prediction
after the other, hence animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
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Subfolders can be created in the Predictions folder in order to group various coverage prediction objects into categories.
Coverage predictions can be directly created under a subfolder and moved from one subfolder to another using the mouse.
9.7.2 Coverage Prediction Types
GSM/GPRS/EDGE coverage predictions can be generated either based on the results from Monte Carlo simulations or on
user-defined cell load configurations.
GSM/GPRS/EDGE coverage prediction types and their display options available in Atoll are listed below.
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Coverage by transmitter (DL)
o Transmitter
o Number of required TRXs
o Cell type
Coverage by signal level (DL)
o Signal level (dBm, dBµV or dBµV/m)
o Path loss (dB)
o Reliability level
o Best C2
Coverage by signal level (UL)
o Signal level (dBm, dBµV or dBµV/m)
o Total loss (dB)
Overlapping zones (DL)
o Number of servers
Coverage by C/I level (DL)
o C/I level
o Minimum C/I level
o Maximum C/I level
Coverage by C/I level (UL)
o C/I level
o Minimum C/I level
o Maximum C/I level
Interfered zones (DL)
o Transmitter
Service area analysis (DL)
GPRS/EDGE coding schemes (DL)
o Coding schemes
o Best coding schemes
Packet quality and throughput analysis (DL)
o Actual, maximum, and average RLC throughput/timeslot
o Actual, maximum, and average RLC throughput
o Actual, maximum, and average application throughput/timeslot
o Actual, maximum, and average application throughput
o Actual, maximum, and average throughput per user
o BLER, maximum BLER
Circuit quality indicator analysis (DL)
o BER, FER, MOS
o Maximum BER, FER, MOS
Examples of GSM/GPRS/EDGE coverage predictions are shown in the figures below.
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Figure 9.33 GSM/GPRS/EDGE coverage by transmitter
Figure 9.34 GSM/GPRS/EDGE coverage by signal level
Figure 9.35 EDGE coding scheme coverage prediction
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Figure 9.36 GSM/GPRS/EDGE coverage by signal reliability level
Figure 9.37 GSM/GPRS/EDGE coverage by C/I level
Figure 9.38 EDGE throughput coverage prediction
Detailed, per-TRX, coverage prediction results are available for the following prediction types:
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Coverage by C/I level
Interfered zones
GPRS/EDGE coding schemes
Packet quality and throughput analysis
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Circuit quality indicator analysis
Different predictions can be compared by overlaying. The figure below shows an example of a coverage prediction by C/I
level with detailed results.
Figure 9.39 Coverage prediction by C/I level calculated for each TRX
Coverage predictions can be calculated for multi-layer networks. For each coverage prediction, two different plot types can
be generated and displayed as multi-layer objects:
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One separate plot for each individual layer
One plot for all the HCS layers by selecting the highest priority HCS layer for each pixel.
Figure 9.40 Micro layer coverage (left) and macro layer coverage (right)
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Figure 9.41 Umbrella layer coverage (left) and all layers coverage (right)
9.7.3 Coverage Prediction Reports
Atoll can generate reports for one or more coverage predictions with various detail levels as defined by the user. Reports are
spread sheet-like tables that can be printed directly from Atoll or exported to any desktop tool. An example of such a report
is given in the figure below.
Figure 9.42 GSM/GPRS/EDGE coverage prediction report
9.7.4 Coverage Prediction Comparison
Comparison (difference, intersection, union, or merge) between two coverage predictions can be performed. As examples,
this functionality can be used:
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To compare uplink and downlink coverage of a service. This enables you to determine uplink/downlink-limited
zones for that service.
To compare service area coverage plots of two different services. This enables you to assess the areas where one
service (e.g., VoIP) is available while the other (e.g., high speed internet) is not.
Service area coverage plots between two different network deployment scenarios (with different technologies). The figure
below illustrates such a case by comparing a GSM and a UMTS coverage. Note that, in this example, UMTS transmitters are
installed on only some of the GSM sites.
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Figure 9.43 Coverage prediction graphical comparison (GSM versus UMTS example)
Atoll also enables you to carry out per-pixel arithmetical operations between coverage predictions. For example, you can
calculate the sum, difference, min, max, and average of similar calculated parameters per pixel from two coverage predictions
of the same or different technologies.
9.7.5 Coverage Prediction Export
Any coverage prediction can be exported in the following formats:
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Atoll format
ArcView SHP
MapInfo MIF and TAB
ArcView Grid TXT and ASC
Vertical Mapper GRD and GRC
BMP
PNG
TIFF
BIL
JPEG2000
JPEG
When exported in MapInfo format, coverage prediction attributes (e.g., signal levels, transmitter IDs, etc.) are exported along
with the plot. The figure below gives an example of the exported attributes for a coding scheme prediction.
Figure 9.44 GSM/GPRS/EDGE coverage prediction attributes export to MapInfo
9.7.6 Point Analysis Tool
A real-time prediction analysis tool is available in Atoll. The point analysis tool is dynamically linked to the map window. The
displayed information is updated as the receiver is moved on the map window. The point analysis tool provides the downlink
signal values numerically and graphically for all cells and for the selected terminal type, mobility type, and service type.
The figures below show the point analysis window.
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Receiver
Reception analysis tool
Parameters
Signal strength
Figure 9.45 GSM/GPRS/EDGE point-to-point real-time analysis
Total interference
Figure 9.46 GSM/GPRS/EDGE point-to-point real-time interference analysis
Figure 9.47 GSM/GPRS/EDGE point-to-point real-time interference details
9.7.7 Multi-Point Analysis
Atoll enables you to carry out point predictions on multiple point locations and at different heights. Multi-point analyses can
be carried out on imported lists of points, subscriber locations from fixed subscriber traffic maps, as well as points created
on the map using the mouse.
Multi-point analyses may be useful in verifying network QoS at specific locations in case of reported incidents such as call
drops, low throughputs, etc. Multi-point analysis calculations can be based on user-defined network load conditions in the
Cells table or loads calculated using Monte Carlo simulations. The figure below shows the multi-point analysis creation dialog
box.
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Figure 9.48 GSM multi-point analysis creation dialog box
Multi-point analysis results include a number of radio parameters at each point calculated for all potential servers. The results
provided by this analysis are the same as available for one point in the Details view of the Point Analysis tool. Multi-point
analysis results are stored in the Multi-Point Analysis folder in the Network explorer. Once calculated, multi-point analysis
results are available in tabular form and visible on the map using symbols and colours based on calculation results.
Figure 9.49 GSM multi-point analysis results
You can export the multi-point analysis results as described in 2.5.1 Network Data Import and Export.
GSM/GPRS/EDGE Neighbour Planning
Atoll supports the following neighbour types in a GSM network configuration:
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Intra-technology neighbours: GSM transmitters defined as neighbours of other GSM transmitters in the same Atoll
document.
Inter-technology neighbours: GSM transmitters defined as neighbours of cells which use a technology other than
GSM.
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Neighbour plans can be generated by any of the following means in Atoll:
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Importing an external neighbour plan (e.g., in Excel format)
Automatically producing a neighbour plan as described in 9.8.1 Automatic Neighbour Allocation
Graphically and/or manually creating, editing and deleting a neighbour plan as presented in 9.8.2 Graphical
Neighbour Plan Editing.
Various neighbour plans can be compared. The results of an automatic neighbour allocation can be compared with the
existing neighbour plan. As well, neighbour plans from external sources can also be compared with the existing neighbour
plan in Atoll.
9.8.1 Automatic Neighbour Allocation
Neighbour lists can be generated automatically in Atoll. For each cell, potential neighbours are ranked according to their
importance. The neighbour planning algorithm considers the following user-specified parameters:
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Hysteresis zone defined by a handover start and a handover end margin with respect to the best server signal
strength
Maximum inter-site distance
Maximum number of neighbours
Minimum area covered (overlapping area between the reference cell and its potential neighbour)
Covered traffic
Importance ranges for distance, coverage, adjacency, and co-site factors.
Neighbour lists can be generated automatically in Atoll. For each cell, potential neighbours are ranked according to their
“importance”. The neighbour planning algorithm considers the following user-specified parameters:
Forcing “neighbour symmetry”, “adjacent cells as neighbour”, “co-site cells as neighbours“ and/or “exceptional neighbour
pairs” is possible with Atoll. The figure below displays the automatic neighbour allocation dialog box.
Figure 9.50 GSM automatic neighbour list generation
9.8.2 Graphical Neighbour Plan Editing
Neighbour plan can be graphically edited in Atoll. Clicking a transmitter on the map displays all its neighbour relations. All
types of neighbour relations (outwards, inwards or symmetrical) can be created, edited and/or deleted graphically. Such an
example is presented in the figures below.
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Figure 9.51 Graphical neighbour plan editing
Figure 9.52 Neighbour planning using a best server plot
9.8.3 Neighbour Consistency Check Tool
A neighbour relation audit is available in Atoll. This function enables you to determine inconsistencies in the current
neighbour plan. The figure below shows the neighbour relation conditions that can be verified using the audit.
Figure 9.53 Neighbour audit
GSM/GPRS/EDGE Automatic Frequency Planning
Atoll’s automatic frequency planning (AFP) module automatically generates frequency plans for GSM/GPRS/EDGE networks.
The following parameters can be allocated automatically:
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Frequency
Base station identification code (BSIC)
Mobile allocation list (MAL)
Hopping sequence number (HSN)
Mobile allocation index offset (MAIO)
The AFP aims at allocating network parameters in a way that optimises the network, i.e. allocations that minimize interference
over the network and comply with a set of user-defined constraints. The two main constraints are the separation constraints
and the spectrum limitations. The AFP uses a cost function in order to evaluate frequency plans. The objective of the AFP
algorithm is to find frequency plans with the least costs. The cost function parameters are specified by the user. Optionally,
the AFP can also optimise the numbers of TRXs assigned to each transmitter in order to increase the amount of non-interfered
traffic.
For the automatic allocation of BSIC, the AFP can take into account reuse distances, and inter-technology neighbour relations
in a multi-RAT network planning environment. In other words, the AFP takes into account BSIC collisions between GSM
transmitters that are neighbours of the same UMTS or LTE cell. The AFP can carry out network-wide automatic allocation or
localised allocation for certain cells while the rest of the network is considered to be locked for allocation.
The Atoll AFP module uses simulated annealing, taboo search, graph heuristics, and machine learning. It manages its time
resources by following a user-defined time directive: the more time available, the more the AFP learns the network in order
to tune its parameters accordingly. During the network learning phase, the AFP executes numerous fast and deterministic
instances of the AFP. The one that promises the best performance is memorized in the project as being the most adapted to
the current network. In the following runs, the AFP starts from where the learning process last ended.
9.9.1 Interference Histogram Matrices
Interference matrices are a key input when using an automatic frequency planning (AFP) tool. Atoll is capable of generating
and importing interference matrices from various sources. Interference matrices can be used in conjunction with the Atoll
AFP module or exported for use with a third party AFP tool.
Interference Matrix Generation
Atoll can generate interference matrices providing a histogram of mutual interference between interfered and interfering
subcells. This histogram contains the probability of interference for different values of C/I, assuming both interfered and
interfering subcells use the same frequency. You can choose whether the interference probability is stated in percentage of
interfered area or of interfered traffic. The figure below gives an example of such a histogram.
Figure 9.54 Mutual interference histogram for a pair of subcells
Interference matrices can be based on predictions, OMC measurements, drive tests, scans and CW measurements.
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Figure 9.55 Interference matrices from various sources
Interference Matrix Analysis
Atoll’s interference matrix analysis tool enables you to visually analyse interference matrices for each individual subcell on
the map as well as in the form of a list. Each subcell can be studied as the interfered or interfering subcell. The resulting list
of interferers can be filtered based on several criteria.
Figure 9.56 Interference matrix analysis tool
Interference Matrix Export
It is possible to export the interference histogram matrices to ASCII text files of different syntaxes. The exported interference
histogram matrix can be used as input to third party AFP tools. The following figure shows an extract of an exported
interference histogram matrix.
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Figure 9.57 Exported interference histogram matrix
9.9.2 Automatic Frequency Planning Parameters
The following AFP parameters can be defined by the user:
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Cost function: Frequency separation violation costs and MAL length contribution
Interferences influence: DTX and MAL length impacts on interference calculations
Directives: The MAL length is either adjusted during the AFP process or set to its maximum length; the HSN can be
allocated either freely or by subcell/transmitter/site; a target fractional load and a target frequency reuse can be
specified as guidelines (rather than strict constraints) for the AFP algorithm.
Resources to allocate: Frequency, BSIC, MAL, HSN, and MAIO
Default separation constraints: Minimum frequency spacing to respect between co-site, co-cell, and neighbours
Exceptional transmitter pair separation constraints: Minimum frequency spacing to respect between co-site, cocell, and neighbours
Interference: To be taken into account or not. Note that interference can be calculated in Atoll (as explained in
9.9.1 Interference Histogram Matrices) or imported from an external source
Discontinuous transmission (DTX): To be included in calculation or not
Shadowing fading
BSIC reuse distance
Bandwidth limitation on transmitters: Frequencies assigned to TRXs of a transmitter must be within the defined
bandwidth due to hardware limitations
In addition, the current frequency plan can be locked per transmitter or per TRX before running the AFP. This allows keeping
the current frequency allocation when assigning frequencies to newly added base stations.
The figures below show the dialog boxes corresponding to the AFP parameters.
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Figure 9.58 AFP parameters
Figure 9.59 AFP progress
9.9.3 Automatic Frequency Planning Outputs
The Atoll AFP outputs are presented in a table where transmitter, subcell, and TRX-level results can be displayed. Details of
each assigned resource are provided: locked resource, modified resource with/without separation violation, resource not
modified, assigned resource with/without separation constraints, etc. Results can be committed to the network database.
An example of the AFP results output window is given in the figure below.
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Figure 9.60 AFP outputs
9.9.4 Interactive Frequency Planning
Atoll’s interactive frequency planning tool is designed to make precise local changes in an existing frequency plan, or to make
new assignments easily without having to rerun the AFP. Selecting a sector on the map shows information regarding conflicts
in the current frequency assignments or candidate channels. This tool uses the AFP cost function to find the most suitable
candidate channels.
Figure 9.61 Interactive frequency planning tool
9.9.5 Frequency Plan Analysis
Frequency Plan Audit
A frequency plan audit tool is available in Atoll which enables to check the following parameters:
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The definition of a unique BCCH TRX per transmitter
The consistency between TRXs and related cell types
In case of “non-hopping” or “baseband hopping”: the definition of a unique frequency per TRX
In case of “synthesised hopping”: the definition of a frequency list per TRX, respecting the maximum MAL lengths,
the MAIO to be less than the number of MAL frequencies.
The following optional checks can be performed:
Domain constraints (frequency, HSN, BSIC and/or compliance with the allocation strategy – “free” or “group
constrained”)
Separation constraints (co-site, co-cell, between neighbours and exceptional pairs).
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The figure below presents the frequency plan audit tool dialog box.
Figure 9.62 Frequency plan audit tool
Frequency Channel Search
A frequency channel search tool is available in Atoll. This feature enables you to easily highlight the transmitters assigned to
a specific channel as well as its adjacent ones. The search can be limited to BCCH channels or TCH channels or involve all types
of TRXs. BSIC or BCCH channel/BSIC combination can also be located in the same manner. The frequency channel search
dialog box is shown in the figure below.
Figure 9.63 Frequency channel search tool
Sector-to-Sector Interference Analysis
To facilitate interference analyses, Atoll offers sector to sector interference tool. This tool enables you to analyse the possible
amount of interference between a pair of particular sectors.
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Figure 9.64 Sector-to-sector interference analysis tool
GSM/GPRS/EDGE Automatic Cell Planning
The Atoll GSM ACP (Automatic Cell Planning) module enables you to automatically determine the best GSM parameter
settings for your network. The aim of the Atoll ACP is to improve network quality in terms of both coverage and capacity. For
a comprehensive description of the Atoll ACP, see 17 Automatic Cell Planning (ACP) Features.
.
The Atoll GSM ACP is capable of optimising network parameters (antenna types, heights, azimuths, tilts, transmission powers,
etc.) based on the following GSM quality indicators:
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BCCH signal level
Co-channel CINR
Overlap
Best server distance
1st-Nth difference
GSM/GPRS/EDGE Co-planning With Other Radio Access Technologies
Atoll supports integrated GSM/UMTS/LTE/NB-IoT co-planning. Other radio access technologies can also be combined with
UMTS in Atoll. For more information, see 11 Multi-RAT Features.
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10 CDMA2000 Features
The Atoll CDMA2000 module provides a comprehensive and accurate modelling of multi-carrier and multi-band CDMA2000
1xRTT and 1xEV-DO networks. It supports all 1xRTT, 1xEV-DO Rev. 0, Rev. A, and Rev. B physical channels and carrier types.
It also includes detailed modelling of forward and reverse link Rev. A and Rev. B bearers, and voice and data services.
Atoll provides the means to set up multi-service traffic maps from multiple sources: vector, raster and live traffic data. Traffic
maps are used in CDMA2000 Monte Carlo simulations for network capacity analysis including forward and reverse link power
control, RRM with multi-carrier allocation algorithms, H-ARQ, and rate downgrading. Coverage predictions can be calculated
based on Monte Carlo simulation results or on live network loads from the OMC in order to study coverage and capacity of
the network.
Atoll includes automatic multi-carrier neighbour planning features that allow analysing handoffs in the network. Automatic
PN offset planning can be performed using various allocation strategies, with analysis tools enabling auditing of PN offset
allocations.
Atoll includes integrated single RAN–multiple RAT network design capabilities for cellular radio access technologies including
5G NR, LTE, NB-IoT, UMTS, GSM, and CDMA. It features a multi-technology network database, a unified traffic model, and a
combined Monte Carlo simulator. The Atoll LTE ACP can be used to automatically optimise network parameters to increase
coverage and capacity. It can also carry out site selection for greenfield and site activation for densification scenarios.
An overview of the CDMA2000 modelling in Atoll is shown in the figure below.
Figure 10.1 CDMA2000 network modelling in Atoll
CDMA2000 Network Model
The CDMA2000 network model comprises radio network elements such as sites, transmitters, and cells. A CDMA2000 base
station is equivalent to a site, its transmitters with one or more radio channels (cells) each.
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Figure 10.2 CDMA2000 network model
10.1.2 Sites
A site represents the physical location where base stations can be installed. An example of a site properties window is shown
in the figure below.
Figure 10.3 Site properties window
Site parameters are:
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Geographic coordinates
Altitude (user-defined or automatically extracted from the terrain elevation data)
Any user-defined flags and parameters such as address, owner, deployment phase, etc.
10.1.3 Transmitters
Transmitters in Atoll correspond to sectors and antennas installed at a site. The main transmitter parameters are:
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Transmitter name and the name of the site where it is installed
X and Y coordinates
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other transmitters
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Tower mounted amplifier (TMA)
Feeder type and its transmission and reception lengths
Maximum coverage range
Any user-defined flags and parameters
An example of a transmitter properties window is shown in the figure below.
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Figure 10.4 CDMA2000 transmitter properties window
10.1.4 Cells (1xRTT, 1xEV-DO)
Atoll supports multi-band, multi-carrier CDMA2000 networks. In Atoll, cells model the carriers used at a transmitter. A
transmitter can support different carriers. Each cell has its own radio resources and parameters, including:
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Cell name and the name of the transmitter to which the cell belongs
Carrier number
PN offset, PN offset locked/unlocked, PN offset domain, and PN offset reuse distance
Transmission powers: maximum, pilot, synchro, paging, total
Idle power gain (used in EV-DO Rev.0 and Rev.A, this gain is applied to the forward link power when there is no
active user connected to the cell)
Power reserved for pooling
Minimum RSCP
Minimum Ec/Io
T_Drop
Noise rise threshold and acceptable noise rise margin (used in EV-DO Rev.0 and Rev.A)
Reverse link load factor
Resource allocation constraints: maximum forward link load and reverse link load factor
EV-DO Rev.B multi-carrier support with associated MUG graph and minimum reverse link Ec/Nt
Maximum number of EV-DO users
MUG graph (used in EV-DO Rev.0 and Rev.A)
DRC error rate (used in EV-DO Rev.0 and Rev.A)
EV-DO timeslots dedicated to BCMCS
EV-DO timeslots dedicated to control channels
BCMCS throughput
Inter-technology interference: forward and reverse link noise rise
Neighbour parameters: maximum numbers of neighbours and neighbours lists
Any user-defined flags and parameters
The figure below presents an example of a transmitter with two cells: one 1xRTT and the other 1xEV-DO.
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Figure 10.5 CDMA2000 cell parameters
10.1.5 Site Templates
A site template is made up of one or more transmitters and cells located on the same site. Site templates can be created and
edited as needed. Building a network is facilitated by working with site templates rather than single site/transmitter/cell. By
default some CDMA2000 site templates are available for dense urban, urban, suburban, and rural environments.
10.1.6 Repeaters
A repeater receives, amplifies, and retransmits signals. Repeaters are used to extend the coverage of their donors. Atoll
models selective as well as non-selective RF repeaters, optic fibre repeaters, microwave repeaters, and remote antennas.
Selective RF repeaters only repeat signals from their donor transmitters whereas non-selective RF repeaters receive and
retransmit wanted signals as well as interference.
The main parameters of a repeater are:
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Donor transmitter name
X and Y coordinates
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other repeaters
Total gain
Amplifier gain
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Feeder type and its transmission and reception lengths
Any user-defined flags and parameters
The figure below presents the repeater properties window while the figure below that gives an example of a best server
prediction plot with a repeater.
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Figure 10.6 Repeater properties window
RF repeater
Donor transmitter
Figure 10.7 RF repeater coverage plot
CDMA2000 Network Configuration Parameters
Atoll allows setting and modifying network-level configurations and parameters applicable to the entire project.
10.2.1 Frequency Bands and Carriers
Atoll enables you to model multi-band, multi-carrier CDMA2000 networks. A frequency band is characterized by its operating
frequency and carriers. You can add, modify, and delete frequency bands in Atoll as required. You can also assign a type
(1xRTT or 1xEV-DO) to each carrier. The default CDMA2000 frequency bands available in Atoll are shown in the figure below.
Figure 10.8 CDMA2000 frequency bands table
Atoll can also calculate inter-carrier interference based on inter-carrier interference IRFs.
10.2.2 Global Network Settings
CDMA2000-specific parameters that are applicable to the entire network are modelled in Atoll as global network settings.
These parameters include the forward link power calculation method, the definition of the forward link load, the interference
calculation method, the soft handoff calculation method, parameters related to the reverse link 1xRTT power control. the
figure below presents the network level properties dialog box.
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Figure 10.9 CDMA2000 network level parameters
10.2.3 Radio Bearers
Radio bearers define the data transport format. Atoll manages forward link and reverse link 1xEV-DO bearers. The 1xEV-DO
radio bearer parameters are:
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Transport block size
RLC peak rate
10.2.4 Quality Indicators
In Atoll, quality indicators (BER, DCH BLER, etc.) represent the coverage quality at different locations. The quality indicators
table lists the available quality indicators which you can add, remove, and modify as required.
Figure 10.10 CDMA2000 quality indicators table
CDMA2000 Radio Equipment
Atoll provides the option to define various pieces of radio equipment such as antennas, transmitter equipment, feeders,
tower mounted amplifiers, reception equipment, etc. For more information on common antenna and radio equipment
features, see 4 Antenna and Radio Equipment Features.
10.3.1 Site Equipment
Site equipment model the base station level parameters that are applicable to all the transmitters and cells located at a site.
The following parameters define the equipment for each site:
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Manufacturer name
Multi-user detection factor
Rake factor (used in the reverse link rake receiver modelling)
Carrier selection method
Four options are available when assigning a carrier to a requesting user: the least loaded carrier in forward link, the
least loaded carrier in reverse link, a random carrier, or sequential allocation of carriers to users.
Overhead channel elements used in both forward and reverse links
Option to restrict the active set to the neighbours only
Option to pool power between transmitters of a base station
Option to share channel elements between transmitters of a base station
Figure 10.11 CDMA2000 site equipment definition
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For each site equipment type, the channel element consumption can be defined per radio configuration (RC). The figure
below gives the example of such a definition table.
Figure 10.12 Channel element consumption
10.3.2 Reception Equipment (1xRTT, 1xEV-DO)
CDMA2000 reception equipment model the reception characteristics of user terminals. Bearer selection thresholds and
quality indicator graphs are defined in CDA2000 reception equipment. The figures below give examples of such an equipment
definition.
Figure 10.13 CDMA2000 reception equipment – Quality indicator graphs
Figure 10.14 CDMA2000 reception equipment – Forward link 1xEV-DO bearer selection thresholds
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Figure 10.15 CDMA2000 reception equipment – Reverse link 1xEV-DO bearer selection thresholds
CDMA2000 Traffic Model
In Atoll, the radio network traffic is modelled using Monte Carlo simulations. According to the definition of the services and
users in the network, and depending on the traffic cartography (traffic data), realistic distributions of users are generated and
used as input to the power control and radio resource management algorithms.
Service and user behaviours are modelled in Atoll through different tables that provide information about:
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The services available in the network
The terminals compatible with the network
The mobility types
The user profiles describing the way users access different services
The CDMA2000 traffic model is shown in the figure below.
Figure 10.16 CDMA2000 traffic model
10.4.1 Services
The services table describes the services that are available in the network. Various types of services (speech, 1xRTT data,
1xEV-DO data, etc.) are supported and have specific parameters. The main service parameters are:
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Type (speech, 1xRTT data, 1xEV-DO Rev.0 data, 1xEV-DO Rev.A data, 1xEV-DO Rev.B data)
Priority level
QoS class (for 1xEV-DO Rev.A and 1xEV-DO Rev.B services)
Reverse link mode: high capacity or low latency (for 1xEV-DO Rev.A and 1xEV-DO Rev.B services)
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Preferred carrier
Bearer downgrading (for 1xEV-DO services)
Soft handoff support (for speech and 1xRTT services)
Forward and reverse link FCH activity factors (for speech and 1xRTT services)
Forward and reverse link guaranteed bit rates (for 1xEV-DO Rev.B services)
Forward and reverse link SCH throughput probabilities(for 1xRTT services)
Reverse link throughput probabilities (for 1xEV-DO services)
Body loss
Forward and reverse link Eb/Nt requirements per terminal type and SCH rate (for speech and 1xRTT services)
Minimum and maximum forward link traffic power per terminal type and SCH rate (for speech and 1xRTT services)
An example of the service properties window is presented in the figure below.
Figure 10.17 Service properties window
10.4.2 Terminals
The terminals table describes the terminals that can be used in the network, cell phones, smartphones, in-car navigation
devices, etc.
The following parameters model a voice/1xRTT terminal:
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Type
Supported frequency bands
Minimum and maximum transmission powers
Noise figures
Transmission and reception losses
Antenna gain
Reception equipment
Rho factor
Forward link rake factor
Active set size for the fundamental channel (FCH) and the supplemental channel (SCH)
Number of fingers
Nominal rate for the forward and reverse links
The minimum percentage of pilot power transmitted even when mobile is idle
The following additional parameters model a 1xEV-DO Rev.0 terminal:
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Acknowledgment (ACK) gain relative to the reverse link pilot power for the ACK channel
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Data rate control (DRC) gains relative to the reverse link pilot power for the DRC channel
Data channel gains relative to the reverse link pilot power for the data channel
The following additional parameters model a 1xEV-DO Rev.A terminal:
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Acknowledgment (ACK) gain relative to the reverse link pilot power for the ACK channel
Radio reverse indicator (RRI) gain relative to the reverse link pilot power for the RRI channel
Data rate control (DRC) gains relative to the reverse link pilot power for the DRC channel
Data channel and auxiliary pilot gains relative to the reverse link pilot power for the data channel
The following additional parameters model a 1xEV-DO Rev.B terminal:
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Handoff enabled/disabled
Highest supported modulation
Maximum number of carriers in multi-carrier mode
An example of a terminal properties window is given in the figures below.
Figure 10.18 Terminal properties window – General and 1xRTT tabs
Figure 10.19 Terminal properties window –1xEV-DO Rev.0 and 1xEV-DO Rev.A tabs
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Figure 10.20 Terminal properties window –1xEV-DO Rev.B tab
10.4.3 Mobility Types
The mobility type defines the minimum signal quality requirements for different user speeds. The following parameters model
a mobility type:
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Minimum Ec/Io offset
T_Drop offset
Minimum reverse link Ec/Nt for 1xEV-DO Rev.0
Graph of forward link throughput as a function of C/I for 1xEV-DO Rev.0
An example of a mobility type properties window is given in the figure below.
Figure 10.21 Mobility type properties window
Figure 10.22 Forward link throughput as a function of C/I
10.4.4 User Profiles
The user profiles table models the behaviour of the different user categories. Every user profile contains a list of services and
their associated parameters describing how these services are accessed by the users.
User profile parameters are:
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The average number of calls per hour
The average duration of each call
The terminal used when requiring access to this service
The figure below shows a user profile window.
Figure 10.23 User profile window
10.4.5 Traffic Data
For information on traffic data cartography, see 2.2.7 Traffic Data.
CDMA2000 Monte Carlo Simulation
CDMA2000 1xRTT networks automatically regulate transmission powers and interference using power control in both
forward and reverse links. CDMA2000 1xEV-DO networks perform power control reverse link and rate control in the forward
link. The overall objective is to minimise interference and maximise network capacity. Atoll simulates CDMA2000 1xRTT
network regulation mechanisms by calculating, for each user distribution (called a random trial), different network
parameters such as active set for each mobile, required power, soft handoff gains, etc. As outputs, Atoll provides the following
parameters characterizing the stabilized network:
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Cell total forward link power
Cell forward link throughput
Cell reverse link load
A Monte Carlo simulation in Atoll corresponds to a given distribution of users. It is a snapshot of a CDMA2000 network.
CDMA2000 Monte Carlo simulations can be analysed, displayed and stored. They can be used in a next step to generate
numerous coverage predictions.
10.5.1 Generation of Realistic User Distributions
Realistic distributions of users on the map are required as inputs to the CDMA2000 simulation algorithm. A “Realistic User
Distribution” corresponds to a user distribution that complies with the service and user model and the traffic data. Atoll
generates these user distributions using a Monte Carlo (statistical) algorithm.
10.5.2 Power Control and Radio Resource Management
For each user distribution, Atoll simulates the power control and RRM mechanism of CDMA2000 cells. In CDMA2000 1xEVDO, the reverse link supports power control whereas the forward link supports rate control based on C/I. The simulation uses
an iterative algorithm that models power control on both forward and reverse links. This iterative process ends when the
network is balanced, i.e., when the convergence criteria are satisfied.
Main simulation outputs are:
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The total forward link transmit power for each cell
The reverse link cell load for each cell
Note that numerous other parameters are available and stored during the simulation for further analysis. For more
information, see 10.5.5 Simulation Reports.
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CDMA2000 1xRTT Monte Carlo Simulation Algorithm
The figure below shows an overview of the power control algorithm for CDMA2000 1xRTT.
Figure 10.24 CDMA2000 1xRTT Monte Carlo simulation algorithm
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Initialisation: The network is initialised as “empty”: there is no mobile connected to any transmitter when starting
a simulation.
Best server determination: The best server is determined for each mobile using the Ec/Io criterion. The mobile is
rejected if the Ec/Io condition is not satisfied or the reverse link load factor is higher than the specified limit.
Active set determination: The active set is determined for each mobile.
FCH reverse link power control: The mobile FCH transmit power is calculated. It corresponds to the power required
to satisfy the FCH reverse link Eb/Nt requirement. The mobile is rejected if the calculated required transmit power
is higher than the maximum mobile output power allowed.
SCH reverse link power control: The mobile SCH transmit power is calculated. It corresponds to the power required
to satisfy the SCH reverse link Eb/Nt requirement. The SCH data rate is downgraded if the calculated required
transmit power is higher than the maximum mobile output power allowed. The downgrading is performed until the
link reaches its quality target knowing the mobile available output power. If the lowest data rate cannot be
provided, then no reverse SCH is allocated to the mobile.
FCH forward link power control: The transmitter FCH power is calculated. It corresponds to the power required to
satisfy the FCH forward link Eb/Nt requirement. “No handoff” and “handoff” situations are handled in different
ways. The mobile is rejected if the calculated traffic channel power is higher than the maximum traffic channel
power allowed.
SCH forward link power control: The transmitter SCH power is calculated. It corresponds to the power required to
satisfy the SCH forward link Eb/Nt requirement. “No handoff” and “handoff” situations are handled in different
ways. The SCH data rate is downgraded if the calculated traffic channel power is higher than the maximum traffic
channel power available. The downgrading is performed until the link reaches its quality target. If the lowest data
rate cannot be provided, then no forward SCH is allocated to the mobile.
Reverse link and forward link interference update: The reverse link load factor and total forward link transmit power
are updated with these results.
Congestion and radio resource control: FCH and SCH are not allocated if any of the following situations occur:
o Reverse link load factor higher than the specified limit
o Total forward link transmit power higher than the maximum total forward link transmit power
o Number of Walsh codes insufficient
o Number of channel elements available insufficient
The above calculations are carried out during each successive iteration until the simulation converges, i.e., both forward and
reverse link convergence criteria are satisfied.
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CDMA2000 1xEV-DO Monte Carlo Simulation Algorithm
The figure below shows an overview of the Monte Carlo simulation algorithm for CDMA2000 1xEV-DO.
Figure 10.25 CDMA2000 1xEV-DO Monte Carlo simulation algorithm
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Initialisation: The network is initialised as “empty”: there is no mobile connected to any transmitter when starting
each simulation. Step 1 to step 4 are repeated for each mobile of the generated user distribution.
Best server determination: The best server is determined for each mobile using the Ec/Io criterion. The mobile is
rejected if the Ec/Io condition is not satisfied or the reverse link load factor higher than the specified limit.
Active set determination: The active set is determined for each mobile.
Reverse link power control: The mobile transmit power is calculated. It corresponds to the power required to satisfy
the reverse link Eb/Nt requirement. The data rate is downgraded if the calculated required transmit power is higher
than the maximum mobile output power. The downgrading is performed until the link reaches its quality target
knowing the mobile available output power. If the lowest data rate cannot be provided, then the mobile is rejected.
Reverse link interference update: The reverse link load factor is updated with these results.
Forward link rate control: Ec/Nt (during pilot time slot) is calculated. Based on this value, the maximum offered rate
is derived for the mobile. Based on the number of mobiles connected and the Multi-User Gain functions, the total
throughput per transmitter is derived. In addition, the forward link actual rate per mobile is estimated.
The above calculations are carried out during each successive iteration until the simulation converges, i.e., both forward and
reverse link convergence criteria are satisfied.
10.5.3 Monte Carlo Simulation Management
CDMA2000 simulations are managed through the Simulations folder in the Atoll Explorer window. This folder is displayed in
the figure below.
Figure 10.26 CDMA2000 simulations folder
The Simulations folder is made up of several simulation “groups”. Each group corresponds to a network configuration for
which a user-specified number of Monte Carlo simulations have been generated. As an example, different groups may
correspond to different traffic assumptions.
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When several simulation groups are available, it is possible to automatically display one group after the other, hence
animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
The figure below shows the simulation creation dialog box. The following information is required when creating a new group
of Monte Carlo simulations:
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The simulation group name
The number of simulations to be run
The load constraints to apply during simulations
The traffic maps used
The convergence criteria.
Figure 10.27 CDMA2000 simulation creation dialog box
Once a simulation (or a group of simulations) has been performed, simulation reports are available and simulation results can
be graphically analysed in Atoll.
10.5.4 Simulation Graphical Analysis
Graphical Display: Mobile Connection Status
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for their connection status. The different possible statuses are:
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Connect DL + UL: the mobile is connected on both forward and reverse links
Connect UL: the mobile is connected on reverse link only
Connect DL: the mobile is connected on forward link only
Inactive: the mobile is inactive
Pmob>PmobMax: the mobile is rejected during reverse link power control as its required reverse link transmitter
power is higher than the maximum mobile transmit power
Ptch>PtchMax: the mobile is rejected during forward link power control as the required forward link traffic channel
power is higher than the maximum forward link traffic channel power
Admission Rejection: the mobile is rejected during best server determination as the reverse link cell load would be
higher than the maximum allowed
Load Saturation: the mobile is rejected during congestion and radio resource control as the reverse link cell load
would be higher than the maximum allowed
Channel Elements Saturation: the mobile is rejected during congestion and radio resource control as there are not
enough channel elements available
Cell Power Saturation: the mobile is rejected during congestion and radio resource control as the forward link total
power is higher than the maximum allowed
Code Saturation: the mobile is rejected during congestion and radio resource control as there are not enough Walsh
codes available
1xEV-DO Resource Saturation: the mobile is rejected as there are not enough EV-DO channel elements available,
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Ec/Io<(Ec/Io)min: the mobile is rejected during best server determination as the best server Ec/Io is less than the
minimum required.
An example of a graphical display of a group of simulations is presented in the figure below.
Figure 10.28 CDMA2000 simulation graphical display
Individual Mobile Result Graphical Display
Parameters for any user can be displayed either in the results table or directly on the map (as presented in the figure below).
Figure 10.29 Individual mobile results display using the tool tip
10.5.5 Simulation Reports
Atoll provides detailed simulation results in the form of reports.
Reports of a Single Simulation
A report is available for each simulation. This report contains information about the simulation statistics, and calculation
results by sites, cell, and mobile as given in the figure below.
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Figure 10.30 CDMA2000 simulation report
The simulation results are provided at the following different levels:
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Global statistics: total users attempting a connection and the corresponding break-up per service; total users
actually connected and the corresponding break-up per service.
Results per site: channel elements consumed (total and due to soft handoff) for both FCH and SCH and the
throughput allocated per service type. All these parameters are given for both forward and reverse links.
Results per cell (1xRTT): forward link transmit power related information (total power, load factor, percentage of
power used, average traffic channel power), reverse link mobile power related information (total noise, load factor,
noise rise, reuse factor), number of radio reverse links, percentage of areas in handoff (distinction made between
soft, softer and other handoff types), throughput allocated to forward and reverse links, number of mobile
rejections split per rejection reason. When relevant, split between FCH and SCH results is provided
Results per cell (1xEV-DO): forward link allocated throughput, reverse link mobile power related information (total
noise, load factor, noise rise, reuse factor), number of radio links for reverse and forward links, number of Walsh
codes used, percentage of areas in handoff (distinction made between soft, softer and other handoff types),
throughput allocated to forward and reverse links, number of mobile rejections split per rejection reason
Results per mobile (1xRTT): geographic location, terminal type, user type, mobility, connection status, carrier,
requested and allocated throughputs for both forward and reverse links, mobile total power, mobile FCH power,
mobile SCH power, best server, active set information
Results per mobile (1xRTT): geographic location, terminal type, user type, mobility, connection status, carrier,
reverse link requested and allocated throughputs, forward link maximum throughput, best server, active set
information
Initial conditions: parameters and traffic maps used to create the simulation.
An option is available to display more detailed results. This extra information includes for each mobile:
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The detailed parameters values for each member of the active set (noise values, interference values, etc.),
The shadowing loss values for each path from a mobile to its first 10 potential servers.
Reports of a Group of Simulations
Atoll provides detailed simulation results averaged over a group of simulations in the form of reports. The report generated
for a simulation group contains:
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Statistics: average statistics obtained from the results of all the simulations in a group
Results per site: average site results obtained from the results of all the simulations in a group
Results per cell: average cell results obtained from the results of all the simulations in a group
Initial conditions: parameters used to create the simulation group.
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Figure 10.31 CDMA2000 simulation group report
10.5.6 Updating Cell Loads
You can store the cell loads calculated by Monte Carlo simulations in the cells data table. This enables you to update the
network cell loads based either on the average results from a simulation group or the results of from a single simulation. Cell
load values for all the cells in the network radio database are then updated with the results generated by the selected
simulation. Cell loads from a simulation, simulation group, or from the cells data table can then be used to generate coverage
prediction plots.
10.5.7 Exporting Results
You can export the simulation results as described in 2.5.1 Network Data Import and Export.
CDMA2000 Coverage Predictions
In Atoll a coverage prediction is a plot displaying calculation results of user-selected parameters on the map and enabling
graphical as well as statistical analysis of the network behaviour. Examples of CDMA2000 coverage predictions are Ec/Io plots,
handoff plots, etc. For each pixel, Atoll calculates the required information. This data is then graphically represented by a
colour according to a user-defined legend. Different display options are available in Atoll, depending on the calculated
parameter.
10.6.1 Coverage Prediction Calculation and Management
Coverage predictions are performed by assuming a “probe mobile” (non-interfering terminal) on each pixel of the considered
area. The probe mobile characteristics (terminal type, mobility type, service type) are specified as inputs to the coverage
prediction in order to calculate the user-defined prediction parameter.
Predictions are stored as multi-layer geographic objects in the Predictions folder of the Explorer window and can be displayed
in the map window. When several coverage predictions are available, it is possible to automatically display one prediction
after the other, hence animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
Subfolders can be created in the Predictions folder in order to group various coverage prediction objects into categories.
Coverage predictions can be directly created under a subfolder and moved from one subfolder to another using the mouse.
10.6.2 Coverage Prediction Types
CDMA2000 coverage predictions can be generated either based on the results from Monte Carlo simulations or on userdefined cell load configurations.
CDMA2000 coverage prediction types and their display options available in Atoll are listed below.
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Coverage by transmitter (DL)
o Transmitter
Coverage by signal level (DL)
o Pilot and maximum signal level (dBm, dBµV or dBµV/m)
o Path loss (dB)
Overlapping zones (DL)
o Number of servers
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Total noise level analysis (DL)
o Minimum, average, and maximum noise level
o Minimum, average, and maximum noise rise
Pilot quality analysis (DL)
o Ec/Io
o Ec/Io margin
o Ec
o Quality indicator
o Reliability level
Service area analysis (Eb/Nt) (DL)
o Eb/Nt margin
o Effective Eb/Nt
o Maximum Eb/Nt
o Required power
o Required power margin
o Quality indicator
o Reliability level
o Throughput
Service area analysis (Eb/Nt) (UL)
o Eb/Nt margin
o Effective Eb/Nt
o Maximum Eb/Nt
o Required power
o Required power margin
o Soft handoff gain
o Quality indicator
o Reliability level
o Throughput
Effective service area analysis (Eb/Nt) (DL+UL)
o Reliability Level
Handoff zones (DL)
o Number of potential active transmitters
Pilot pollution analysis (DL)
o Number of polluters
PN offset collision zones (DL)
o Number of interferers
o Number of interferers per transmitter
Inter-technology interference level analysis (DL)
o Noise level
o Noise rise
The first three coverage predictions (coverage by transmitter, coverage by signal level, and overlapping zones) are not based
on interference, hence neither require cell load information nor Monte Carlo simulations. The remaining coverage predictions
depend on the network’s behaviour under load. These predictions can be calculated for a service, mobility type, and user
terminal equipment.
Various CDMA2000 coverage prediction plots are shown in the figures below.
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Figure 10.32 CDMA2000 coverage by transmitter
Figure 10.33 CDMA2000 coverage by pilot Ec/Io
Figure 10.34 CDMA2000 effective service area coverage prediction
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Figure 10.35 CDMA2000 pilot pollution coverage prediction
Figure 10.36 CDMA2000 handoff status coverage prediction
Figure 10.37 CDMA2000 coverage by number of potential servers for handoff
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Figure 10.38 CDMA2000 coverage by forward link total noise
Figure 10.39 CDMA2000 1xEV-DO coverage by throughput
Figure 10.40 CDMA2000 1xEV-DO coverage by reverse link Eb/Nt
10.6.3 Coverage Prediction Reports
Atoll can generate reports for one or more coverage predictions with various detail levels as defined by the user. Reports are
spread sheet-like tables that can be printed directly from Atoll or exported to any desktop tool. An example of such a report
is given in the figure below.
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Figure 10.41 CDMA2000 coverage prediction report
10.6.4 Coverage Prediction Comparison
Comparison (difference, intersection, union, or merge) between two coverage predictions can be performed. As examples,
this functionality can be used:
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To compare forward and reverse link coverage of a service. This enables you to determine forward/reverse linklimited zones for that service.
To compare service area coverage plots of two different services. This enables you to assess the areas where one
service (e.g., Mobile Internet Access) is available while the other (e.g., Video Conferencing) is not.
To compare service area coverage plots of two networks deployment scenarios (possibly with different
technologies). The figure below illustrates such a case by comparing CDMA2000 and LTE coverage. Note that, in
this example, LTE transmitters are installed on only some of the CDMA2000 sites.
Figure 10.42 Coverage prediction graphical comparison (CDMA2000 versus LTE example)
Atoll also enables you to carry out per-pixel arithmetical operations between coverage predictions. For example, you can
calculate the sum, difference, min, max, and average of similar calculated parameters per pixel from two coverage predictions
of the same or different technologies.
10.6.5 Coverage Prediction Export
Any coverage prediction can be exported in the following formats:
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Atoll format
ArcView SHP
MapInfo MIF and TAB
ArcView Grid TXT and ASC
Vertical Mapper GRD and GRC
BMP
PNG
TIFF
BIL
JPEG2000
JPEG
When exported in MapInfo format, coverage prediction attributes (e.g., signal levels, transmitter IDs, etc.) are exported along
with the plot. The figure below gives an example of the exported attributes for a downlink Eb/Nt prediction.
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Figure 10.43 CDMA2000 coverage prediction attributes export to MapInfo
10.6.6 Point Analysis Tool
A real-time prediction analysis tool is available in Atoll. The point analysis tool is dynamically linked to the map window. The
displayed information is updated as the receiver is moved on the map window. The point analysis tool provides the forward
link signal values numerically and graphically for all cells and for the selected terminal type, mobility type, and service type.
The figure below shows the point analysis window as well as its link to the map window.
Real-time active set links
display
Pilot Ec/Io information
Active set analysis window
Analysis parameters
Figure 10.44 CDMA2000 point-to-point real-time analysis
10.6.7 Multi-Point Analysis
Atoll enables you to carry out point predictions on multiple point locations and at different heights. Multi-point analyses can
be carried out on imported lists of points, subscriber locations from fixed subscriber traffic maps, as well as points created
on the map using the mouse.
Multi-point analyses may be useful in verifying network QoS at specific locations in case of reported incidents such as call
drops, low throughputs, etc. Multi-point analysis calculations can be based on user-defined network load conditions in the
Cells table or loads calculated using Monte Carlo simulations. The figure below shows the multi-point analysis creation dialog
box.
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Figure 10.45 CDMA multi-point analysis creation dialog box
Multi-point analysis results include a number of radio parameters at each point calculated for all potential servers. The results
provided by this analysis are the same as available for one point in the Details view of the Point Analysis tool. Multi-point
analysis results are stored in the Multi-Point Analysis folder in the Network explorer. Once calculated, multi-point analysis
results are available in tabular form and visible on the map using symbols and colours based on calculation results.
Figure 10.46 CDMA multi-point analysis results
You can export the multi-point analysis results as described in 2.5.1 Network Data Import and Export.
CDMA2000 Neighbour Planning
Atoll supports the following neighbour types in a CDMA2000 network configuration:
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Intra-technology neighbours: CDMA2000 cells defined as neighbours of other CDMA2000cells in the same Atoll
document. Intra-technology neighbours can be divided into:
o Intra-carrier neighbours: CDMA2000cells defined as neighbours to which a call is handed over using the
same carrier.
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o
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Inter-carrier neighbours: CDMA2000cells defined as neighbours to which a call is handed over using a
different carrier.
Inter-technology neighbours: CDMA2000cells defined as neighbours of cells which use a technology other than
CDMA2000.
Neighbour plans can be generated by any of the following means in Atoll:
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Importing an external neighbour plan (e.g., in Excel format)
Automatically producing a neighbour plan as described in 10.7.1 Automatic Neighbour Allocation
Graphically and/or manually creating, editing and deleting a neighbour plan as presented in 10.7.2 Graphical
Neighbour Plan Editing
Various neighbour plans can be compared. The results of an automatic neighbour allocation can be compared with the
existing neighbour plan. As well, neighbour plans from external sources can also be compared with the existing neighbour
plan in Atoll.
10.7.1 Automatic Neighbour Allocation
Neighbour lists can be generated automatically in Atoll. For each cell, potential neighbours are ranked according to their
importance. The neighbour planning algorithm considers the following user-specified parameters:
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Minimum received pilot signal strength
Minimum pilot Ec/Io
T_Drop margin
Maximum inter-site distance
Maximum number of neighbours
Minimum area covered (overlapping area between the studied cell and its potential neighbour)
Importance ranges for distance, coverage, adjacency, and co-site factors
Forcing “neighbour symmetry”, “adjacent cells as neighbour”, “co-site cells as neighbours“ and/or “exceptional neighbour
pairs” is possible with Atoll. Inter-carrier neighbour allocation can be carried out for user-defined source and destination
carrier numbers. The figure below displays the automatic neighbour allocation dialog box.
Figure 10.47 CDMA2000 automatic neighbour list generation
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10.7.2 Graphical Neighbour Plan Editing
Neighbour plan can be graphically edited in Atoll. Clicking a transmitter on the map displays all its neighbour relations. All
types of neighbour relations (outwards, inwards or symmetrical) can be created, edited and/or deleted graphically. Such an
example is presented in the figures below.
Figure 10.48 Graphical neighbour plan editing
Figure 10.49 Neighbour planning using a best server plot
10.7.3 Neighbour Consistency Check Tool
A neighbour relation audit is available in Atoll. This function enables you to determine inconsistencies in the current
neighbour plan. The figure below shows the neighbour relation conditions that can be verified using the audit.
Figure 10.50 Neighbour audit
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CDMA2000 PN Offset Planning
PN offset plans can be generated by any of the following means in Atoll:
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Importing an external PN offset plan (e.g., in Excel format),
Manually creating, editing and/or deleting a PN offset plan,
Automatically producing a PN offset plan as described in 8.8.1 Automatic PN Offset Planning Tool
Once created, PN offset plan consistency can be verified in Atoll.
10.8.1 Automatic PN Offset Planning Tool
Atoll’s automatic PN offset planning tool is based on a cost-based algorithm. The cost function takes into account several
criteria. The following constraints are applied when running the automatic planning algorithm:
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Domain constraint: required to distinguish different zones
Groups: it is possible to define scrambling code groups
Exceptional pairs: it is possible to define cell pairs that cannot have the same scrambling code
Reuse distance: a minimum reuse distance is defined (globally or per cell)
Additional constraints such as minimum Ec/Io
Three PN offset allocation strategies are available:
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PN offset per cell: The purpose of this strategy is to reduce the spectrum of allocated PN offsets.
Adjacent PN-clusters per site: This strategy consists in allocating one cluster of adjacent PN offsets to each base
station and one PN offset of the cluster to each cell of each transmitter according to its azimuth.
Distributed PN-clusters per site: This strategy consists in allocating one cluster of PN offsets to each base station
and one PN offset of the cluster to each cell of each transmitter according to its azimuth.
Atoll facilitates the management of PN offsets by letting you create groups of PN offsets and domains, where each domain is
a defined set of groups. PN offset domains can then be assigned to cells in order to provide a list of possible PN offsets for
each cell.
The figures below present the automatic PN offset allocation tool and an example of a PN offset allocation.
Figure 10.51 Automatic PN offset planning
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Figure 10.52 PN offset display on map
Atoll can also display the PN offset code distribution as a histogram. An example is shown below.
Figure 10.53 PN offset distribution histogram
10.8.2 PN Offset Consistency Check Tool
A PN offset consistency check tool is available in Atoll. This function enables you to detect any inconsistency due to potential
manual changes. The figure below shows the conditions that can be verified using the audit.
Figure 10.54 PN offset audit
10.8.3 PN offset interference analysis
The point analysis tool enables analysing PN offset interference. You can study the received pilot Ec/Io and find interfering
cells using this tool.
Figure 10.55 PN offset interference analysis
CDMA2000 Automatic Cell Planning
The Atoll CDMA2000 ACP (Automatic Cell Planning) module enables you to automatically determine the best CDMA2000
parameter settings for your network. The aim of the Atoll ACP is to improve network quality in terms of both coverage and
capacity. For a comprehensive description of the Atoll ACP, see 17 Automatic Cell Planning (ACP) Features.
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.
The Atoll CDMA2000 ACP is capable of optimising network parameters (antenna types, heights, azimuths, tilts, transmission
powers, etc.) based on the following CDMA2000 quality indicators:
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Signal level
Ec/Io
Overlap
Best server distance
1st-Nth difference
CDMA2000 Co-planning Features
Atoll supports co-planning of CDMA2000 networks with other radio access technologies. For more information, see 11 MultiRAT Features.
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11 Multi-RAT Features
Atoll supports single-RAT as well as multi-RAT network planning (co-planning). Atoll includes advanced multi-technology
network planning and optimisation features for all supported radio access technologies. These features include:
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Site sharing
Antenna sharing
Simultaneous display and analysis of all technologies in multi-RAT networks
Inter-RAT handover-based neighbour planning
Inter-RAT interference analysis
Atoll includes integrated network planning for GSM/UMTS/LTE/NB-IoT and CDMA2000/LTE/NB-IoT radio access technologies.
In addition to the above features, the 3GPP Multi-RAT and 3GPP2 Multi-RAT project types include:

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Multi-technology network database
Unified traffic model with multi-technology services and users
Combined GSM/UMTS/LTE/NB-IoT and CDMA2000/LTE/NB-IoT Monte Carlo simulators
Moreover, Atoll also supports the latest advances in wireless technologies such as mobile traffic offloading to Wi-Fi and LTE
small cells (HetNets). Atoll’s multi-technology Monte Carlo simulations can integrate Wi-Fi networks deployed on top of
mobile technology networks in order to provide operators with the means to evaluate a strategy for enhancing network
capacity.
This chapter focuses on the multi-technology planning and optimisation features offered by Atoll. For information on a
technology-specific parameter, see the chapter related to that particular technology.
Multi-RAT Network Model
Atoll’s multi-RAT network model is based on a single multi-technology network database combining different technologies,
such as GSM, UMTS, LTE, and NB-IoT or CDMA2000, LTE, and NB-IoT.
The 3GPP Multi-RAT project template provides you with the possibility to create single-RAT (GSM, UMTS, or LTE) and multiRAT projects including any or all of the 3GPP technologies (GSM, UMTS, LTE, NB-IoT). The 3GPP2 Multi-RAT project template
provides you with the possibility to create single-RAT (CDMA2000 or LTE) and multi-RAT projects including any or all of the
3GPP technologies (CDMA2000, LTE, NB-IoT). This is shown in the figure below.
Projects created using the 3GPP multi-RAT and 3GPP2 multi-RAT project templates include integrated multi-technology
databases in a single Atoll document (ATL file).
Figure 11.1 Creation of 3GPP and 3GPP2 multi-RAT documents
A 3GPP multi-RAT project contains shared sites and antennas databases with GSM, UMTS, LTE, and NB-IoT-related network
elements such as transmitters, cells, repeaters, etc. A 3GPP2 multi-RAT project contains shared sites and antennas databases
with CDMA2000, LTE, and NB-IoT-related network elements such as transmitters, cells, repeaters, etc. Technology-specific
network data are organised as separate layers in the explorer window. The figure below gives an example of the explorer
window in a 3GPP multi-RAT project.
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Figure 11.2 Network explorer with multi-RAT network elements in folders
The figure below gives an example of the map window with different technology sectors.
Figure 11.3 Multi-RAT network display on map
In addition to the above, Atoll also provides the possibility to plan and optimise any two single-technology networks together.
Single-RAT Atoll projects can be linked together for carrying out planning and optimisation tasks that depend on interactions
between different technologies. In such an environment, the network databases exist as separate single-RAT databases,
however Atoll provides a fully integrated working environment to the user. Any change in one project is reflected in the other.
The figures below give an example of two single-RAT projects linked together for co-planning and optimisation.
Figure 11.4 Network explorer with LTE/Wi-Fi data
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Figure 11.5 LTE/Wi-Fi co-planning network display on map
For more information on technology-specific network data, see the corresponding chapter.
Multi-RAT Network Configuration Parameters
The parameters explorer contains technology-specific network configuration parameters in folders corresponding to each
technology, as shows in the figure below.
Figure 11.6 Technology Related Parameters
For more information on technology-specific network configuration parameters, see the corresponding chapter.
Multi-RAT Radio Equipment
The parameters explorer contains multi-technology as well as technology-specific radio equipment. For more information on
common antenna and radio equipment features, see 4 Antenna and Radio Equipment Features. For more information on
technology-specific radio equipment, see the corresponding chapter.
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Multi-RAT Traffic Model (Multi-technology Services and Users)
In Atoll, the radio network traffic is modelled using Monte Carlo simulations. According to the definition of the services and
users in the network, and depending on the traffic cartography (traffic data), realistic distributions of users are generated and
used as input to the scheduling and radio resource management algorithms.
Service and user behaviours are modelled in Atoll through different tables that provide information about:
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The services available in the network
The terminals compatible with the network
The mobility types
The user profiles describing the way users access different services
The unified multi-technology traffic model is shown in the figure below.
Figure 11.7 Multi-RAT traffic model
11.4.1 Services
The services table describes the services that are available in the network. Both voice and data type services are supported
and have specific parameters. A service can be offered by one or more technologies in a multi-RAT network. For each service,
you can set access priorities of different technologies in a multi-RAT network.
The service parameters are:
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Technology priorities
Activity factors on uplink and downlink,
Average requested throughput on uplink and downlink
Technology-specific parameters (described in the corresponding chapter for each technology)
An example of a service properties window is presented in the figure below.
Figure 11.8 Service properties windows
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11.4.2 Terminals
The terminals table describes the terminals that can be used in the network, cell phones, smartphones, in-car navigation
devices, etc. A terminal can be compatible with one or more technologies in a multi-RAT network. For each terminal, you can
define compatibility with different technologies in a multi-RAT network.
An example of a terminal properties window is given in the figure below.
Figure 11.9 Terminal properties window
11.4.3 Mobility Types
The mobility type defines different user speeds and, in some cases, receiver sensitivities.
11.4.4 User Profiles
The user profiles table models the behaviour of the different user categories. Every user profile contains a list of services and
their associated parameters describing how these services are accessed by the users.
Parameters for voice services are:
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
The average number of calls per hour
The average duration of each call
The terminal used when requiring access to this service.
Parameters for data services are:
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The average number of sessions per hour
The data volume transferred on the downlink during each session
The data volume transferred on the uplink during each session
The terminal used when requiring access to this service.
The figure below shows a user profile window.
Figure 11.10 User profile window
11.4.5 Traffic Data
For information on traffic data cartography, see 2.2.7 Traffic Data.
Multi-RAT Monte Carlo Simulations
Multi-RAT Monte Carlo simulations combine GSM/UMTS/LTE/NB-IoT, CDMA2000/LTE/NB-IoT, and optionally Wi-Fi Monte
Carlo simulations to provide integrated multi-technology traffic and capacity analysis results. Atoll’s consolidated multitechnology radio resource management and scheduling algorithms perform traffic spreading and balancing between different
technologies of a multi-RAT network. Atoll takes into account the user-defined service-level technology priorities and
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terminal-level compatibilities to distribute mobiles among different technologies covering a given traffic. Next, Atoll
calculates, for each user distribution (called a random trial), the different network parameters such as the mobile activity,
received signal levels and signal quality, required radio resources, and user throughputs. As outputs, Atoll provides the traffic
loads which can then be assigned to the different cells and the C/(I+N) coverage can be performed based on realistic
simulation results.
Multi-RAT Monte Carlo simulations can be analysed, displayed and stored. They can be used in a next step to generate
numerous coverage predictions. The figure below presents a multi-RAT simulation scenario including GSM, UMTS, LTE, NBIoT, and Wi-Fi technologies in the same network.
Figure 11.11 Multi-RAT Monte Carlo simulation results (Wi-Fi  LTE  UMTS  GSM)
For more information on technology-specific Monte Carlo simulations, see the corresponding chapter. For more information
on mobile traffic offloading to Wi-Fi, see 14.6.7 Wi-Fi Co-planning With Mobile Radio Access Technologies.
11.5.1 Definition
A Monte Carlo simulation in Atoll corresponds to a given distribution of users. It is a snapshot of a multi-RAT network.
11.5.2 Generation of Realistic User Distributions
Realistic distributions of users on the map are required as inputs to the multi-RAT simulation algorithm. A “Realistic User
Distribution” corresponds to a user distribution that complies with the service and user model and the traffic data. Atoll
generates these user distributions using a Monte Carlo (statistical) algorithm.
11.5.3 Scheduling and Radio Resource Management
For each user distribution, Atoll simulates the scheduling and RRM mechanisms. The simulation ends when the scheduler has
allocated resources to all the users selected for the scheduling process and has determined the traffic loads for all the cells
in the simulation.
For more information on technology-specific Monte Carlo simulation algorithms, see the corresponding chapter.
11.5.4 Monte Carlo Simulation Management
Multi-RAT simulation scenarios are managed through the Simulations folder in the Atoll Explorer window. This folder is
displayed in the figure below.
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Figure 11.12 Simulations folder
The Simulations folder is made up of several simulation “groups”. Each group corresponds to a network configuration for
which a user-specified number of Monte Carlo simulations have been generated. As an example, different groups may
correspond to different traffic assumptions. Each group contains results for all the technologies in the multi-RAT network.
When several simulation groups are available, it is possible to automatically display one group after the other, hence
animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
The following information is required when creating a new group of Monte Carlo simulations:
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The simulation group name,
The number of simulations to be run
The traffic maps used
Technology-specific load constraints and convergence criteria
The figure below shows the simulation creation dialog boxes.
Figure 11.13 Multi-RAT simulation creation dialog boxes
Once a simulation (or a group of simulations) has been performed, simulation reports are available and simulation results can
be graphically analysed in Atoll.
11.5.5 Simulation Graphical Analysis
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours based on:

Activity status
o Active DL + UL: the mobile is active on both downlink and uplink
o Active UL: the mobile is active on uplink only
o Active DL: the mobile is active on downlink only
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Throughput
Connection status
o Connected DL + UL: the mobile is connected on both downlink and uplink
o Connected UL: the mobile is connected on uplink only
o Connected DL: the mobile is connected on downlink only
o Scheduler Saturation: the mobile is rejected because the scheduler has reached its maximum limit
o Resource Saturation: the mobile is rejected because all the resources have been allocated to other
mobiles
o No Service: the mobile is rejected because it is outside the coverage area
An example of a graphical display of multi-RAT simulations is presented in the figure below.
Figure 11.14 Multi-RAT simulation results display on map
Individual Mobile Result Graphical Display
Parameters for any user can be displayed either in the results table or directly on the map (as presented in the figure below).
Figure 11.15 Individual mobile results display using the tool tip
11.5.6 Simulation Reports
Atoll provides detailed simulation results in the form of reports.
Reports of a Single Simulation
A report is available for each simulation. This report contains information about the simulation statistics, and calculation
results by sites, cell, and mobile as given in the figure below.
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Figure 11.16 Multi-RAT simulation report for LTE cells and mobiles
The simulation results are provided at the following different levels: global, per site, per cell, per mobile, initial conditions.
Reports of a Group of Simulations
Atoll provides detailed simulation results averaged over a group of simulations in the form of reports. The report generated
for a simulation group contains:
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Statistics: average statistics obtained from the results of all the simulations in a group
Results per site: average site results obtained from the results of all the simulations in a group
Results per cell: average cell results obtained from the results of all the simulations in a group
Initial conditions: parameters used to create the simulation group.
Figure 11.17 Multi-RAT simulation group report for LTE cells
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11.5.7 Updating Cell Loads
You can store the cell loads calculated by Monte Carlo simulations in the cells data table. This enables you to update the
network cell loads based either on the average results from a simulation group or the results of from a single simulation. Cell
load values for all the cells in the network radio database are then updated with the results generated by the selected
simulation. Cell loads from a simulation, simulation group, or from the cells data table can then be used to generate coverage
prediction plots.
11.5.8 Exporting Results
You can export the simulation results as described in 2.5.1 Network Data Import and Export.
Multi-RAT Coverage Predictions
In Atoll a coverage prediction is a plot displaying calculation results of user-selected parameters on the map and enabling
graphical as well as statistical analysis of the network behaviour. Examples of coverage predictions are signal level, signal
quality, throughput plots, etc. For each pixel, Atoll calculates the required information. This data is then graphically
represented by a colour according to a user-defined legend. Different display options are available in Atoll, depending on the
calculated parameter.
11.6.1 Coverage Prediction Calculation and Management
Coverage predictions are performed by assuming a “probe mobile” (non-interfering terminal) on each pixel of the considered
area. The probe mobile characteristics (terminal type, mobility type, service type) are specified as inputs to the coverage
prediction in order to calculate the user-defined prediction parameter.
Predictions are stored as multi-layer geographic objects in the Predictions folder of the Explorer window and can be displayed
in the map window. When several coverage predictions are available, it is possible to automatically display one prediction
after the other, hence animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
Subfolders can be created in the Predictions folder in order to group various coverage prediction objects into categories.
Coverage predictions can be directly created under a subfolder and moved from one subfolder to another using the mouse.
11.6.2 Coverage Prediction Types
Multi-RAT coverage prediction types and their display options available in Atoll are listed below.

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All single-RAT coverage predictions
For information on technology-specific coverage predictions, see the corresponding chapter.
Effective service area analysis (DL+UL)
o Available technologies
Coverage by throughput (DL)
o Effective RLC throughput
o Application throughput
11.6.3 Coverage Prediction Reports
Atoll can generate reports for one or more coverage predictions with various detail levels as defined by the user. Reports are
spread sheet-like tables that can be printed directly from Atoll or exported to any desktop tool. An example of such a report
is given in the figure below.
Figure 11.18 Coverage prediction report
11.6.4 Coverage Prediction Comparison
Comparison (difference, intersection, union, or merge) between two coverage predictions can be performed. For example,
coverages of different technologies can be compared on a pixel-by-pixel basis (e.g. CDMA2000 voice coverage plot vs. LTE
voice coverage plot) as shows in the figure below.
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Figure 11.19 Coverage prediction graphical comparison
Atoll also enables you to carry out per-pixel arithmetical operations between coverage predictions. For example, you can
calculate the sum, difference, min, max, and average of similar calculated parameters per pixel from two coverage predictions
of the same or different technologies.
11.6.5 Coverage Prediction Export
Any coverage prediction can be exported in the following formats:
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Atoll format
ArcView SHP
MapInfo MIF and TAB
ArcView Grid TXT and ASC
Vertical Mapper GRD and GRC
BMP
PNG
TIFF
BIL
JPEG2000
JPEG
When exported in MapInfo format, coverage prediction attributes (e.g., signal levels, transmitter IDs, etc.) are exported along
with the plot. The figure below gives an example of the exported attributes for a prediction.
Figure 11.20 Coverage prediction attributes export to MapInfo
11.6.6 Point Analysis Tool
For information on technology-specific point analysis, see the corresponding chapter.
11.6.7 Multi-Point Analysis
Atoll enables you to carry out multi-technology point predictions on multiple point locations and at different heights. Multipoint analyses can be carried out on imported lists of points as well as points created on the map using the mouse.
Multi-point analyses may be useful in verifying network QoS at specific locations in case of reported incidents such as call
drops, low throughputs, etc. Multi-point analysis calculations can be based on user-defined network load conditions in the
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Cells tables or loads calculated using Monte Carlo simulations. The figure below shows the multi-point analysis creation dialog
box.
Figure 11.21 Multi-point analysis creation dialog box
Multi-point analysis results include a number of radio parameters at each point calculated for all potential servers. The results
provided by this analysis are the same as available for one point in the Details views of the Point Analysis tools. Multi-point
analysis results are stored in the Multi-Point Analysis folder in the Network explorer. Once calculated, multi-point analysis
results are available in tabular form and visible on the map using symbols and colours based on calculation results.
Figure 11.22 Multi-point analysis results
You can export the multi-point analysis results as described in 2.5.1 Network Data Import and Export.
Multi-RAT Inter-technology Neighbour Planning
Inter-technology neighbours (LTE neighbours of UMTS cells, etc.) can be generated by any of the following means in Atoll:
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Importing an external neighbour plan (e.g., in Excel format)
Automatically producing a neighbour plan as described in 11.7.1 Automatic Inter-technology Neighbour Allocation
Graphically and/or manually creating, editing and deleting a neighbour plan as presented in 11.7.2 Graphical
Neighbour Plan Editing
Various neighbour plans can be compared. The results of an automatic neighbour allocation can be compared with the
existing neighbour plan. As well, neighbour plans from external sources can also be compared with the existing neighbour
plan in Atoll.
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11.7.1 Automatic Inter-technology Neighbour Allocation
Inter-technology neighbour lists can be generated automatically in Atoll. For each cell, potential neighbours are ranked
according to their importance. The neighbour planning algorithm considers the following user-specified parameters:
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Technology-specific radio criteria (hysteresis, signal level, Ec/Io, margin, etc.)
Maximum inter-site distance
Maximum number of neighbours
Minimum area covered (overlapping area between the reference cell and its potential neighbour).
Importance ranges for distance, coverage, adjacency, and co-site factors.
Forcing “co-site cells as neighbours” or “exceptional inter-technology neighbour pairs” is possible with Atoll. The figure below
displays the automatic inter-technology neighbour allocation dialog box.
Figure 11.23 Multi-RAT automatic neighbour list generation
11.7.2 Graphical Neighbour Plan Editing
Neighbour plan can be graphically edited in Atoll. Clicking a transmitter on the map displays all its neighbour relations. All
types of neighbour relations (outwards, inwards or symmetrical) can be created, edited and/or deleted graphically. Such an
example is presented in the figure below.
Figure 11.24 Graphical neighbour plan editing
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11.7.3 Neighbour Consistency Check Tool
A neighbour relation audit is available in Atoll. This function enables you to determine inconsistencies in the current
neighbour plan. The figure below shows the neighbour relation conditions that can be verified using the audit.
Figure 11.25 Multi-RAT neighbour audit
Multi-RAT Inter-technology Interference Analysis
In addition to the analysis of interference between network elements of the same technology, Atoll enables you to analyse
interference between co-located networks of different technologies. Atoll can take into account interference from co-existing
networks in Monte Carlo simulations and coverage predictions.
The following inter-technology interference scenarios are modelled in Atoll:
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
Interference received by mobiles on the downlink from other technology base stations and mobiles in the vicinity.
Interference received by cells on the uplink from other technology base stations and mobiles in the vicinity.
Figure 11.26 Interference received by mobiles on the downlink
Figure 11.27 Interference received by cells on the uplink
You can enter inter-technology interference reduction factor graphs in Atoll (as shown in the figure below) in order for Atoll
to automatically calculate interference from external base stations in the downlink. Furthermore, user-defined intertechnology noise rise values can be set for both downlink and uplink per cell.
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Figure 11.28 Inter-technology interference reduction factor graphs
Figure 11.29 Inter-technology interference analysis example
Multi-RAT Automatic Cell Planning
The Atoll ACP (Automatic Cell Planning) module enables you to automatically determine the best GSM/UMTS/LTE/NB-IoT and
CDMA2000/LTE/NB-IoT cell parameter settings for your multi-RAT network. The aim of the Atoll ACP is to improve network
quality in terms of both coverage and capacity. The ACP optimises all the technologies in a multi-RAT network simultaneously
and allows you to set the ACP optimisation objectives for each technology individually.
For a comprehensive description of the ACP, see 16
.
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12 TD-SCDMA Features
The Atoll TD-SCDMA module provides a comprehensive and accurate modelling of TD-SCDMA/HSDPA networks. It also
includes detailed modelling of the N-frequency mode, HSDPA, UpPCH shifting, and MBMS. Atoll TD-SCDMA also includes
comprehensive modelling of different smart antenna models including beamforming smart antennas.
Atoll provides the means to set up multi-service traffic maps from multiple sources: vector, raster and live traffic data. Traffic
maps are used in TD-SCDMA Monte Carlo simulations for network capacity analysis including dynamic channel allocation,
RRM, and carrier allocation. Coverage predictions can be calculated based on Monte Carlo simulation results or on live
network loads from the OAM in order to study coverage and capacity of the network.
In terms of HSDPA Atoll takes into account transport and physical channels, fast link adaptation, higher order modulation
schemes, and different modes of power allocation. HSDPA can be analysed as a separate layer or combined with R99 traffic,
thus estimating the impact of HSDPA users on R99 users and vice versa.
Atoll includes automatic multi-carrier neighbour planning features that allow analysing handovers in the network. Automatic
scrambling code planning can be performed using various allocation strategies, with analysis tools enabling auditing of
scrambling code allocations. Atoll’s inter-technology handover modelling features allow studying the co-existence of other
technology networks with TD-SCDMA.
An overview of the TD-SCDMA modelling in Atoll is shown in the figure below.
Figure 12.1 TD-SCDMA network modelling in Atoll
TD-SCDMA Network Model
The TD-SCDMA network model comprises radio network elements such as sites, transmitters, and cells. A TD-SCDMA NodeB is equivalent to a site, its transmitters with one or more radio channels (cells) each.
Figure 12.2 TD-SCDMA network model
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12.1.1 Sites
A site represents the physical location where Node-Bs can be installed. An example of a site properties window is shown in
the figure below.
Figure 12.3 Site properties window
Site parameters are:
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

Geographic coordinates
Altitude (user-defined or automatically extracted from the terrain elevation data)
Any user-defined flags and parameters such as address, owner, deployment phase, etc.
12.1.2 Transmitters
Transmitters in Atoll correspond to sectors and antennas installed at a site. The main transmitter parameters are:

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Transmitter name and the name of the site where it is installed
X and Y coordinates
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Smart antenna
Numbers of transmission and reception antenna ports for diversity
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other transmitters
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Tower mounted amplifier (TMA)
Feeder type and its transmission and reception lengths
Maximum coverage range
Any user-defined flags and parameters
An example of a transmitter properties window is shown in the figure below.
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Figure 12.4 TD-SCDMA transmitter properties window
12.1.3 Cells (R99, HSDPA, and HSUPA)
Atoll supports multi-band, multi-carrier TD-SCDMA networks. In Atoll, cells model the carriers used at a transmitter. A
transmitter can support different carriers. Each cell has its own radio resources and parameters, including:

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Cell name and the name of the transmitter to which the cell belongs
N-frequency mode support
Carrier number and type (master, slave, standalone)
Scrambling code, SC locked/unlocked, SC domain, and SC reuse distance
Transmission powers: maximum, P-CCPCH, other CCH, DwPCH
Minimum P-CCPCH RSCP
P-CCPCH RSCP T_Comp
Timeslot configuration and
Required downlink and uplink resource units
HSPA support: None, HSDPA, HSPA
HSDPA parameters: HSDPA, HS‐SCCH, and HS-SICH power allocation modes, available HSDPA and HS‐SCCH powers
per timeslot, power headroom, number of HS‐SCCH and HS-SICH channels, minimum and maximum numbers of
HS‐PDSCH codes per timeslot, maximum and actual numbers of HSDPA users, HSDPA scheduler algorithm
HSUPA parameters: Downlink EDCH power per timeslot and allocation mode, maximum and actual numbers of
HSUPA users
Neighbour parameters: maximum numbers of neighbours and neighbours lists
Timeslot parameters: timeslot type (R99, HSDPA, HSUPA), blocked or not, downlink traffic and control channel
powers, uplink load factor and reuse factor, maximum downlink load and uplink load factor, resource unit overhead,
available HSDPA power, minimum and maximum numbers of HS‐PDSCH codes, uplink load factor due to HSUPA,
angular distributions of uplink and downlink loads
Any user-defined flags and parameters
The figure below presents an example of a transmitter with two cells: one with carrier 0 and the other with carrier 1.
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Figure 12.5 TD-SCDMA cell parameters
12.1.4 Site Templates
A site template is made up of one or more transmitters and cells located on the same site. Site templates can be created and
edited as needed. Building a network is facilitated by working with site templates rather than single site/transmitter/cell. By
default some TD-SCDMA site templates are available for dense urban, urban, suburban, and rural environments.
12.1.5 Repeaters
A repeater receives, amplifies, and retransmits signals. Repeaters are used to extend the coverage of their donors. Atoll
models selective as well as non-selective RF repeaters, optic fibre repeaters, microwave repeaters, and remote antennas.
Selective RF repeaters only repeat signals from their donor transmitters whereas non-selective RF repeaters receive and
retransmit wanted signals as well as interference.
The main parameters of a repeater are:
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Donor transmitter name
X and Y coordinates
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other repeaters
Total gain
Amplifier gain
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Feeder type and its transmission and reception lengths
Any user-defined flags and parameters
The figure below presents the repeater properties window while the figure below that gives an example of a best server
prediction plot with a repeater.
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Figure 12.6 Repeater properties window
RF repeater
Donor transmitter
Figure 12.7 RF repeater coverage plot
TD-SCDMA Network Configuration Parameters
Atoll allows setting and modifying network-level configurations and parameters applicable to the entire project.
12.2.1 Frequency Bands and Carriers
Atoll enables you to model multi-band, multi-carrier TD-SCDMA networks. A frequency band is characterized by its operating
frequency and carriers. You can add, modify, and delete frequency bands in Atoll as required.
Atoll can also calculate inter-carrier interference based on inter-carrier interference IRFs.
12.2.2 Global Network Settings
TD-SCDMA- and HSPA-specific parameters that are applicable to the entire network are modelled in Atoll as global network
settings. These parameters include the downlink power calculation method, quality threshold type to use in calculations
(Eb/Nt or C/I), spreading rate, P-CCPCH processing gain, spreading factor, the interference calculation method, and HSDPA
interference method. The figure below presents the network level properties dialog box.
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Figure 12.8 TD-SCDMA network level parameters
12.2.3 Radio Bearers (R99, HSDPA, and HSUPA)
Radio bearers define the data transport format. Atoll manages R99, HSDPA, and HSUPA bearers. The R99 radio bearer
parameters are:
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Type
Nominal uplink and downlink rates
Uplink and downlink spreading factors
Uplink and downlink processing gains
Minimum and maximum downlink traffic channel powers
Uplink and downlink numbers of timeslots
An example of an R99 bearer properties window is presented in the figure below.
Figure 12.9 R99 radio bearer properties
The HSDPA radio bearer parameters are:
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Transport block size
Number of used HS-PDSCH channels per timeslot
RLC peat rate
Number of used timeslots
UE category
Highest supported modulation
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The HSUPA radio bearer parameters are:
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Transport block size
Number of used E-PUCH channels per timeslot
RLC peat rate
Number of used timeslots
UE category
Highest supported modulation
12.2.4 UE categories (HSDPA and HSUPA)
UE categories define the HSDPA and HSUPA capabilities of user equipment. The HSDPA UE category parameters include:
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Maximum number of HS-PDSCH channels per HSDPA timeslot
Maximum number of HS-PDSCH timeslots per TTI
Maximum transport block size
Highest supported modulation
The HSUPA UE category parameters are:
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Maximum number of E-PUCH channels per HSUPA timeslot
Maximum number of E-PUCH timeslots per TTI
Maximum transport block size
Highest supported modulation
TD-SCDMA Radio Equipment
Atoll provides the option to define various pieces of radio equipment such as antennas, transmitter equipment, feeders,
tower mounted amplifiers, reception equipment, smart antenna equipment, etc. For more information on common antenna
and radio equipment features, see 4 Antenna and Radio Equipment Features.
12.3.1 Site Equipment
Site equipment model the Node-B level parameters that are applicable to all the transmitters and cells located at a site. The
following parameters define the equipment for each site:
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Manufacturer name
JD factor
MCJD factor
12.3.2 Reception Equipment (R99, HSDPA, and HSUPA)
TD-SCDMA reception equipment model the reception characteristics of user terminals. R99, HSDPA, and HSUPA bearer
selection thresholds are defined in TD-SCDMA reception equipment. The figures below give examples of such an equipment
definition.
Figure 12.10 TD-SCDMA reception equipment – R99 bearer selection thresholds
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Figure 12.11 TD-SCDMA reception equipment – HSDPA bearer selection thresholds
Figure 12.12 TD-SCDMA reception equipment – HSUPA bearer selection thresholds
12.3.3 Smart Antenna Equipment
Atoll includes the following smart antenna models:
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Beam-switching smart antennas, also referred to as grid of beams (GOB)
A grid of beams is a list of antenna beams with different azimuths. Atoll selects the best suited beam from the GOB
for each served mobile. The best suited beam is the one which provides the highest gain in the direction of the
mobile.
Beamforming smart antennas
Beamforming smart antenna models support linear adaptive array systems that work by forming beams in the
direction of the served mobiles. The conventional beamformer performs beamforming in downlink and uplink. The
optimum beamformer performs beamforming in downlink, and beamforming and interference cancellation in the
uplink using an MMSE (Minimum Mean Square Error) algorithm. Smart antenna models dynamically calculate and
apply weights on each antenna element in order to create beams in the direction of served users. In uplink, the
Minimum Mean Square Error algorithm models the effect of null steering towards interfering mobiles.
Beam-steering smart antennas
3rd party smart antenna models
Grid of beams, optimum beamformer, conventional beamformer, adaptive beam, and third-party models require Monte
Carlo simulations to simulate the effect of the dynamic channel allocation (DCA) and power control. The results generated by
the Monte Carlo simulations can be used for calculating coverage predictions.
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Figure 12.13 Grid of beams smart antenna properties
Figure 12.14 Beamforming smart antenna properties
Smart antenna equipment models adaptive antenna array systems with more than one antenna element. The beamforming
smart antenna model also supports cross-polar diversity. Smart antenna gains can be fine-tuned with user-defined gain
offsets per clutter class.
The figure below shows smart antenna calculation results, i.e., the angular distribution of interference, output by Atoll’s
Monte Carlo simulations.
Figure 12.15 Angular distribution of uplink and downlink loads per timeslot from smart antennas
TD-SCDMA Traffic Model
In Atoll, the radio network traffic is modelled using Monte Carlo simulations. According to the definition of the services and
users in the network, and depending on the traffic cartography (traffic data), realistic distributions of users are generated and
used as input to the power control and radio resource management algorithms.
Service and user behaviours are modelled in Atoll through different tables that provide information about:
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The services available in the network
The terminals compatible with the network
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The mobility types
The user profiles describing the way users access different services
The TD-SCDMA traffic model is shown in the figure below.
Figure 12.16 TD-SCDMA traffic model
12.4.1 Services
The services table describes the services that are available in the network. Various types of services (circuit, packet, etc.) are
supported and have specific parameters. The main service parameters are:
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R99 radio bearer
Type (circuit R99, packet R99, packet HSDPA, packet HSPA)
Preferred carriers
Priority level
Uplink and downlink activity factors (for circuit services)
Uplink and downlink efficiency factors (for packet services, the percentage of data volume increase due to
retransmissions)
Packet session parameters (packet sizes, packet call durations, etc.)
Body loss
An example of the service properties window is presented in the figure below.
Figure 12.17 Service properties window
12.4.2 Terminals
The terminals table describes the terminals that can be used in the network, cell phones, smartphones, in-car navigation
devices, etc. The following parameters model a terminal:
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Number of supported carriers
Minimum, maximum, UpPCH, and HS-SICH transmission powers
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Noise figures
JD factor
Rho factor
Transmission and reception losses
Reception equipment
HSPA UE categories
An example of a terminal properties window is given in the figure below.
Figure 12.18 Terminal properties window
12.4.3 Mobility Types
The mobility type defines the minimum required signal level and quality for different user speeds. The following parameters
model a mobility type:
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User speed
P-CCPCH RSCP T_Add
P-CCPCH RSCP T_Drop
P-CCPCH Ec/Nt threshold
DwPCH RSCP threshold
DwPCH C/I threshold
UpPCH RSCP threshold
HS-SCCH Ec/Nt threshold
HS-SICH Ec/Nt threshold
E-DCH Ec/Nt threshold
An example of a mobility type properties window is given in the figure below.
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Figure 12.19 Mobility type properties window
12.4.4 User Profiles
The user profiles table models the behaviour of the different user categories. Every user profile contains a list of services and
their associated parameters describing how these services are accessed by the users.
Parameters for circuit-switched services are:
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The average number of calls per hour
The average duration of each call
The terminal used when requiring access to this service
Parameters for packet-switched services are:
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The average number of sessions per hour
The data volume transferred on the downlink during each session
The data volume transferred on the uplink during each session
The terminal used when requiring access to this service
The figure below shows a user profile window.
Figure 12.20 User profile window
12.4.5 Traffic Data
For information on traffic data cartography, see 2.2.7 Traffic Data.
TD-SCDMA Monte Carlo Simulations
A TD-SCDMA network automatically regulates power and resource allocation on both uplink and downlink with the objective
of minimising interference and maximising network capacity. Using dynamic channel allocation (DCA), a TD-SCDMA network
allocates resources to users accessing different services. HSPA networks perform fast link adaptation for HSDPA users. Atoll
simulates TD-SCDMA/HSPA network regulation mechanisms by calculating, for each user distribution (called a random trial),
different network parameters.
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A Monte Carlo simulation in Atoll corresponds to a given distribution of users. It is a snapshot of a TD-SCDMA network.
TD-SCDMA Monte Carlo simulations can be analysed, displayed and stored. They can be used in a next step to generate
numerous coverage predictions.
12.5.1 Generation of Realistic User Distributions
Realistic distributions of users on the map are required as inputs to the TD-SCDMA simulation algorithm. A “Realistic User
Distribution” corresponds to a user distribution that complies with the service and user model and the traffic data. Atoll
generates these user distributions using a Monte Carlo (statistical) algorithm.
12.5.2 Power Control and Radio Resource Management
For each user distribution, Atoll simulates the power control, dynamic channel allocation (DCA), and RRM mechanism of TDSCDMA cells. The simulation uses an iterative algorithm that models power control on both downlink and uplink for R99
bearers and link adaptation for HSDPA users. This iterative process ends when the network is balanced, i.e., when the
convergence criteria are satisfied.
The figure below shows an overview of the simulation algorithm.
Figure 12.21 TD-SCDMA simulation overview
The R99 part of the TD-SCDMA Monte Carlo simulations applies to all the generated mobiles regardless of their service and
terminal HSPA capabilities. This phase of calculations includes the following steps:
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Initialisation: The network is initialised as “empty”. There is no mobile connected to any transmitter when starting
a simulation. The following steps are repeated for each mobile (R99, HSDPA, and HSUPA) of the generated user
distribution.
Dynamic channel allocation (DCA): DCA reduces interference and maximises the usage of resource units. Resource
units from different carriers can be shared and allocated to the same mobile connected to an N-frequency mode
compatible transmitter. In TD-SCDMA networks, interference for a given timeslot can be downlink-to-downlink,
uplink-to-uplink, downlink-to-uplink, and uplink-to-downlink. Atoll selects a carrier for each user according to the
selected DCA algorithm:
o Preferred carrier: If defined, Atoll assigns the preferred carrier of the service to its user.
o Load: Atoll selects the least loaded cell and timeslots with enough free OVSF codes for the user’s service.
o Available RUs: Atoll selects the cell and timeslots with the most available resource units.
o Direction of arrival: Atoll selects the cell and timeslots that do not have an interfering mobile located
nearby at the same angle as the direction of arrival of the targeted mobile.
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o Sequential: Atoll assigns cells and timeslots to users in a sequential order.
Uplink power control: The mobile transmit power is calculated. It corresponds to the power required to satisfy the
uplink Eb/Nt or C/I requirement. The mobile is rejected if the calculated required transmit power is higher than the
maximum mobile transmit power.
Downlink power control: The transmitter traffic channel power is calculated. It corresponds to the power required
to satisfy the downlink Eb/Nt or C/I requirement. The mobile is rejected if the calculated traffic channel power is
higher than the maximum traffic channel power allowed.
Uplink and downlink interference update: The uplink load factor and total downlink transmit power are updated
with these results. Atoll also updates the angular distributions of uplink and downlink loads for cells using smart
antennas.
Congestion and radio resource control (R99 bearers): Atoll then carries out congestion and radio resource control,
verifying the uplink load, the total transmitted power, the number of resource units, and OVSF codes consumed
considering the services which require several timeslots.
At this point, mobiles can be either connected or rejected. They are rejected if:
o Insufficient signal quality:
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P-CCPCH RSCP is not enough.
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The power required to reach the mobile is greater than the maximum allowed: Ptch > Max Ptch
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Not enough power to transmit: Pmob > Max Pmob
o Insufficient resources:
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The maximum uplink load factor is exceeded: Admission Rejection or UL Load Saturation
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Not enough resource units in the cell: RU Saturation
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Not enough power for cells: DL Load Saturation
The HSDPA part of the TD-SCDMA Monte Carlo simulations applies to HSDPA mobiles. This phase of calculations includes the
following steps:
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Fast link adaptation: Atoll selects the appropriate HSDPA Bearer.
Scheduling: The scheduler shares cell radio resources according to the policy of the scheduler (max C/I, round robin
or proportional fair).
Radio resource control
The above calculations are carried out during each successive iteration until the simulation converges, i.e., both uplink and
downlink convergence criteria are satisfied.
Main simulation outputs are:
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Cell loads per timeslot
HSDPA throughputs
Note that numerous other parameters are available and stored during the simulation for further analysis. For more
information, see 12.5.5 Simulation Reports.
12.5.3 Monte Carlo Simulation Management
TD-SCDMA simulations are managed through the Simulations folder in the Atoll Explorer window. This folder is displayed in
the figure below.
Figure 12.22 TD-SCDMA simulations folder
The Simulations folder is made up of several simulation “groups”. Each group corresponds to a network configuration for
which a user-specified number of Monte Carlo simulations have been generated. As an example, different groups may
correspond to different traffic assumptions.
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When several simulation groups are available, it is possible to automatically display one group after the other, hence
animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
The figure below shows the simulation creation dialog box. The following information is required when creating a new group
of Monte Carlo simulations:
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The simulation group name
The number of simulations to be run
The load constraints to apply during simulations
The traffic maps used
The convergence criteria.
Figure 12.23 TD-SCDMA simulation creation dialog box
Once a simulation (or a group of simulations) has been performed, simulation reports are available and simulation results can
be graphically analysed in Atoll.
12.5.4 Simulation Graphical Analysis
Graphical Display: Mobile Connection Status
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for their connection status. The different possible statuses are:
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Connect DL + UL: the mobile is connected on both downlink and uplink
Connect UL: the mobile is connected on uplink only
Connect DL: the mobile is connected on downlink only
Inactive: the mobile is inactive
Pmob > PmobMax: the mobile is rejected during uplink power control as its required uplink transmitter power is
higher than the maximum mobile transmit power
Ptch > PtchMax: the mobile is rejected during downlink power control as the required downlink traffic channel
power is higher than the maximum downlink traffic channel power
P-CCPCH RSCP < Min P-CCPCH RSCP: the mobile is rejected during best server determination as the Best Server PCCPCH RSCP is less than the minimum required
Admission Rejection: the mobile is rejected during best server determination as the uplink cell load would be higher
than the maximum allowed
UL Load Saturation: the mobile is rejected during congestion and radio resource control as the uplink cell load would
be higher than the maximum allowed
DL Load Saturation: the mobile is rejected during congestion and radio resource control as the downlink total power
is higher than the maximum allowed
RU Saturation: the mobile is rejected during the “Congestion and Radio Resource Control Step” as there are not
enough resource units available
HSDPA Delayed: the mobile cannot obtain lower HSDPA bearer or HS-SCCH signal quality is not sufficient
HSDPA Scheduler Saturation: the maximum HSDPA users per cell or max number of HS-SCCH channel are exceeded
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An example of a graphical display of a group of simulations is presented in the figure below.
Figure 12.24 TD-SCDMA simulation graphical display
Individual Mobile Result Graphical Display
Parameters for any user can be displayed either in the results table or directly on the map (as presented in the figure below).
Figure 12.25 Individual mobile results display using the tool tip
12.5.5 Simulation Reports
Atoll provides detailed simulation results in the form of reports.
Reports of a Single Simulation
A report is available for each simulation. This report contains information about the simulation statistics, and calculation
results by sites, cell, and mobile as given in the figure below.
Figure 12.26 TD-SCDMA simulation report
The simulation results are provided at the following different levels:
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Global statistics: total users attempting a connection and the corresponding break-up per service; total users
actually connected and the corresponding break-up per service.
Results per site: throughput allocated per service type.
Results per cell and timeslot: downlink transmit power related information, uplink mobile power related
information, number of radio links for uplink and downlink, throughput allocated to downlink and uplink, number
of mobile rejections split per rejection reason.
Results per mobile: geographic location, terminal type, user type, mobility, connection status, carrier, requested
and allocated throughputs for uplink and downlink, best server information.
Initial conditions: parameters and traffic maps used to create the simulation.
An option is available to display more detailed results. This extra information includes for each mobile:
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The detailed parameters values for each member of the active set (noise values, interference values, etc.),
The shadowing loss values for each path from a mobile to its first 10 potential servers.
Reports of a Group of Simulations
Atoll provides detailed simulation results averaged over a group of simulations in the form of reports. The report generated
for a simulation group contains:
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Statistics: average statistics obtained from the results of all the simulations in a group
Results per site: average site results obtained from the results of all the simulations in a group
Results per cell: average cell results obtained from the results of all the simulations in a group
Results per timeslot: average timeslot results obtained from the results of all the simulations in a group
Initial conditions: parameters used to create the simulation group.
Figure 12.27 TD-SCDMA simulation group report
12.5.6 Updating Cell Loads
You can store the cell loads calculated by Monte Carlo simulations in the cells data table. This enables you to update the
network cell loads based either on the average results from a simulation group or the results of from a single simulation. Cell
load values for all the cells in the network radio database are then updated with the results generated by the selected
simulation. Cell loads from a simulation, simulation group, or from the cells data table can then be used to generate coverage
prediction plots.
12.5.7 Exporting Results
You can export the simulation results as described in 2.5.1 Network Data Import and Export.
TD-SCDMA Coverage Predictions
In Atoll a coverage prediction is a plot displaying calculation results of user-selected parameters on the map and enabling
graphical as well as statistical analysis of the network behaviour. For each pixel, Atoll calculates the required information.
This data is then graphically represented by a colour according to a user-defined legend. Different display options are available
in Atoll, depending on the calculated parameter.
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12.6.1 Coverage Prediction Calculation and Management
Coverage predictions are performed by assuming a “probe mobile” (non-interfering terminal) on each pixel of the considered
area. The probe mobile characteristics (terminal type, mobility type, service type) are specified as inputs to the coverage
prediction in order to calculate the user-defined prediction parameter.
Predictions are stored as multi-layer geographic objects in the Predictions folder of the Explorer window and can be displayed
in the map window. When several coverage predictions are available, it is possible to automatically display one prediction
after the other, hence animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
Subfolders can be created in the Predictions folder in order to group various coverage prediction objects into categories.
Coverage predictions can be directly created under a subfolder and moved from one subfolder to another using the mouse.
12.6.2 Coverage Prediction Types
TD-SCDMA coverage predictions can be generated either based on the results from Monte Carlo simulations or on userdefined cell load configurations.
TD-SCDMA coverage prediction types and their display options available in Atoll are listed below.
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Coverage by P-CCPCH best server (DL)
o Transmitter
Coverage by P-CCPCH RSCP (DL)
o Best signal level
o RSCP margin
o Reliability level
P-CCPCH pollution analysis (DL)
o Number of servers
Coverage by DwPCH RSCP (DL)
o DwPCH RSCP
o RSCP margin
Coverage by UpPCH RSCP (UL)
o UpPCH RSCP
o RSCP margin
P-CCPCH quality analysis (Eb/Nt) (DL)
o Eb/Nt
o Eb/Nt margin
P-CCPCH quality analysis (C/I) (DL)
o C/I
o C/I margin
DwPCH quality analysis (C/I) (DL)
o C/I
o C/I margin
Coverage by TCH RSCP (DL)
o DL TCH RSCP
o RSCP margin
Coverage by TCH RSCP (UL)
o UL TCH RSCP
o RSCP margin
Service area analysis (Eb/Nt) (DL)
o Effective Eb/Nt
o Max Eb/Nt
o Eb/Nt margin
o Required power
o Required power margin
Service area analysis (C/I) (DL)
o C/I
o Max C/I
o C/I margin
o Required power
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o Required power margin
Service area analysis (Eb/Nt) (UL)
o Effective Eb/Nt
o Max Eb/Nt
o Eb/Nt margin
o Required power
o Required power margin
Service area analysis (C/I) (UL)
o C/I
o Max C/I
o C/I margin
o Required power
o Required power margin
Effective service area analysis (Eb/Nt) (DL+UL)
Effective service area analysis (C/I) (DL+UL)
Total noise level analysis (DL)
o Minimum, average, and maximum noise level
Cell to cell interference zones
o Minimum, average, and maximum interference level
UpPCH interference zones (UL)
o Minimum, average, and maximum noise level
Baton handover zones (DL)
o Number of potential neighbours
Scrambling code collision zones (DL)
o Interfered scrambling code
HSDPA quality and throughput analysis (DL)
o Minimum, average, and maximum HS-PDSCH RSCP
o Minimum, average, and maximum HS-PDSCH Ec/Nt
o Peak RLC throughput
o Peak MAC throughput
Various TD-SCDMA coverage prediction plots are shown in the figures below.
Figure 12.28 TD-SCDMA coverage by P-CCPCH best server
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Figure 12.29 TDSCDMA coverage by P-CCPCH RSCP
Figure 12.30 TDSCDMA P-CCPCH quality analysis coverage prediction
Figure 12.31 TDSCDMA P-CCPCH pollution coverage prediction
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Figure 12.32 TDSCDMA DwPCH quality analysis coverage prediction
Figure 12.33 TDSCDMA coverage by DwPCH RSCP
Figure 12.34 TDSCDMA coverage by UpPCH RSCP
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Figure 12.35 TDSCDMA coverage by downlink traffic channel RSCP
Figure 12.36 TDSCDMA coverage by uplink traffic channel RSCP
Figure 12.37 TDSCDMA downlink service area analysis coverage prediction
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Figure 12.38 TDSCDMA uplink service area analysis coverage prediction
Figure 12.39 TDSCDMA effective service area analysis coverage prediction
Figure 12.40 TDSCDMA downlink total noise level analysis coverage prediction
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Figure 12.41 TDSCDMA UpPCH interference zones coverage prediction
Figure 12.42 TDSCDMA baton handover zones coverage prediction
Figure 12.43 TDSCDMA scrambling code collision zones coverage prediction
12.6.3 Coverage Prediction Reports
Atoll can generate reports for one or more coverage predictions with various detail levels as defined by the user. Reports are
spread sheet-like tables that can be printed directly from Atoll or exported to any desktop tool. An example of such a report
is given in the figure below.
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Figure 12.44 TD-SCDMA coverage prediction report
12.6.4 Coverage Prediction Comparison
Comparison (difference, intersection, union, or merge) between two coverage predictions can be performed. As examples,
this functionality can be used:
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To compare uplink and downlink coverage of a service. This enables you to determine uplink/downlink-limited
zones for that service.
To compare service area coverage plots of two different services. This enables you to assess the areas where one
service (e.g., Mobile Internet Access) is available while the other (e.g., Video Conferencing) is not.
To compare service area coverage plots of two networks deployment scenarios (possibly with different
technologies).
12.6.5 Coverage Prediction Export
Any coverage prediction can be exported in the following formats:
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Atoll format
ArcView SHP
MapInfo MIF and TAB
ArcView Grid TXT and ASC
Vertical Mapper GRD and GRC
BMP
PNG
TIFF
BIL
JPEG2000
JPEG
When exported in MapInfo format, coverage prediction attributes (e.g., signal levels, transmitter IDs, etc.) are exported along
with the plot. The figure below gives an example of the exported attributes for a downlink Eb/Nt prediction.
Figure 12.45 TD-SCDMA coverage prediction attributes export to MapInfo
12.6.6 Point Analysis Tool
A real-time prediction analysis tool is available in Atoll. The point analysis tool is dynamically linked to the map window. The
displayed information is updated as the receiver is moved on the map window. The point analysis tool provides the downlink
signal values numerically and graphically for all cells and for the selected terminal type, mobility type, and service type.
The figure below shows the point analysis window as well as its link to the map window.
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Receiver
Reception analysis tool
Parameters
Signal strength
Figure 12.46 TD-SCDMA real-time point analysis tool
TD-SCDMA Neighbour Planning
Atoll supports the following neighbour types in a TD-SCDMA network configuration:
Atoll supports the following neighbour types in a TD-SCDMA network configuration:
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Intra-technology neighbours: TD-SCDMA cells defined as neighbours of other TD-SCDMA cells in the same Atoll
document.
Inter-technology neighbours: TD-SCDMA cells defined as neighbours of cells which use a technology other than TDSCDMA.
Neighbour plans can be generated by any of the following means in Atoll:
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Importing an external neighbour plan (e.g., in Excel format)
Automatically producing a neighbour plan as described in 12.7.1 Automatic Neighbour Allocation
Graphically and/or manually creating, editing and deleting a neighbour plan as presented in 12.7.2 Graphical
Neighbour Plan Editing
Various neighbour plans can be compared. The results of an automatic neighbour allocation can be compared with the
existing neighbour plan. As well, neighbour plans from external sources can also be compared with the existing neighbour
plan in Atoll.
12.7.1 Automatic Neighbour Allocation
Neighbour lists can be generated automatically in Atoll. For each cell, potential neighbours are ranked according to their
importance. The neighbour planning algorithm considers the following user-specified parameters:
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P-CCPCH RSCP T_Add
P-CCPCH RSCP T_Drop
P-CCPCH RSCP T_Comp
Maximum inter-site distance
Maximum number of neighbours
Minimum area covered (overlapping area between the studied cell and its potential neighbour)
Importance ranges for distance, coverage, adjacency, and co-site factors
Forcing “neighbour symmetry”, “adjacent cells as neighbour”, “co-site cells as neighbours“ and/or “exceptional neighbour
pairs” is possible with Atoll. The figure below displays the automatic neighbour allocation dialog box.
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Figure 12.47 TD-SCDMA automatic neighbour list generation
12.7.2 Graphical Neighbour Plan Editing
Neighbour plan can be graphically edited in Atoll. Clicking a transmitter on the map displays all its neighbour relations. All
types of neighbour relations (outwards, inwards or symmetrical) can be created, edited and/or deleted graphically. Such an
example is presented in the figures below.
Figure 12.48 Graphical neighbour plan editing
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Figure 12.49 Neighbour planning using a best server plot
12.7.3 Neighbour Consistency Check Tool
A neighbour relation audit is available in Atoll. This function enables you to determine inconsistencies in the current
neighbour plan. The figure below shows the neighbour relation conditions that can be verified using the audit.
Figure 12.50 Neighbour audit
TD-SCDMA Master/Slave Carrier Planning in N-Frequency Mode
TD-SCDMA networks can work in single-carrier as well as multi-carrier modes. In single-carrier mode, each transmitter has
only one cell (carrier), which is considered a stand-alone carrier. In multi-carrier mode, each transmitter can have up to six
carriers, with one master carrier and several slave carriers. The master carrier is used for P-CCPCH broadcast, scrambling code
broadcast, and handover management, whereas the slave carriers are only used for carrying traffic. The multi-carrier mode
is called N-Frequency Mode in Atoll.
You can set the type of carrier for each cell of a transmitter manually, or you can let Atoll automatically allocate carrier types
(master/slave) to cells on transmitters that support the N-frequency mode. Atoll’s automatic carrier type allocation algorithm
is based on the inter-site distance criterion. Its aim is to optimise the reuse of the same carrier as master/slave in the network.
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Figure 12.51 TD-SCDMA automatic carrier type planning
An N-frequency mode carrier type audit is also available in Atoll. The audit enables you to find out the following potential
problems in you N-frequency mode network:
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Master carriers:
o Transmitters in N-frequency mode: Transmitters that are not N-frequency mode compatible and have a
master carrier assigned.
o One master carrier per transmitter: Transmitters that have either no or more than one master carrier.
o Defined P-CCPCH power: The transmitters whose master carriers do not have a P-CCPCH power defined.
Stand-alone carriers:
o Defined P-CCPCH power: The transmitters whose stand-alone carriers do not have a P-CCPCH power
defined.
Slave carriers:
o Linked to a master carrier: The transmitters whose slave carriers are not linked to any master carrier.
o P-CCPCH, DwPCH, and Other CCH fields empty: The transmitters whose slave carriers have P-CCPCH,
DwPCH, and other CCH powers defined.
o Timeslot configurations, Scrambling codes, and Neighbours same as the master carrier: Slave carriers that
do not have the same timeslot configurations, scrambling codes, and neighbours as the master carrier.
TD-SCDMA Scrambling Code Planning
Scrambling code plans can be generated by any of the following means in Atoll:
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Importing an external scrambling code plan (e.g., in Excel format),
Manually creating, editing and/or deleting a scrambling code plan,
Automatically producing a scrambling code plan as described in 12.9.1 Automatic Scrambling Code Planning Tool
Once created, scrambling code plan consistency can be verified in Atoll.
12.9.1 Automatic Scrambling Code Planning Tool
Atoll’s automatic scrambling code planning tool is based on a cost-based algorithm. The cost function takes into account
several criteria. The following constraints are applied when running the automatic planning algorithm:
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Domain constraint: required to distinguish different zones
Groups: it is possible to define scrambling code groups
Exceptional pairs: it is possible to define cell pairs that cannot have the same scrambling code
Reuse distance: a minimum reuse distance is defined (globally or per cell)
Four code allocation strategies are available:
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Clustered: Scrambling codes are chosen among a minimum number of SYNC_DLs, Atoll preferentially allocates all
the codes from same SYNC_DL.
Distributed per cell: Scrambling codes are chosen among as many SYNC_DLs as possible. Atoll preferentially
allocates codes from different SYNC_DLs.
One SYNC_DL per site: Allocates one SYNC_DL to each site, then one code of the SYNC_DL to each cell of each site.
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Distributed per site: Allocates a group of adjacent SYNC_DLs to each site, then one SYNC_DL to each transmitter of
the site according to its azimuth and finally one code of the SYNC_DL to each cell of each transmitter.
Atoll facilitates the management of scrambling codes by letting you create groups of scrambling codes and domains, where
each domain is a defined set of groups. Scrambling code domains can then be assigned to cells in order to provide a list of
possible scrambling codes for each cell. Atoll also takes into account the scrambling code relativity clusters, if defined.
The figure below presents the automatic scrambling code allocation tool.
Figure 12.52 Automatic scrambling code planning
12.9.2 Scrambling Code Consistency Check Tool
A scrambling code consistency check tool is available in Atoll. This function enables you to detect any inconsistency due to
potential manual code changes. The figure below shows the conditions that can be verified using the audit.
Figure 12.53 Scrambling code audit
Atoll can also display distribution histograms of scrambling codes and SYNC_DLs.
TD-SCDMA Co-planning With Other Radio Access Technologies
Atoll supports co-planning of TD-SCDMA networks with other radio access technologies. For more information, see 11 MultiRAT Features.
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13 LPWA Features
The Atoll LPWA module enables wireless IoT (Internet of Things) network operators to design, plan, and optimise their
networks based on Low Power Wide Area (LPWA) technologies, such as LoRa, Sigfox, Ingenu, Wireless MBus, and other
technologies.
Atoll LPWA supports licensed as well as unlicensed frequency bands worldwide, technology-specific channel configurations
and modulation techniques with and without link adaptation, and transmission and reception diversity. Based on Atoll’s 64bit platform, Atoll LPWA can support large-scale IoT wireless networks comprising gateways covering wide areas and massive
numbers of connected objects and end-devices.
Atoll’s high-performance propagation models and comprehensive analysis features allow evaluating LPWA network coverage,
service areas, and service quality. Atoll can also calculate LPWA service availability and quality for user-defined lists of
connected objects providing their exact locations.
Atoll also includes an end devices database which can contain information about end devices with fixed locations, and
predictions can be run at exact end device locations to determine the service availability and quality.
Moreover, the Atoll LPWA ACP can be used for LPWA site selection based on server redundancy as well as signal level and
quality objectives. The ACP can also be used to optimise operational IoT networks.
LPWA Network Model
The LPWA network model comprises radio network elements such as sites, transmitters, and cells. An LPWA gateway or base
station is equivalent to a site, its transmitters with one or more radio channels (cells) each.
Figure 13.1 LPWA network model
13.1.1 Sites
A site represents the physical location where base stations can be installed. An example of a site properties window is shown
in the figure below.
Figure 13.2 Site properties window
Site parameters are:
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Geographic coordinates
Altitude (user-defined or automatically extracted from the terrain elevation data)
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Any user-defined flags and parameters such as address, owner, deployment phase, etc.
13.1.2 Transmitters
Transmitters in Atoll correspond to sectors and antennas installed at a site. The main transmitter parameters are:
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Transmitter name and the name of the site where it is installed
X and Y coordinates
Transmitter type (server and interferer, or interferer only)
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Numbers of transmission and reception antennas for MIMO
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other transmitters
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Tower mounted amplifier (TMA)
Feeder type and its transmission and reception lengths
Any user-defined flags and parameters
An example of a transmitter properties window is shown in the figure below.
Figure 13.3 LPWA transmitter properties window
13.1.3 Cells
Atoll supports multi-band LPWA network deployments. In Atoll, cells model frequency channels used at a transmitter. A
transmitter can support more than one cell. Each cell has its own radio resources and parameters, including:
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Cell name and the name of the transmitter to which the cell belongs
Frequency band
Channel configuration
BSID
Transmission power
Reception equipment
Minimum C/N
AMS threshold
Maximum number of simultaneous users
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Resource allocation constraints: maximum uplink and downlink traffic loads
Cell loads and resource allocation results: uplink and downlink traffic loads, uplink and downlink noise rise, numbers
of connected users in downlink and uplink
Neighbour parameters: maximum numbers of neighbours and neighbours lists
Any user-defined flags and parameters
The figure below presents an example of a transmitter with a single cell.
Figure 13.4 LPWA cell parameters
13.1.4 Site Templates
A site template is made up of one or more transmitters and cells located on the same site. Site templates can be created and
edited as needed. Building a network is facilitated by working with site templates rather than single site/transmitter/cell. In
Atoll LPWA, it is possible to create site templates with multiple cells using different technologies. 4By default some LPWA site
templates are available for LoRa, Sigfox, and Wireless MBus.
13.1.5 Repeaters
A repeater receives, amplifies, and retransmits signals. Repeaters are used to extend the coverage of their donors. Atoll
models selective as well as non-selective RF repeaters, optic fibre repeaters, microwave repeaters, and remote antennas.
Selective RF repeaters only repeat signals from their donor transmitters whereas non-selective RF repeaters receive and
retransmit wanted signals as well as interference.
The main parameters of a repeater are:
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Donor transmitter name
X and Y coordinates
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other repeaters
Total gain
Amplifier gain
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Feeder type and its transmission and reception lengths
Any user-defined flags and parameters
The figure below presents the repeater properties window while the figure below that gives an example of a best server
prediction plot with a repeater.
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Figure 13.5 Repeater properties window
RF repeater
Donor transmitter
Figure 13.6 RF repeater coverage plot
LPWA Network Configuration Parameters
Atoll allows setting and modifying network-level configurations and parameters applicable to the entire project.
13.2.1 Frequency Bands
Atoll supports multi-band LPWA networks. Atoll supports all frequency bands supported by LPWA technologies such as LoRa,
Sigfox, Wireless MBus, etc. A frequency band is characterized by its uplink and downlink frequencies, and its band bandwidth.
You can add, modify, and delete frequency bands in Atoll as required. A number of default frequency bands are available by
default as shown in the figure below.
Figure 13.7 LPWA frequency bands table
13.2.2 Channel Configurations
The following LPWA frame configurations are available in Atoll:
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Channel configurations allow you to model channels within frequency bands. Each channel configuration corresponds to a
given band width, and allows you to define the width of monitored spectrum in downlink and uplink, the width of an individual
channel in downlink and uplink, and the numbers of channels in downlink and uplink. Moreover, depending on the base
station equipment, antenna diversity parameters can also be defined.
You can add, modify, and delete channel configurations in Atoll as required. An example of channel configuration definition
is shown in the figure below.
Figure 13.8 LPWA channel configuration properties
13.2.3 Radio Bearers
Radio bearers are used to carry user data on the downlink and uplink traffic channels. A bearer refers to a combination
modulation and coding scheme. The radio bearers table lists the available radio bearers in downlink and uplink. You can add,
remove, and modify bearer properties according to your network and equipment. The figure below shows the default bearers
in Atoll.
Figure 13.9 Default LPWA bearers
13.2.4 Quality Indicators
In Atoll, quality indicators (BER, BLER, etc.) represent the coverage quality at different locations. The quality indicators table
lists the available quality indicators which you can add, remove, and modify as required.
LPWA Radio Equipment
Atoll provides the option to define various pieces of radio equipment such as antennas and reception equipment. For more
information on common antenna and radio equipment features, see 4 Antenna and Radio Equipment Features.
13.3.1 LPWA Reception Equipment
LPWA reception equipment model the reception characteristics of cells and terminals. Bearer selection thresholds, quality
indicator graphs, and MIMO gains are defined in LPWA reception equipment. The figure below gives an example of such an
equipment definition.
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Figure 13.10 LPWA bearer selection thresholds
Diversity gains as well as MIMO throughput gains can be defined for each equipment for different numbers of transmission
and reception antennas, modulation and coding schemes, and user speeds.
LPWA Traffic Model
In Atoll, the radio network traffic is modelled according to the definition of the services and users in the network. Service and
user behaviours are modelled in Atoll through different tables that provide information about:
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The services available in the network
The terminals compatible with the network
The mobility types, i.e., speeds
The LPWA traffic model is shown in the figure below.
Figure 13.11 LPWA traffic model
13.4.1 Services
The services table describes the services that are available in the network. The main service parameters are:
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Service type
Priority level
Lowest and highest bearers allowed
Uplink and downlink maximum throughput demands
Uplink and downlink minimum throughput demands
Uplink and downlink average requested throughputs
Uplink and downlink activity factors
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Throughput conversion parameters from MAC to Application layer
Body loss
An example of a service properties window is presented in the figure below.
Figure 13.12 Service properties window
13.4.2 Terminals
The terminals table describes the end devices or objects used in the network. The following parameters model a terminal:
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Minimum and maximum transmission powers
Noise figure
Transmission and reception loss
Reception equipment
Antenna pattern
Antenna gain
Diversity support
Numbers of MIMO antennas
An example of a terminal properties window is given in the figure below.
Figure 13.13 Terminal properties window
13.4.3 Mobility Types
The mobility type defines different user speeds.
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LPWA Coverage Predictions
In Atoll a coverage prediction is a plot displaying calculation results of user-selected parameters on the map and enabling
graphical as well as statistical analysis of the network behaviour. Examples of LPWA coverage predictions are signal level,
signal quality, radio bearer, throughput plots, etc. For each pixel, Atoll calculates the required information. This data is then
graphically represented by a colour according to a user-defined legend. Different display options are available in Atoll,
depending on the calculated parameter.
13.5.1 Coverage Prediction Calculation and Management
Coverage predictions are performed by assuming a “probe mobile” (non-interfering terminal) on each pixel of the considered
area. The probe mobile characteristics (terminal type, mobility type, service type) are specified as inputs to the coverage
prediction in order to calculate the user-defined prediction parameter.
Predictions are stored as multi-layer geographic objects in the Predictions folder of the Explorer window and can be displayed
in the map window. When several coverage predictions are available, it is possible to automatically display one prediction
after the other, hence animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
Subfolders can be created in the Predictions folder in order to group various coverage prediction objects into categories.
Coverage predictions can be directly created under a subfolder and moved from one subfolder to another using the mouse.
13.5.2 Coverage Prediction Types
LPWA coverage prediction types and their display options available in Atoll are listed below.
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Coverage by transmitter (DL)
o Transmitter
Coverage by signal level (DL)
o Signal level (dBm, dBµV or dBµV/m)
o Path loss (dB)
Overlapping zones (DL)
o Number of servers
Effective signal analysis (DL)
o Downlink signal level and C/N
Effective signal analysis (UL)
o Uplink signal level and C/N
Coverage by C/(I+N) level (DL)
o Downlink total noise (I+N) and C/(I+N)
Coverage by C/(I+N) level (UL)
o Uplink total noise (I+N) and C/(I+N)
o Uplink transmission power
Service area analysis (DL)
o Bearer
o Modulation
Service area analysis (UL)
o Bearer
o Modulation
Effective service area analysis (DL + UL)
Coverage by throughput (DL)
o Peak MAC, effective MAC, and application channel throughput
o Peak MAC, effective MAC, and application cell capacity
o Peak MAC, effective MAC, and application throughput per user
Coverage by throughput (UL)
o Peak MAC, effective MAC, and application channel throughput
o Peak MAC, effective MAC, and application cell capacity
o Peak MAC, effective MAC, and application throughput per user
Coverage by quality indicator (DL)
o BER, BLER, etc.
Coverage by quality indicator (UL)
o BER, BLER, etc.
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The first five coverage predictions (coverage by transmitter, coverage by signal level, overlapping zones, and effective signal
analyses) are not based on interference. Coverage predictions can be calculated for a service, mobility type, and user terminal
equipment.
Various LPWA coverage prediction plots are shown in the figures below.
Figure 13.14 LPWA base station coverage
Figure 13.15 LPWA coverage by signal level
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Figure 13.16 LPWA coverage by number of servers (outdoor)
Figure 13.17 LPWA coverage by number of servers (indoor)
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Figure 13.18 LPWA service area
13.5.3 Coverage Prediction Reports
Atoll can generate reports for one or more coverage predictions with various detail levels as defined by the user. Reports are
spread sheet-like tables that can be printed directly from Atoll or exported to any desktop tool. An example of such a report
is given in the figure below.
Figure 13.19 LPWA coverage prediction report
13.5.4 Coverage Prediction Comparison
Comparison (difference, intersection, union, or merge) between two coverage predictions can be performed. As examples,
this functionality can be used:
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To compare uplink and downlink coverage of a service. This enables you to determine uplink/downlink-limited
zones for that service.
To compare service area coverage plots of two different LPWA technologies. This enables you to assess the areas
where one technology is available while the other is not.
To compare service area coverage plots of two networks deployment scenarios.
To compare service area coverage plots for indoor vs. outdoor service availability. The figure below illustrates such
a case by comparing LTE and LPWA coverage.
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Figure 13.20 Coverage prediction graphical comparison
Atoll also enables you to carry out per-pixel arithmetical operations between coverage predictions. For example, you can
calculate the sum, difference, min, max, and average of similar calculated parameters per pixel from two coverage predictions
of the same or different technologies.
13.5.5 Coverage Prediction Export
Any coverage prediction can be exported in the following formats:
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Atoll format
ArcView SHP
MapInfo MIF and TAB
ArcView Grid TXT and ASC
Vertical Mapper GRD and GRC
BMP
PNG
TIFF
BIL
JPEG2000
JPEG
When exported in MapInfo format, coverage prediction attributes (e.g., signal levels, transmitter IDs, etc.) are exported along
with the plot. The figure below gives an example of the exported attributes for a C/(I+N) prediction.
Figure 13.21 LPWA coverage prediction attributes export to MapInfo
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13.5.6 Point Analysis Tool
A real-time prediction analysis tool is available in Atoll. The point analysis tool is dynamically linked to the map window. The
displayed information is updated as the receiver is moved on the map window. The point analysis tool provides the downlink
signal values numerically and graphically for all cells and for the selected terminal type, mobility type, and service type.
The figure below shows the point analysis window as well as its link to the map window.
Receiver
Received
signal
strength
Figure 13.22 LPWA point-to-point real-time analysis
13.5.7 Multi-Point Analysis at Device Locations
Fixed connected objects and end devices are modelled in Atoll LPWA through fixed subscriber traffic maps. For more
information, see 2.2.7 Traffic Data. The figure below shows a sample list of connected objects as modelled in Atoll.
Figure 13.23 List of connected objects (extract)
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Atoll enables you to carry out point predictions on multiple point locations and at different heights. Multi-point analyses can
be carried out on device locations from fixed subscriber traffic maps and points created on the map using the mouse. Fixed
subscriber analysis results include detailed results for the device’s best server.
Multi-point analysis results are stored in the Multi-Point Analysis folder in the Network explorer. Once calculated, multi-point
analysis results are available in tabular form and visible on the map using symbols and colours based on calculation results.
You can export the multi-point analysis results as described in 2.5.1 Network Data Import and Export.
Figure 13.24 End devices displayed on the map
LPWA Neighbour Planning
Atoll supports the following neighbour types in an LPWA network configuration:
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Intra-technology neighbours: LPWA cells defined as neighbours of other LPWA cells in the same Atoll document.
Inter-technology neighbours: LPWA cells defined as neighbours of cells which use a technology other than LPWA.
Neighbour plans can be generated by any of the following means in Atoll:



Importing an external neighbour plan (e.g., in Excel format)
Automatically producing a neighbour plan as described in 13.6.1 Automatic Neighbour Allocation
Graphically and/or manually creating, editing and deleting a neighbour plan as presented in 13.6.2 Graphical
Neighbour Plan Editing
Various neighbour plans can be compared. The results of an automatic neighbour allocation can be compared with the
existing neighbour plan. As well, neighbour plans from external sources can also be compared with the existing neighbour
plan in Atoll.
13.6.1 Automatic Neighbour Allocation
Neighbour lists can be generated automatically in Atoll. For each cell, potential neighbours are ranked according to their
importance. The neighbour planning algorithm considers the following user-specified parameters:
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Hysteresis zone defined by a handover start and a handover end margin with respect to the best server signal
strength
Maximum inter-site distance
Maximum number of neighbours
Minimum area covered (overlapping area between the reference cell and its potential neighbour).
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Importance ranges for distance, coverage, adjacency, and co-site factors.
Forcing “neighbour symmetry”, “adjacent cells as neighbours”, “co-site cells as neighbours“ and/or “exceptional neighbour
pairs” is possible with Atoll. The figure below displays the automatic neighbour allocation dialog box.
Figure 13.25 LPWA automatic neighbour list generation
13.6.2 Graphical Neighbour Plan Editing
Neighbour plan can be graphically edited in Atoll. Clicking a transmitter on the map displays all its neighbour relations. All
types of neighbour relations (outwards, inwards or symmetrical) can be created, edited and/or deleted graphically.
13.6.3 Neighbour Consistency Check Tool
A neighbour relation audit is available in Atoll. This function enables you to determine inconsistencies in the current
neighbour plan. The figure below shows the neighbour relation conditions that can be verified using the audit.
Figure 13.26 Neighbour audit
LPWA Automatic Cell Planning
The Atoll LPWA ACP (Automatic Cell Planning) module enables you to automatically determine the best LPWA site locations
that ensure more than one server covering connected objects in the network. The ACP can also be used to optimise operating
IoT networks and to find the best LPWA parameter settings for your network.
The aim of the Atoll ACP is to improve network quality in terms of both coverage and capacity. For a comprehensive
description of the Atoll ACP, see 17 Automatic Cell Planning (ACP) Features.
.
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The Atoll LPWA ACP is capable of optimising network parameters (antenna types, heights, azimuths, tilts, transmission
powers, etc.) based on the following LPWA quality indicators:
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Signal level
Server redundancy
C
C/N
CINR
Overlap
Best server distance
1st-Nth difference
The following figures depict the setup of an LPWA site selection scenario in the Atoll ACP and its results.
Figure 13.27 Atoll LPWA ACP site selection setup
Figure 13.28 Atoll LPWA ACP site selection objectives
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Figure 13.29 LPWA signal level improvement
Figure 13.30 LPWA server redundancy improvement
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14 Wi-Fi Features
The Atoll WiMAX/BWA module provides a comprehensive and accurate modelling of multi-band WiMAX and Wi-Fi networks.
It supports all WiMAX and Wi-Fi frequency bands and carrier widths along with detailed frame structure modelling for both
technologies. Atoll WiMAX/BWA also includes comprehensive modelling of different MIMO techniques.
Atoll supports all modulation and coding schemes, voice, VoIP, and data services, and different user equipment. Atoll provides
the means to set up multi-service traffic maps from multiple sources: vector, raster and live traffic data. Traffic maps are used
in WiMAX and Wi-Fi Monte Carlo simulations for network capacity analysis including RRM, scheduling, and backhaul
constraints. Coverage predictions can be calculated based on Monte Carlo simulation results or on live network loads from
the OMC in order to study coverage and capacity of the network.
Atoll enables you to design IEEE 802.11 WLAN networks including the 802.11a, 802.11g, 802.11n, 802.11p, 802.11ad, and
802.11ac standards.
Operating
Channel Widths
Frequencies
(MHz)
(GHz)
802.11a (Release 1999)
5
20
Modulations
MIMO
Maximum AP
Throughput
(Mbps)
BPSK, QPSK, 16QAM, 64QAM
–
54
802.11g (Release 2003, Revision 2007)
2.4
20
BPSK, QPSK, 16QAM, 64QAM
–
54
802.11n (Release 2009)
2.4, 5
20, 40
BPSK, QPSK, 16QAM, 64QAM
4x4 (Maximum)
540 (Long GI)
600 (Short GI)
802.11p (Release 2010)
5
1
BPSK, QPSK, 16QAM, 64QAM
–
27
802.11ad (Release 2012)
60
2160
BPSK, QPSK, 16QAM, 64QAM
–
6756 (OFDM)
4620 (SC)
2503 (LPSC)
802.11ac (Release 2012)
5
20, 40, 80, 160
BPSK, QPSK, 16QAM, 64QAM, 256QAM
8x8 (Maximum)
6240 (Long GI)
6933 (Short GI)
Atoll can predict radio coverage, evaluate network capacity, and analyse the amount of mobile traffic that can be offloaded
from a mobile (HSPA, LTE, etc.) network to a Wi‐Fi network. Atoll includes advanced traffic offload analysis features that
enable operators to plan and evaluate Wi-Fi-based scenarios for network capacity enhancement.
Wi-Fi Network Model
The Wi-Fi network model comprises radio network elements such as sites, transmitters, and cells. A Wi-Fi access point is
equivalent to a site, its transmitters with one or more radio channels (cells) each.
Figure 14.1 Wi-Fi network model
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14.1.2 Sites
A site represents the physical location where access points can be installed. An example of a site properties window is shown
in the figure below.
Figure 14.2 Site properties window
Site parameters are:




Geographic coordinates
Altitude (user-defined or automatically extracted from the terrain elevation data)
Any user-defined flags and parameters such as address, owner, deployment phase, etc.
The maximum downlink and uplink backhaul throughputs: Backhaul links connect access points to serving gateways.
The backhaul capacity between an access point and its serving gateway imposes a limit on the aggregate throughput
of the users served by the access point. The maximum backhaul throughputs that you enter here can be taken into
account in Monte Carlo simulations as backhaul constraints.
14.1.3 Transmitters
Transmitters in Atoll correspond to sectors and antennas installed at a site. The main transmitter parameters are:











Transmitter name and the name of the site where it is installed
X and Y coordinates
Transmitter type (server and interferer, or interferer only)
Active/inactive (to be included in calculations or not)
Antenna patterns, heights, azimuths, and tilts
Numbers of transmission and reception antennas for MIMO
A flag to indicate antenna sharing with other transmitters
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Any user-defined flags and parameters
An example of a transmitter properties window is shown in the figure below.
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Figure 14.3 Wi-Fi transmitter properties window
14.1.4 Cells
Atoll supports multi-band, multi-carrier Wi-Fi network deployments. In Atoll, cells model frequency channels used at a
transmitter. A transmitter can support cells with different channel bandwidths and different carriers. Each cell has its own
radio resources and parameters, including:

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












Cell name and the name of the transmitter to which the cell belongs
Frequency band and channel number
Cell layer
BSID
AFP parameters: channel status (allocated, locked, etc.) and minimum frequency reuse distance
Transmission power
Minimum C/N
Reception equipment
Frame configuration
AMS thresholds
Maximum number of simultaneous users
Resource allocation constraints: maximum uplink and downlink traffic loads
Cell loads and resource allocation results: uplink and downlink traffic loads, uplink noise rise, numbers of connected
users in downlink and uplink
These parameters can be outputs of Monte Carlo simulations as well as user-defined values.
Neighbour parameters: maximum numbers of neighbours and neighbours lists
Inter-technology interference: downlink and uplink noise rise
Any user-defined flags and parameters
The figure below presents an example of a transmitter with a single cell.
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Figure 14.4 Wi-Fi cell parameters
14.1.5 Site Templates
A site template is made up of one or more transmitters and cells located on the same site. Site templates can be created and
edited as needed. Building a network is facilitated by working with site templates rather than single site/transmitter/cell. By
default some Wi-Fi site templates are available for 802.11g and 802.11n technologies.
Wi-Fi Network Configuration Parameters
Atoll allows setting and modifying network-level configurations and parameters applicable to the entire project.
14.2.1 Frequency Bands and Channels
Atoll supports multi-band Wi-Fi networks. Atoll supports all channel bandwidths and frequency bands supported by Wi-Fi
equipment. A frequency band is characterized by its uplink and downlink frequencies, channel bandwidth, channel numbers,
channel numbering steps, inter-channel spacing, and adjacent channel interference suppression factor. You can add, modify,
and delete frequency bands in Atoll as required. A number of default frequency bands are available by default as shown in
the figure below.
Atoll calculates inter-channel (co- and adjacent channel) interference by determining the co- and adjacent channel overlaps
between channels assigned to cells. The adjacent channel suppression factor is applied to the interference received on the
adjacent channel overlap.
Figure 14.5 Wi-Fi frequency bands table
14.2.2 Frame Configurations
The following Wi-Fi frame configurations are available in Atoll:
802.11a — 20 MHz
802.11g — 20 MHz
802.11n — 20 MHz
802.11n — 20 MHz (HT)
802.11n — 40 MHz
802.11n — 40 MHz (HT)
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Total Number of
Subcarriers
64
64
64
64
128
128
Number of Used
Subcarriers
52
52
52
56
104
114
Number of Data
Subcarriers
48
48
48
52
96
108
Diversity Support
None
None
AMS
AMS
AMS
AMS
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802.11p — 10 MHz
802.11ad — 2.16 GHz (LPSC)
802.11ad — 2.16 GHz (OFDM)
802.11ad — 2.16 GHz (SC)
802.11ac — 20 MHz (VHT)
802.11ac — 40 MHz (VHT)
802.11ac — 80 MHz (VHT)
802.11ac — 160 MHz (VHT)
64
1
512
1
64
128
256
512
52
1
352
1
56
114
242
484
48
1
336
1
52
108
234
468
None
None
None
None
AMS
AMS
AMS
AMS
Frame configurations can be used to define the number of total, used, and traffic subcarriers, the guard interval, and diversity
mode support in downlink and uplink. An example of frame configuration definition is shown in the figure below.
Figure 14.6 Wi-Fi frame configuration properties
14.2.3 Radio Bearers
Wi-Fi radio bearers are used to carry user data on the downlink and uplink traffic channels. A bearer refers to a combination
modulation and coding scheme. The radio bearers table lists the available radio bearers in downlink and uplink. You can add,
remove, and modify bearer properties according to your network and equipment. The figure below shows the default bearers
in Atoll.
Figure 14.7 Default Wi-Fi bearers
14.2.4 Quality Indicators
In Atoll, quality indicators (BER, BLER, etc.) represent the coverage quality at different locations. The quality indicators table
lists the available quality indicators which you can add, remove, and modify as required.
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Wi-Fi Radio Equipment
Atoll provides the option to define various pieces of radio equipment such as antennas and reception equipment. For more
information on common antenna and radio equipment features, see 4 Antenna and Radio Equipment Features.
14.3.1 Reception Equipment and MIMO Gains
Wi-Fi reception equipment model the reception characteristics of cells and user terminals. Bearer selection thresholds,
quality indicator graphs, and MIMO gains are defined in Wi-Fi reception equipment. The figures below give examples of such
an equipment definition.
Figure 14.8 Wi-Fi bearer selection thresholds
Diversity gains as well as SU-MIMO throughput gains can be defined for each equipment for different numbers of transmission
and reception antennas, modulation and coding schemes, and user speeds. The figure below shows the MIMO gains tab.
Figure 14.9 Wi-Fi MIMO gains
Wi-Fi Traffic Model
In Atoll, the radio network traffic is modelled using Monte Carlo simulations. According to the definition of the services and
users in the network, and depending on the traffic cartography (traffic data), realistic distributions of users are generated and
used as input to the scheduling and radio resource management algorithms.
Service and user behaviours are modelled in Atoll through different tables that provide information about:




The services available in the network
The terminals compatible with the network
The mobility types
The user profiles describing the way users access different services
The Wi-Fi traffic model is shown in the figure below.
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Figure 14.10 Wi-Fi traffic model
14.4.2 Services
The services table describes the services that are available in the network. Both voice and data type services are supported
and have specific parameters. The main service parameters are:









Service type
Priority level
Lowest and highest bearers allowed
Uplink and downlink maximum throughput demands
Uplink and downlink minimum throughput demands
Uplink and downlink average requested throughputs
Uplink and downlink activity factors
Throughput conversion parameters from MAC to Application layer
Body loss
An example of a service properties window is presented in the figure below.
Figure 14.11 Service properties window
14.4.3 Terminals
The terminals table describes the terminals that can be used in the network, cell phones, smartphones, in-car navigation
devices, etc. The following parameters model a terminal:







Minimum and maximum transmission powers
Noise figure
Transmission and reception loss
Reception equipment
UE category
Antenna pattern
Antenna gain
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
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Diversity support
Numbers of MIMO antennas
Atoll enables you to assign directional antennas to different terminals and define whether the terminal supports MIMO. The
antenna patterns are used in coverage predictions and Monte Carlo simulations. An example of a terminal properties window
is given in the figure below.
Figure 14.12 Terminal properties window
14.4.4 Mobility Types
The mobility type defines different user speeds.
14.4.5 User Profiles
The user profiles table models the behaviour of the different user categories. Every user profile contains a list of services and
their associated parameters describing how these services are accessed by the users.
Parameters for voice services are:



The average number of calls per hour
The average duration of each call
The terminal used when requiring access to this service.
Parameters for data services are:




The average number of sessions per hour
The data volume transferred on the downlink during each session
The data volume transferred on the uplink during each session
The terminal used when requiring access to this service.
The figure below shows a user profile window.
Figure 14.13 User profile window
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14.4.6 Traffic Data
For information on traffic data cartography, see 2.2.7 Traffic Data.
Wi-Fi Monte Carlo Simulations
The radio resource management and scheduling algorithms in a Wi-Fi network automatically perform resource allocation to
users. Atoll simulates this resource allocation mechanism. It calculates, for each user distribution (called a random trial), the
different network parameters such as the mobile activity, received power, antenna diversity mode, interference, C/(I+N),
best radio bearer available for the calculated C/(I+N), required resources to satisfy the minimum and maximum throughput
demands, and user throughputs (peak MAC, effective MAC, and application-level) after the allocation of resources by the
scheduler. As outputs, Atoll provides the traffic loads which can then be assigned to the different cells and the C/(I+N)
coverage can be performed based on realistic simulation results.
Moreover, traffic from a mobile network (HSPA, LTE, etc.) can be offloaded to Wi-Fi access points. This aspect of multi-layer
multi-technology network capacity analysis, and the impact of adding a layer of Wi-Fi hot spots on top of a mobile network
is fully modelled in Atoll. This enables operators to plan and evaluate Wi-Fi-based scenarios for network capacity
enhancement. For more information on mobile traffic offloading to Wi-Fi, see 14.10 Wi-Fi Co-planning With Mobile Radio
Access Technologies.
A Monte Carlo simulation in Atoll corresponds to a given distribution of users. It is a snapshot of a Wi-Fi network.
Wi-Fi Monte Carlo simulations can be analysed, displayed and stored. They can be used in a next step to generate numerous
coverage predictions.
14.5.1 Generation of Realistic User Distributions
Realistic distributions of users on the map are required as inputs to the Wi-Fi simulation algorithm. A “Realistic User
Distribution” corresponds to a user distribution that complies with the service and user model and the traffic data. Atoll
generates these user distributions using a Monte Carlo (statistical) algorithm.
14.5.2 Scheduling and Radio Resource Management
For each user distribution, Atoll simulates the scheduling and RRM mechanism of Wi-Fi access points. The simulation ends
when the scheduler has allocated resources to all the users selected for the scheduling process and has determined the traffic
loads for all the cells in the simulation.
The figure below shows an overview of the simulation algorithm.
Figure 14.14 Wi-Fi simulation overview
The following steps are carried out during each iteration of a Wi-Fi Monte Carlo simulation for all the generated mobiles:
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Best server determination: Atoll determines the best server for each mobile based on the signal level in the
downlink. If more than one cell cover the mobile, the one with the highest layer is selected as the serving cell.
Users can be rejected at this stage for "No Coverage".

Downlink calculations: The downlink calculations include the calculation of C/(I+N), determination of the best
available bearer for the C/(I+N), allocation of resources (RRM), and calculation of user throughputs.
Users can be rejected at this stage for "No Service".

Uplink calculations: The uplink calculations include the calculation of C/(I+N), determination of the best available
bearer for the C/(I+N), resource allocation (RRM), update of uplink noise rise values for cells, and calculation of user
throughputs.
Users can be rejected at this stage for "No Service".

Radio resource management and cell load calculation: Atoll uses an intelligent scheduling algorithm to perform
radio resource management.
Users can be rejected at this stage for "Scheduler Saturation," "Resource Saturation," or “Backhaul Saturation.”
Main simulation outputs are:


The cell loads (i.e., uplink and downlink traffic loads, uplink noise rise), and
User throughputs.
Note that numerous other parameters are available and stored during the simulation for further analysis. For more
information, see 14.5.5 Simulation Reports.
14.5.3 Monte Carlo Simulation Management
Wi-Fi simulations are managed through the Simulations folder in the Atoll Explorer window. This folder is displayed in the
figure below.
Figure 14.15 Wi-Fi simulations folder
The Simulations folder is made up of several simulation “groups”. Each group corresponds to a network configuration for
which a user-specified number of Monte Carlo simulations have been generated. As an example, different groups may
correspond to different traffic assumptions. The figure below shows the simulation creation dialog box.
When several simulation groups are available, it is possible to automatically display one group after the other, hence
animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
The following information is required when creating a new group of Monte Carlo simulations:





The simulation group name
The number of simulations to be run
The load and backhaul constraints to apply during simulations
The traffic maps used
The convergence criteria.
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Figure 14.16 Wi-Fi simulation creation dialog box
Once a simulation (or a group of simulations) has been performed, simulation reports are available and simulation results can
be graphically analysed in Atoll.
14.5.4 Simulation Graphical Analysis
Graphical Display: Mobile Connection Status
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for their connection status. The different possible statuses are:






Connected DL + UL: the mobile is connected on both downlink and uplink
Connected UL: the mobile is connected on uplink only
Connected DL: the mobile is connected on downlink only
Scheduler Saturation: the mobile is rejected because the scheduler has reached its maximum limit
Resource Saturation: the mobile is rejected because all the resources have been allocated to other mobiles
No Service: the mobile is rejected because it is outside the coverage area.
An example of a graphical display of a group of simulations is presented in the figure below.
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Figure 14.17 Wi-Fi simulation display by connection status
Individual Mobile Results Graphical Display
Parameters for any user can be displayed either in the results table or directly on the map (as presented in the figure below).
Figure 14.18 Individual mobile results display using the tool tip
14.5.5 Simulation Reports
Atoll provides detailed simulation results in the form of reports.
Reports of a Single Simulation
A report is available for each simulation. This report contains information about the simulation statistics, and calculation
results by sites, cell, and mobile as given in the figure below.
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Figure 14.19 Wi-Fi simulation report
The simulation results are provided at the following different levels:

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
Global statistics: total users attempting a connection and the corresponding break-up per service; total users
actually connected and the corresponding break-up per service.
Results per site: sum of user throughputs (peak MAC, effective MAC, and application level throughputs) for all the
cells of a site, globally and per service type, for both uplink and downlink and numbers of rejected mobiles per
rejection cause.
Results per cell: uplink and downlink traffic loads, uplink noise rise, sum of user throughputs (peak MAC, effective
MAC, and application level throughputs), for both uplink and downlink, numbers of rejected mobiles per rejection
cause.
Results per mobile: geographic location, receiver height, terminal type, service, user profile, mobility, activity status
(DL/UL), serving cell, path loss, received power levels, uplink transmit power, channel and user throughputs (peak
MAC, effective MAC, and application throughputs), connection status (connected in DL, UL, DL+UL, or rejected due
to no service, scheduler saturation or resource saturation), C/(I+N) and interference levels, antenna diversity
modes, bearer, BLER, etc.
Initial conditions: parameters and traffic maps used to create the simulation.
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Reports of a Group of Simulations
Atoll provides detailed simulation results averaged over a group of simulations in the form of reports. The report generated
for a simulation group contains:




Statistics: average statistics obtained from the results of all the simulations in a group
Results per site: average site results obtained from the results of all the simulations in a group
Results per cell: average cell results obtained from the results of all the simulations in a group
Initial conditions: parameters used to create the simulation group.
Figure 14.20 Wi-Fi simulation group report
14.5.6 Updating Cell Loads
You can store the cell loads calculated by Monte Carlo simulations in the cells data table. This enables you to update the
network cell loads based either on the average results from a simulation group or the results of from a single simulation. Cell
load values for all the cells in the network radio database are then updated with the results generated by the selected
simulation. Cell loads from a simulation, simulation group, or from the cells data table can then be used to generate coverage
prediction plots.
14.5.7 Exporting Results
You can export the simulation results as described in 2.5.1 Network Data Import and Export.
Wi-Fi Coverage Predictions
In Atoll a coverage prediction is a plot displaying calculation results of user-selected parameters on the map and enabling
graphical as well as statistical analysis of the network behaviour. Examples of Wi-Fi coverage predictions are signal level,
signal quality, radio bearer, throughput plots, etc. For each pixel, Atoll calculates the required information. This data is then
graphically represented by a colour according to a user-defined legend. Different display options are available in Atoll,
depending on the calculated parameter.
14.6.1 Coverage Prediction Calculation and Management
Coverage predictions are performed by assuming a “probe mobile” (non-interfering terminal) on each pixel of the considered
area. The probe mobile characteristics (terminal type, mobility type, service type) are specified as inputs to the coverage
prediction in order to calculate the user-defined prediction parameter.
Predictions are stored as multi-layer geographic objects in the Predictions folder of the Explorer window and can be displayed
in the map window. When several coverage predictions are available, it is possible to automatically display one prediction
after the other, hence animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
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Subfolders can be created in the Predictions folder in order to group various coverage prediction objects into categories.
Coverage predictions can be directly created under a subfolder and moved from one subfolder to another using the mouse.
14.6.2 Coverage Prediction Types
Wi-Fi coverage predictions can be generated either based on the results from Monte Carlo simulations or on user-defined
cell load configurations.
Wi-Fi coverage prediction types and their display options available in Atoll are listed below.


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


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

Coverage by transmitter (DL)
o Transmitter
Coverage by signal level (DL)
o Signal level (dBm, dBµV or dBµV/m)
o Path loss (dB)
Overlapping zones (DL)
o Number of servers
Effective signal analysis (DL)
o Downlink signal level and C/N
Effective signal analysis (UL)
o Uplink signal level and C/N
Coverage by C/(I+N) level (DL)
o Downlink total noise (I+N) and C/(I+N)
Coverage by C/(I+N) level (UL)
o Uplink total noise (I+N) and C/(I+N)
o Uplink transmission power
Service area analysis (DL)
o Bearer
o Modulation
Service area analysis (UL)
o Bearer
o Modulation
Effective service area analysis (DL + UL)
Coverage by throughput (DL)
o Peak MAC, effective MAC, and application channel throughput
o Peak MAC, effective MAC, and application cell capacity
o Aggregate peak MAC, effective MAC, and application cell throughput
o Peak MAC, effective MAC, and application throughput per user
Coverage by throughput (UL)
o Peak MAC, effective MAC, and application channel throughput
o Peak MAC, effective MAC, and application cell capacity
o Aggregate peak MAC, effective MAC, and application cell throughput
o Peak MAC, effective MAC, and application throughput per user
Coverage by quality indicator (DL)
o BER, BLER, etc.
Coverage by quality indicator (UL)
o BER, BLER, etc.
The first five coverage predictions (coverage by transmitter, coverage by signal level, overlapping zones, and effective signal
analyses) are not based on interference, hence neither require cell load information nor Monte Carlo simulations. The
remaining coverage predictions depend on the network’s behaviour under load. These predictions can be calculated for a
service, mobility type, and user terminal equipment.
Various Wi-Fi coverage prediction plots are shown in the figures below.
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Figure 14.21 Wi-Fi access point coverage
Figure 14.22 Wi-Fi coverage by signal level
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Figure 14.23 Wi-Fi coverage by C/(I+N) level
Figure 14.24 Wi-Fi coverage by throughput
14.6.3 Coverage Prediction Reports
Atoll can generate reports for one or more coverage predictions with various detail levels as defined by the user. Reports are
spread sheet-like tables that can be printed directly from Atoll or exported to any desktop tool. An example of such a report
is given in the figure below.
Figure 14.25 Wi-Fi coverage prediction report
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14.6.4 Coverage Prediction Comparison
Comparison (difference, intersection, union, or merge) between two coverage predictions can be performed. As examples,
this functionality can be used:



To compare uplink and downlink coverage of a service. This enables you to determine uplink/downlink-limited
zones for that service.
To compare service area coverage plots of two different services. This enables you to assess the areas where one
service (e.g., VoIP) is available while the other (e.g., high speed internet) is not.
To compare service area coverage plots of two networks deployment scenarios (possibly with different
technologies). The figure below illustrates such a case by comparing LTE and Wi-Fi coverage.
Figure 14.26 Coverage prediction graphical comparison (LTE versus Wi-Fi example)
Atoll also enables you to carry out per-pixel arithmetical operations between coverage predictions. For example, you can
calculate the sum, difference, min, max, and average of similar calculated parameters per pixel from two coverage predictions
of the same or different technologies.
14.6.5 Coverage Prediction Export
Any coverage prediction can be exported in the following formats:











Atoll format
ArcView SHP
MapInfo MIF and TAB
ArcView Grid TXT and ASC
Vertical Mapper GRD and GRC
BMP
PNG
TIFF
BIL
JPEG2000
JPEG
When exported in MapInfo format, coverage prediction attributes (e.g., signal levels, transmitter IDs, etc.) are exported along
with the plot. The figure below gives an example of the exported attributes for a C/(I+N) prediction.
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Figure 14.27 Wi-Fi coverage prediction attributes export to MapInfo
14.6.6 Point Analysis Tool
A real-time prediction analysis tool is available in Atoll. The point analysis tool is dynamically linked to the map window. The
displayed information is updated as the receiver is moved on the map window. The point analysis tool provides the downlink
signal values numerically and graphically for all cells and for the selected terminal type, mobility type, and service type.
Based on user-defined or calculated cell load values, the point analysis tool also provides numeric values of signal levels and
signal quality, downlink and uplink bearers, and downlink and uplink throughput values.
The figure below shows the point analysis window as well as its link to the map window.
Receiving
mobile
Received
signal
strength
Figure 14.28 Wi-Fi point-to-point real-time analysis
14.6.7 Multi-Point Analysis
Atoll enables you to carry out point predictions on multiple point locations and at different heights. Multi-point analyses can
be carried out on subscriber locations from fixed subscriber traffic maps and points created on the map using the mouse.
Multi-point analyses may be useful in verifying network QoS at specific locations in case of reported incidents such as call
drops, low throughputs, etc. Multi-point analysis calculations can be based on user-defined network load conditions in the
Cells table or loads calculated using Monte Carlo simulations. Fixed subscriber analysis results include detailed results for the
subscriber’s best server. These results are similar to the results provided by a Monte Carlo simulation.
Multi-point analysis results are stored in the Multi-Point Analysis folder in the Network explorer. Once calculated, multi-point
analysis results are available in tabular form and visible on the map using symbols and colours based on calculation results.
You can export the multi-point analysis results as described in 2.5.1 Network Data Import and Export.
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Wi-Fi Neighbour Planning
Atoll supports the following neighbour types in a Wi-Fi network configuration:
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Intra-technology neighbours: Wi-Fi cells defined as neighbours of other Wi-Fi cells in the same Atoll document.
Inter-technology neighbours: Wi-Fi cells defined as neighbours of cells which use a technology other than Wi-Fi.
Neighbour plans can be generated by any of the following means in Atoll:
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Importing an external neighbour plan (e.g., in Excel format)
Automatically producing a neighbour plan as described in 14.7.1 Automatic Neighbour Allocation
Graphically and/or manually creating, editing and deleting a neighbour plan as presented in 14.7.2 Graphical
Neighbour Plan Editing
Various neighbour plans can be compared. The results of an automatic neighbour allocation can be compared with the
existing neighbour plan. As well, neighbour plans from external sources can also be compared with the existing neighbour
plan in Atoll.
14.7.1 Automatic Neighbour Allocation
Neighbour lists can be generated automatically in Atoll. For each cell, potential neighbours are ranked according to their
importance. The neighbour planning algorithm considers the following user-specified parameters:
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Hysteresis zone defined by a handover start and a handover end margin with respect to the best server signal
strength
Maximum inter-site distance
Maximum number of neighbours
Minimum area covered (overlapping area between the reference cell and its potential neighbour).
Importance ranges for distance, coverage, adjacency, and co-site factors.
Forcing “neighbour symmetry”, “adjacent cells as neighbours”, “co-site cells as neighbours“ and/or “exceptional neighbour
pairs” is possible with Atoll. The figure below displays the automatic neighbour allocation dialog box.
Figure 14.29 Wi-Fi automatic neighbour list generation
14.7.2 Graphical Neighbour Plan Editing
Neighbour plan can be graphically edited in Atoll. Clicking a transmitter on the map displays all its neighbour relations. All
types of neighbour relations (outwards, inwards or symmetrical) can be created, edited and/or deleted graphically.
14.7.3 Neighbour Consistency Check Tool
A neighbour relation audit is available in Atoll. This function enables you to determine inconsistencies in the current
neighbour plan. The figure below shows the neighbour relation conditions that can be verified using the audit.
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Figure 14.30 Neighbour audit
Wi-Fi Automatic Frequency Planning
The Atoll Wi-Fi AFP (Automatic Frequency Planning module) enables you to automatically configure frequency channels in a
multi-carrier Wi-Fi network supporting dynamic channel selection (DCS). The aim of the AFP is to allocate frequencies in a
way that minimises interference following the user‐defined constraints. The AFP assigns a cost to each constraint and then
uses an iterative algorithm to evaluate possible allocation plans and propose the allocation plan with the lowest costs. The
AFP cost function comprises input elements such as interference matrices, neighbour relations, and allowed ranges of
resources for allocation.
The figure below presents the Wi-Fi AFP window.
Figure 14.31 Wi-Fi AFP
14.8.2 AFP Cost Components
The AFP cost components include relations and constraints. The AFP’s automatic planning algorithm can take the following
relations into account:
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Interference-based relations, i.e., cells that interfere each other
The probability of interference is extracted from interference matrices. One or more interference matrices can be
calculated using Atoll or imported from external files in standard TXT, CSV, and IM2 formats, in order to provide
the AFP with:
o The co-channel interference probability
o The adjacent channel interference probability
Neighbour cells
The importance of each neighbour relation is determined from the neighbour relation definition.
Inter-cell distance
A minimum reuse distance can be defined per cell or globally for all the cells.
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For automatic frequency allocation, the AFP can take into account the frequency channel collision and overlap.
The impact of each relation and constraint can be fine-tuned by the user by defined the associated weights. The figure below
shows the AFP constraint weights dialog box.
Figure 14.32 User-defined AFP constraint weights
14.8.3 Automatic Frequency Planning
Atoll enables you to assign frequency channels manually or automatically to any cell in the network. Atoll facilitates the
management of frequency bands and channels by letting you define these as needed. Atoll can automatically assign frequency
channels to cells taking into account the allowed frequency channels, interference matrices, reuse distance, and any
constraints imposed by neighbours.
Once the allocation is complete, you can implement the proposed allocation plan, export the results to TXT, CSV, or XML
spread sheet files, audit the frequencies, analyse frequency reuse and interference on the map, and make an analysis of
frequency distribution.
Figure 14.33 Wi-Fi frequency planning
Figure 14.34 Wi-Fi frequency audit
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14.8.1 Frequency Plan Analysis
Frequency Search Tool
A search tool is available in Atoll which enables you to search for frequencies. You can display the current allocation plan of
the selected parameter on the map and highlight the transmitters and their coverage areas respectively.
Frequency Display on Map
You can display the frequency allocation on transmitters by using the transmitters’ display settings.
Wi-Fi Automatic Cell Planning
The Atoll Wi-Fi ACP (Automatic Cell Planning) module enables you to automatically determine the best Wi-Fi parameter
settings for your network. The aim of the Atoll ACP is to improve network quality in terms of both coverage and capacity. For
a comprehensive description of the Atoll ACP, see 17 Automatic Cell Planning (ACP) Features.
.
The Atoll Wi-Fi ACP is capable of optimising network parameters (antenna types, heights, azimuths, tilts, transmission powers,
etc.) based on the following Wi-Fi quality indicators:
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Signal level
C
C/N
CINR
Overlap
Best server distance
1st-Nth difference
Wi-Fi Co-planning With Mobile Radio Access Technologies
Atoll is a multi-technology radio network planning and optimisation software. You can work on several technologies at the
same time, for example, you can design an LTE and a Wi-Fi network for a given area in Atoll, and then use Atoll’s co-planning
features to study the mutual impacts of the two networks. For more information, see 11 Multi-RAT Features.
Atoll enables you to carry out analyses of mobile traffic offloading to Wi-Fi. In other words, you can carry out network capacity
analyses of your mobile network alone and with Wi-Fi deployed as an additional layer to carry a part of your mobile network
traffic.
Atoll provides an efficient and accurate means to analyse and compare the behaviour of your mobile network with and
without a Wi-Fi network layer on top. Atoll’s combined mobile/Wi-Fi Monte Carlo simulations make it possible to compare
different traffic balancing and offloading scenarios. As an example, if you wish to analyse the increase in your LTE network
capacity due to Wi-Fi using Atoll, you can run LTE-only and LTE/Wi-Fi Monte Carlo simulations.
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Figure 14.35 Analysis of network capacity enhancement with mobile-to-Wi-Fi traffic offloading
Atoll’s Monte Carlo simulation results provide comprehensive network capacity analysis details including the amount of
served and blocked traffic in terms of the number of users as well as aggregate throughputs. A side-by-side comparison of
the two simulation results provides you with key information, such as the number of mobile users served by Wi-Fi and the
aggregate throughput over the Wi-Fi hotspots, clearly representing the increase in the overall network capacity due to Wi-Fi
compared to a pure LTE mobile network.
The figure below illustrates the effect of mobile traffic offloading to Wi-Fi. Mobiles compatible with Wi-Fi and covered by WiFi are connected to Wi-Fi access points until radio resources are available. Mobiles not connected to Wi-Fi, due to
incompatibility, limited coverage, or resource saturation, fall back to the LTE mobile network layer.
Figure 14.36 Example of combined mobile/Wi-Fi Monte Carlo simulation results
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15 WiMAX Features
The Atoll WiMAX/BWA module provides a comprehensive and accurate modelling of multi-band WiMAX and Wi-Fi networks.
It supports all WiMAX and Wi-Fi frequency bands and carrier widths along with detailed frame structure modelling for both
technologies. All downlink and uplink permutation zones and subchannel allocation modes are fully modelled. Atoll
WiMAX/BWA also includes comprehensive modelling of different MIMO techniques (diversity, SU-MIMO, MU-MIMO) and
beamforming smart antennas.
Atoll supports all modulation and coding schemes, QoS classes, voice, VoIP, and data services, and different user equipment.
Atoll provides the means to set up multi-service traffic maps from multiple sources: vector, raster and live traffic data. Traffic
maps are used in WiMAX and Wi-Fi Monte Carlo simulations for network capacity analysis including RRM, scheduling, and
backhaul constraints. Fractional frequency reuse modelling is available for analysing the improved quality due to interference
coordination in co-channel deployments. Coverage predictions can be calculated based on Monte Carlo simulation results or
on live network loads from the OMC in order to study coverage and capacity of the network.
Atoll includes automatic inter- and intra-carrier neighbour planning features that allow analysing handovers in the network.
Atoll can work with multiple interference matrices from various sources: prediction-based (calculated within Atoll), based on
OMC statistics, and based on drive test measurements. The Atoll WiMAX AFP can automatically allocate frequencies,
preamble indexes, segments, and permbases on user-definable constraints and costs. Analysis tools enabling auditing of
frequency and preamble index plans are also available.
The Atoll WiMAX ACP can be used to automatically optimise network parameters to increase coverage and capacity. It can
also carry out site selection for greenfield and site activation for densification scenarios.
An overview of the WiMAX modelling in Atoll is shown in the figure below.
Figure 15.1 WiMAX network modelling in Atoll
WiMAX Network Model
The WiMAX network model comprises radio network elements such as sites, transmitters, and cells. A WiMAX base station
is equivalent to a site, its transmitters with one or more radio channels (cells) each.
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Figure 15.2 WiMAX network model
15.2.1 Sites
A site represents the physical location where base stations can be installed. An example of a site properties window is shown
in the figure below.
Figure 15.3 Site properties window
Site parameters are:
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Geographic coordinates
Altitude (user-defined or automatically extracted from the terrain elevation data)
Any user-defined flags and parameters such as address, owner, deployment phase, etc.
The maximum downlink and uplink backhaul throughputs: Backhaul links connect sites to serving gateways. The
backhaul capacity between a site and its serving gateway imposes a limit on the aggregate throughput served by
the cells of the same site. This also imposes a limit on the throughput of each individual user served. The maximum
backhaul throughputs that you enter here can be taken into account in Monte Carlo simulations as backhaul
constraints.
15.2.2 Transmitters
Transmitters in Atoll correspond to sectors and antennas installed at a site. The main transmitter parameters are:
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Transmitter name and the name of the site where it is installed
X and Y coordinates
Transmitter type (server and interferer, or interferer only)
Active/inactive (to be included in calculations or not)
Main, secondary, and smart antennas
Numbers of transmission and reception antennas for MIMO
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other transmitters
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Tower mounted amplifier (TMA)
Feeder type and its transmission and reception lengths
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Any user-defined flags and parameters
An example of a transmitter properties window is shown in the figure below.
Figure 15.4 WiMAX transmitter properties window
15.2.3 Cells
Atoll supports multi-band, multi-carrier WiMAX network deployments. In Atoll, cells model frequency channels used at a
transmitter. A transmitter can support cells with scalable channel bandwidths and different carriers. Each cell has its own
radio resources and parameters, including:
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Cell name and the name of the transmitter to which the cell belongs
Frequency band and channel number
Cell layer
BSID, preamble index, segment cell permbase, uplink and downlink zone permbases
AFP parameters: channel status (allocated, locked, etc.) and preamble index status (allocated, locked, etc.),
segment locked/unlocked, preamble index domain, minimum frequency and preamble index reuse distance
Transmission powers: preamble power with traffic and pilot power reduction offsets
Minimum preamble C/N
Reception equipment
Frame configuration
AMS & MU-MIMO thresholds
RRM parameters: scheduler type, maximum number of simultaneous users
Resource allocation constraints: maximum uplink and downlink traffic loads
Cell loads and resource allocation results: uplink and downlink traffic loads, uplink noise rise, segmentation usage,
segmented zone uplink noise rise, AAS usage, angular distribution of uplink noise rise, MU-MIMO capacity gain,
numbers of connected users in downlink and uplink
These parameters can be outputs of Monte Carlo simulations as well as user-defined values.
Inter-technology interference: downlink and uplink noise rise
Neighbour parameters: maximum numbers of neighbours and neighbours lists
Any user-defined flags and parameters
The figure below presents an example of a transmitter with a single cell.
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Figure 15.5 WiMAX cell parameters
15.2.4 Site Templates
A site template is made up of one or more transmitters and cells located on the same site. Site templates can be created and
edited as needed. Building a network is facilitated by working with site templates rather than single site/transmitter/cell. By
default some WiMAX site templates are available for dense urban, urban, suburban, and rural environments.
15.2.5 Repeaters
A repeater receives, amplifies, and retransmits signals. Repeaters are used to extend the coverage of their donors. Atoll
models selective as well as non-selective RF repeaters, optic fibre repeaters, microwave repeaters, and remote antennas.
Selective RF repeaters only repeat signals from their donor transmitters whereas non-selective RF repeaters receive and
retransmit wanted signals as well as interference.
The main parameters of a repeater are:
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Donor transmitter name
X and Y coordinates
Active/inactive (to be included in calculations or not)
Main and secondary antennas
Antenna heights, azimuths, and tilts
A flag to indicate antenna sharing with other repeaters
Total gain
Amplifier gain
Transmission and reception losses
Noise figure in reception
Main and extended propagation models, path loss calculation radii and resolutions (for more information, see 2.4
Propagation Models)
Feeder type and its transmission and reception lengths
Any user-defined flags and parameters
The figure below presents the repeater properties window while the figure below that gives an example of a best server
prediction plot with a repeater.
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Figure 15.6 Repeater properties window
RF repeater
Donor transmitter
Figure 15.7 RF repeater coverage plot
WiMAX Network Configuration Parameters
Atoll allows setting and modifying network-level configurations and parameters applicable to the entire project.
15.3.1 Frequency Bands and Channels
Atoll supports multi-band FDD and TDD WiMAX networks. Atoll supports all channel bandwidths and frequency bands
supported by WiMAX equipment. A frequency band is characterized by its uplink and downlink frequencies, channel
bandwidth, channel numbers, channel numbering steps, inter-channel spacing, adjacent channel interference suppression
factor, sampling factor, and the duplexing method. You can add, modify, and delete frequency bands in Atoll as required. A
number of default frequency bands are available by default as shown in the figure below.
Atoll calculates inter-channel (co- and adjacent channel) interference by determining the co- and adjacent channel overlaps
between channels assigned to cells. The adjacent channel suppression factor is applied to the interference received on the
adjacent channel overlap.
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Figure 15.8 WiMAX frequency bands table
The figure below shows the different available frequency bands for WiMAX and Wi-Fi world-wide.
Figure 15.9 Licensed/Unlicensed WiMAX / Wi-Fi Frequency Bands
15.3.2 Global Network Settings
WiMAX-specific parameters that are applicable to the entire network are modelled in Atoll as global network settings. These
parameters include frame structure parameters such as the frame duration, the cyclic prefix, and the downlink and uplink
overheads for preamble, DL-MAP, and UL-MAP. This also enables modelling TDD-specific parameters for defining the
proportion of downlink and uplink subframes within a WiMAX frame, and the transmit time guard (TTG) and receive time
guard (RTG).
Other advanced options are also available for setting the best server, serving cell, and permutation zone selection methods,
adaptive MIMO switching criterion, and interference calculation method, etc. The figure below presents the network level
properties dialog box.
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Figure 15.10 WiMAX network level parameters
15.3.3 Frame Configurations
Channel and frame structure parameters for different channel bandwidths are modelled through frame configurations. Each
frame configuration has a number of total subcarriers per channel, a number of preamble subcarriers, a cyclic prefix ratio,
can contain more than one permutation zone, and can perform segmentation (Fractional Frequency Reuse) using the PUSC
permutation zones in downlink and uplink. The frame configurations table is shown in the figure below.
Figure 15.11 WiMAX frame configuration properties
Each permutation zone in a frame configuration can be assigned a different subchannel allocation mode, numbers of data
and used subcarriers, numbers of subchannels per channel, quality thresholds, priority, and diversity mode support. Atoll
supports all subchannel allocation modes defined in the IEEE 802.16 specifications, i.e., PUSC, FUSC, OPUSC, OFUSC, AMC,
TUSC1, and TUSC2. Segmentation (fractional frequency reuse) is modelled using the primary and secondary subchannel
groups for the PUSC DL permutation zone. The figure below shows the properties of different permutation zones in a frame
configuration.
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Figure 15.12 WiMAX permutation zones
15.3.4 Radio Bearers
WiMAX radio bearers are used to carry user data on the downlink and uplink traffic channels. A bearer refers to a combination
modulation and coding scheme. The radio bearers table lists the available radio bearers in downlink and uplink. You can add,
remove, and modify bearer properties according to your network and equipment. The figure below shows the default bearers
in Atoll.
Figure 15.13 Default WiMAX bearers
15.3.5 Schedulers
In Atoll, schedulers perform the allocation and management of radio resources according to the QoS classes of the services
being accessed by the selected users. Various scheduling methods are available in Atoll, including proportional fair, round
robin, QoS biased, etc., as well as the support for multi-user diversity gains specific to proportional fair schedulers.
Figure 15.14 Default WiMAX schedulers
15.3.6 Quality Indicators
In Atoll, quality indicators (BER, BLER, etc.) represent the coverage quality at different locations. The quality indicators table
lists the available quality indicators which you can add, remove, and modify as required.
WiMAX Radio Equipment
Atoll provides the option to define various pieces of radio equipment such as antennas, transmitter equipment, feeders,
tower mounted amplifiers, reception equipment, smart antenna equipment, etc. For more information on common antenna
and radio equipment features, see 4 Antenna and Radio Equipment Features.
15.4.1 Reception Equipment and MIMO Gains
WiMAX reception equipment model the reception characteristics of cells and user terminals. Bearer selection thresholds,
quality indicator graphs, and MIMO gains are defined in WiMAX reception equipment. The figures below give examples of
such an equipment definition.
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Figure 15.15 WiMAX bearer selection thresholds
Figure 15.16 WiMAX quality indicator graphs
Diversity gains as well as SU-MIMO throughput gains can be defined for each equipment for different numbers of transmission
and reception antennas, modulation and coding schemes, and user speeds. The figures below show the MIMO gains tabs.
Figure 15.17 Traffic MIMO gains
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Figure 15.18 Preamble diversity gains
15.4.2 Smart Antenna Equipment
Atoll includes two beamforming smart antenna models that support linear adaptive array systems that work by forming
beams in the direction of the served mobiles. The conventional beamformer performs beamforming in downlink and uplink.
The optimum beamformer performs beamforming in downlink, and beamforming and interference cancellation in the uplink
using an MMSE (Minimum Mean Square Error) algorithm. Smart antenna models dynamically calculate and apply weights on
each antenna element in order to create beams in the direction of served users. In uplink, the Minimum Mean Square Error
algorithm models the effect of null steering towards interfering mobiles.
Smart antenna equipment models adaptive antenna array systems with more than one antenna element. The beamforming
smart antenna model also supports cross-polar diversity. Smart antenna gains can be fine-tuned with user-defined gain
offsets per clutter class.
The figures below shows a smart antenna properties window and the smart antenna calculation results, i.e., the angular
distribution of interference, output by Atoll’s Monte Carlo simulations.
Figure 15.19 Smart antenna properties
Figure 15.20 Angular distribution of interference from smart antennas
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WiMAX Traffic Model
In Atoll, the radio network traffic is modelled using Monte Carlo simulations. According to the definition of the services and
users in the network, and depending on the traffic cartography (traffic data), realistic distributions of users are generated and
used as input to the scheduling and radio resource management algorithms.
Service and user behaviours are modelled in Atoll through different tables that provide information about:
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The services available in the network
The terminals compatible with the network
The mobility types
The user profiles describing the way users access different services
The WiMAX traffic model is shown in the figure below.
Figure 15.21 WiMAX traffic model
15.5.1 Services
The services table describes the services that are available in the network. Both voice and data type services are supported
and have specific parameters. The main service parameters are:
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Service type
Priority level
QoS class (UGS, rtPS, ErtPS, nrtPS, or BE),
Lowest and highest bearers allowed
Uplink and downlink maximum throughput demands
Uplink and downlink minimum throughput demands
Uplink and downlink average requested throughputs
Uplink and downlink activity factors
Throughput conversion parameters from MAC to Application layer
Body loss
An example of a service properties window is presented in the figure below.
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Figure 15.22 Service properties window
15.5.2 Terminals
The terminals table describes the terminals that can be used in the network, cell phones, smartphones, in-car navigation
devices, etc. The following parameters model a terminal:
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Minimum and maximum transmission powers
Noise figure
Transmission and reception loss
Reception equipment
UE category
Antenna pattern
Antenna gain
Diversity support
Numbers of MIMO antennas
Atoll enables you to assign directional antennas to different terminals, and define whether the terminal supports MIMO and
beamforming. The antenna patterns are used in coverage predictions and Monte Carlo simulations. An example of a terminal
properties window is given in the figure below.
Figure 15.23 Terminal properties window
15.5.3 Mobility Types
The mobility type defines different user speeds.
15.5.4 User Profiles
The user profiles table models the behaviour of the different user categories. Every user profile contains a list of services and
their associated parameters describing how these services are accessed by the users.
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Parameters for voice services are:
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The average number of calls per hour
The average duration of each call
The terminal used when requiring access to this service.
Parameters for data services are:
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The average number of sessions per hour
The data volume transferred on the downlink during each session
The data volume transferred on the uplink during each session
The terminal used when requiring access to this service.
The figure below shows a user profile window.
Figure 15.24 User profile window
15.5.5 Traffic Data
For information on traffic data cartography, see 2.2.7 Traffic Data.
WiMAX Monte Carlo Simulations
The radio resource management and scheduling algorithms in a WiMAX network automatically perform the best suitable
resource allocation to users. The objective is to optimise the resource usage within cells according to the C/(I+N) conditions
at user locations. Atoll simulates this resource allocation mechanism. It calculates, for each user distribution (called a random
trial), the different network parameters such as the mobile activity, received power, permutation zone, antenna diversity
mode used, interference, C/(I+N), best radio bearer available for the calculated C/(I+N), required resources to satisfy the
minimum and maximum throughput demands, and user throughputs (peak MAC, effective MAC, and application-level) after
the allocation of resources by the scheduler. As outputs, Atoll provides the traffic loads which can then be assigned to the
different cells and the C/(I+N) coverage can be performed based on realistic simulation results.
A Monte Carlo simulation in Atoll corresponds to a given distribution of users. It is a snapshot of a WiMAX network.
WiMAX Monte Carlo simulations can be analysed, displayed and stored. They can be used in a next step to generate numerous
coverage predictions.
15.6.1 Generation of Realistic User Distributions
Realistic distributions of users on the map are required as inputs to the WiMAX simulation algorithm. A “Realistic User
Distribution” corresponds to a user distribution that complies with the service and user model and the traffic data. Atoll
generates these user distributions using a Monte Carlo (statistical) algorithm.
15.6.2 Scheduling and Radio Resource Management
For each user distribution, Atoll simulates the scheduling and RRM mechanism of WiMAX cells. The simulation ends when
the scheduler has allocated resources to all the users selected for the scheduling process and has determined the traffic loads
for all the cells in the simulation.
The figure below shows an overview of the simulation algorithm.
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Figure 15.25 WiMAX simulation overview
The following steps are carried out during each iteration of a WiMAX Monte Carlo simulation for all the generated mobiles:

Best server determination: Atoll determines the best server for each mobile based on the preamble signal level in
the downlink. If more than one cell cover the mobile, the one with the highest layer is selected as the serving cell.
Users can be rejected at this stage for "No Coverage".

Downlink calculations: The downlink calculations include the calculation of preamble, pilot, and traffic C/(I+N),
determination of the best available bearer for the traffic C/(I+N), allocation of resources (RRM), and calculation of
user throughputs.
Segmentation is performed if the frame configuration, selected for a cell, supports segmentation. Interference
calculation is based on the probabilities of collision between segments.
Users can be rejected at this stage for "No Service".

Uplink calculations: The uplink calculations include the calculation of traffic C/(I+N), determination of the best
available bearer for the traffic C/(I+N), uplink power control, uplink bandwidth allocation, resource allocation
(RRM), update of uplink noise rise values for cells, and calculation of user throughputs.
Segmentation is performed if the frame configuration, selected for a cell, supports segmentation. Interference
calculation is based on the probabilities of collision between segments.
Users can be rejected at this stage for "No Service".
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Radio resource management and cell load calculation: Atoll uses an intelligent scheduling algorithm to perform
radio resource management.
Users can be rejected at this stage for "Scheduler Saturation," "Resource Saturation," or “Backhaul Saturation.”
Main simulation outputs are:
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The cell loads (i.e., uplink and downlink traffic loads, uplink noise rise), and
User throughputs.
Note that numerous other parameters are available and stored during the simulation for further analysis. For more
information, see 15.6.5 Simulation Reports.
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15.6.3 Monte Carlo Simulation Management
WiMAX simulations are managed through the Simulations folder in the Atoll Explorer window. This folder is displayed in the
figure below.
Figure 15.26 WiMAX simulations folder
The Simulations folder is made up of several simulation “groups”. Each group corresponds to a network configuration for
which a user-specified number of Monte Carlo simulations have been generated. As an example, different groups may
correspond to different traffic assumptions. The figure below shows the simulation creation dialog box.
When several simulation groups are available, it is possible to automatically display one group after the other, hence
animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
The following information is required when creating a new group of Monte Carlo simulations:
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The simulation group name
The number of simulations to be run
The load and backhaul constraints to apply during simulations
The traffic maps used
The convergence criteria.
Figure 15.27 WiMAX simulation creation dialog box
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Once a simulation (or a group of simulations) has been performed, simulation reports are available and simulation results can
be graphically analysed in Atoll.
15.6.4 Simulation Graphical Analysis
Graphical Display: Mobile Activity Status
Simulations can be displayed in the map window as a graphical layer. Users are displayed on the map, using representative
colours for their activity status. The different possible statuses are:
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Active DL + UL: the mobile is active on both downlink and uplink
Active UL: the mobile is active on uplink only
Active DL: the mobile is active on downlink only
An example of a graphical display of a group of simulations is presented in the figure below.
Figure 15.28 WiMAX simulation display by activity status
Individual Mobile Results Graphical Display
Parameters for any user can be displayed either in the results table or directly on the map (as presented in the figure below).
Figure 15.29 Individual mobile results display using the tool tip
15.6.5 Simulation Reports
Atoll provides detailed simulation results in the form of reports.
Reports of a Single Simulation
A report is available for each simulation. This report contains information about the simulation statistics, and calculation
results by sites, cell, and mobile as given in the figure below.
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Figure 15.30 WiMAX simulation report – Cells tab
Figure 15.31 WiMAX simulation report – Mobiles tab
The simulation results are provided at the following different levels:
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Global statistics: total users attempting a connection and the corresponding break-up per service; total users
actually connected and the corresponding break-up per service.
Results per site: sum of user throughputs (peak MAC, effective MAC, and application level throughputs) for all the
cells of a site, globally and per service type, for both uplink and downlink and numbers of rejected mobiles per
rejection cause.
Results per cell: uplink and downlink traffic loads, uplink noise rise, MU-MIMO capacity gain, sum of user
throughputs (peak MAC, effective MAC, and application level throughputs), for both uplink and downlink, numbers
of rejected mobiles per rejection cause.
Results per mobile: geographic location, receiver height, terminal type, service, user profile, mobility, activity status
(DL/UL), serving cell, path loss, received power levels, uplink transmit power, uplink allocated bandwidth, channel
and user throughputs (peak MAC, effective MAC, and application throughputs), connection status (connected in
DL, UL, DL+UL, or rejected due to no service, scheduler saturation or resource saturation), C/(I+N) and interference
levels, antenna diversity modes, bearer, BLER, etc.
Initial conditions: parameters and traffic maps used to create the simulation.
Reports of a Group of Simulations
Atoll provides detailed simulation results averaged over a group of simulations in the form of reports. The report generated
for a simulation group contains:
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Statistics: average statistics obtained from the results of all the simulations in a group
Results per site: average site results obtained from the results of all the simulations in a group
Results per cell: average cell results obtained from the results of all the simulations in a group
Initial conditions: parameters used to create the simulation group.
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Figure 15.32 WiMAX simulation group report
15.6.6 Updating Cell Loads
You can store the cell loads calculated by Monte Carlo simulations in the cells data table. This enables you to update the
network cell loads based either on the average results from a simulation group or the results of from a single simulation. Cell
load values for all the cells in the network radio database are then updated with the results generated by the selected
simulation. Cell loads from a simulation, simulation group, or from the cells data table can then be used to generate coverage
prediction plots.
15.6.7 Exporting Results
You can export the simulation results as described in 2.5.1 Network Data Import and Export.
WiMAX Coverage Predictions
In Atoll a coverage prediction is a plot displaying calculation results of user-selected parameters on the map and enabling
graphical as well as statistical analysis of the network behaviour. Examples of WiMAX coverage predictions are signal level,
signal quality, radio bearer, throughput plots, etc. For each pixel, Atoll calculates the required information. This data is then
graphically represented by a colour according to a user-defined legend. Different display options are available in Atoll,
depending on the calculated parameter.
15.7.1 Coverage Prediction Calculation and Management
Coverage predictions are performed by assuming a “probe mobile” (non-interfering terminal) on each pixel of the considered
area. The probe mobile characteristics (terminal type, mobility type, service type) are specified as inputs to the coverage
prediction in order to calculate the user-defined prediction parameter.
Predictions are stored as multi-layer geographic objects in the Predictions folder of the Explorer window and can be displayed
in the map window. When several coverage predictions are available, it is possible to automatically display one prediction
after the other, hence animating the prediction plot display on the map, at a user-defined speed using the slideshow function.
Subfolders can be created in the Predictions folder in order to group various coverage prediction objects into categories.
Coverage predictions can be directly created under a subfolder and moved from one subfolder to another using the mouse.
15.7.2 Coverage Prediction Types
WiMAX coverage predictions can be generated either based on the results from Monte Carlo simulations or on user-defined
cell load configurations.
WiMAX coverage prediction types and their display options available in Atoll are listed below.
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Coverage by transmitter (DL)
o Transmitter
Coverage by signal level (DL)
o Signal level (dBm, dBµV or dBµV/m)
o Path loss (dB)
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Overlapping zones (DL)
o Number of servers
Effective signal analysis (DL)
o Preamble signal level and C/N
o Pilot signal level and C/N
o Traffic signal level and C/N
o Permutation zone
o Segment
Effective signal analysis (UL)
o Signal level and C/N
o Permutation zone
Coverage by C/(I+N) level (DL)
o Preamble total noise (I+N) and C/(I+N)
o Pilot total noise (I+N) and C/(I+N)
o Traffic total noise (I+N) and C/(I+N)
Coverage by C/(I+N) level (UL)
o Total noise (I+N) and C/(I+N)
o Uplink allocated bandwidth
o Uplink transmission power
Service area analysis (DL)
o Bearer
o Modulation
Service area analysis (UL)
o Bearer
o Modulation
Effective service area analysis (DL + UL)
Coverage by throughput (DL)
o Peak MAC, effective MAC, and application channel throughput
o Peak MAC, effective MAC, and application cell capacity
o Aggregate peak MAC, effective MAC, and application cell throughput
o Peak MAC, effective MAC, and application throughput per user
Coverage by throughput (UL)
o Peak MAC, effective MAC, and application channel throughput
o Peak MAC, effective MAC, and application cell capacity
o Peak MAC, effective MAC, and application allocated bandwidth throughput
o Aggregate peak MAC, effective MAC, and application cell throughput
o Peak MAC, effective MAC, and application throughput per user
Coverage by quality indicator (DL)
o BER, BLER, etc.
Coverage by quality indicator (UL)
o BER, BLER, etc.
Cell identifier collision zones (DL)
Displays collisions between preamble index, segment, cell permbases, and uplink and downlink zone permbases
o Interferer
o Number of interferers
o Number of interferers per cell
The first five coverage predictions (coverage by transmitter, coverage by signal level, overlapping zones, and effective signal
analyses) are not based on interference, hence neither require cell load information nor Monte Carlo simulations. The
remaining coverage predictions depend on the network’s behaviour under load. These predictions can be calculated for a
service, mobility type, and user terminal equipment.
Various WiMAX coverage prediction plots are shown in the figures below.
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Figure 15.33 WiMAX coverage by transmitter
Figure 15.34 WiMAX coverage by signal level
Figure 15.35 WiMAX overlapping zones coverage
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Figure 15.36 WiMAX effective downlink traffic coverage (isotropic receiver, frequency reuse 1:3)
Figure 15.37 WiMAX coverage by downlink traffic C/(I+N) level (isotropic receiver, frequency reuse 1:3)
Figure 15.38 WiMAX coverage by downlink traffic C/(I+N) level (directional receiver, frequency reuse 1:3)
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Figure 15.39 WiMAX downlink bearer coverage (directional receiver, frequency reuse 1:3)
Figure 15.40 WiMAX coverage by peak MAC downlink throughput (directional receiver, frequency reuse 1:3)
Figure 15.41 WiMAX aggregate peak MAC downlink throughput coverage (isotopic receiver, frequency reuse 1:3)
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Figure 15.42 WiMAX coverage by downlink traffic C/(I+N) level (isotropic receiver, frequency reuse 1:1)
Figure 15.43 WiMAX coverage by downlink traffic C/(I+N) level (isotropic receiver, fractional frequency reuse 1:3)
Figure 15.44 WiMAX effective uplink traffic coverage (isotropic receiver, frequency reuse 1:3)
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Figure 15.45 WiMAX coverage by uplink traffic C/(I+N) level (isotropic receiver, frequency reuse 1:3)
Figure 15.46 WiMAX coverage by uplink traffic C/(I+N) level (directional receiver, frequency reuse 1:3)
Figure 15.47 WiMAX uplink bearer coverage (directional receiver, frequency reuse 1:3)
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Figure 15.48 WiMAX coverage by peak MAC uplink throughput (directional receiver, frequency reuse 1:3)
Figure 15.49 WiMAX aggregate peak MAC uplink throughput coverage (isotopic receiver, frequency reuse 1:3)
Figure 15.50 WiMAX coverage by downlink traffic C/(I+N) level (without smart antennas)
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Figure 15.51 WiMAX coverage by downlink traffic C/(I+N) level (with smart antennas)
Figure 15.52 WiMAX coverage by downlink throughput (without MIMO)
Figure 15.53 WiMAX coverage by downlink throughput (with adaptive MIMO switching)
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15.7.3 Coverage Prediction Reports
Atoll can generate reports for one or more coverage predictions with various detail levels as defined by the user. Reports are
spread sheet-like tables that can be printed directly from Atoll or exported to any desktop tool. An example of such a report
is given in the figure below.
Figure 15.54 WiMAX coverage prediction report
15.7.4 Coverage Prediction Comparison
Comparison (difference, intersection, union, or merge) between two coverage predictions can be performed. As examples,
this functionality can be used:
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To compare uplink and downlink coverage of a service. This enables you to determine uplink/downlink-limited
zones for that service.
To compare service area coverage plots of two different services. This enables you to assess the areas where one
service (e.g., VoIP) is available while the other (e.g., high speed internet) is not.
To compare service area coverage plots of two networks deployment scenarios (possibly with different
technologies). The figure below illustrates such a case by comparing GSM and WiMAX coverage. Note that, in this
example, WiMAX transmitters are installed on only some of the GSM sites.
Figure 15.55 Coverage prediction graphical comparison (GSM versus WiMAX example)
Atoll also enables you to carry out per-pixel arithmetical operations between coverage predictions. For example, you can
calculate the sum, difference, min, max, and average of similar calculated parameters per pixel from two coverage predictions
of the same or different technologies.
15.7.5 Coverage Prediction Export
Any coverage prediction can be exported in the following formats:
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Atoll format
ArcView SHP
MapInfo MIF and TAB
ArcView Grid TXT and ASC
Vertical Mapper GRD and GRC
BMP
PNG
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TIFF
BIL
JPEG2000
JPEG
When exported in MapInfo format, coverage prediction attributes (e.g., signal levels, transmitter IDs, etc.) are exported along
with the plot. The figure below gives an example of the exported attributes for a C/(I+N) prediction.
Figure 15.56 WiMAX coverage prediction attributes export to MapInfo
15.7.6 Point Analysis Tool
A real-time prediction analysis tool is available in Atoll. The point analysis tool is dynamically linked to the map window. The
displayed information is updated as the receiver is moved on the map window. The point analysis tool provides the downlink
signal values numerically and graphically for all cells and for the selected terminal type, mobility type, and service type.
Based on user-defined or calculated cell load values, the point analysis tool also provides numeric values of signal levels and
signal quality for the preamble, pilot, and traffic channels, downlink and uplink bearers, and downlink and uplink throughput
values.
The figure below shows the point analysis window as well as its link to the map window.
Receiving
mobile
Received
strength
signal
Figure 15.57 WiMAX point-to-point real-time analysis
15.7.7 Multi-Point Analysis
Atoll enables you to carry out point predictions on multiple point locations and at different heights. Multi-point analyses can
be carried out on imported lists of points, subscriber locations from fixed subscriber traffic maps, as well as points created
on the map using the mouse.
Multi-point analyses may be useful in verifying network QoS at specific locations in case of reported incidents such as call
drops, low throughputs, etc. Multi-point analysis calculations can be based on user-defined network load conditions in the
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Cells table or loads calculated using Monte Carlo simulations. The figure below shows the multi-point analysis creation dialog
box.
Figure 15.58 WiMAX multi-point analysis creation dialog box
Two types of multi-point analyses are available. Point analysis results include a number of radio parameters at each point
calculated for all potential servers. These results are the same as available for one point in the Details view of the Point
Analysis tool. Fixed subscriber analysis results include more detailed results for the subscriber’s best server. These results are
similar to the results provided by a Monte Carlo simulation.
Multi-point analysis results are stored in the Multi-Point Analysis folder in the Network explorer. Once calculated, multi-point
analysis results are available in tabular form and visible on the map using symbols and colours based on calculation results.
Figure 15.59 WiMAX multi-point analysis results
You can export the multi-point analysis results as described in 2.5.1 Network Data Import and Export.
WiMAX Neighbour Planning
Atoll supports the following neighbour types in a WiMAX network configuration:
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Intra-technology neighbours: WiMAX cells defined as neighbours of other WiMAX cells in the same Atoll document.
Inter-technology neighbours: WiMAX cells defined as neighbours of cells which use a technology other than
WiMAX.
Neighbour plans can be generated by any of the following means in Atoll:
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Importing an external neighbour plan (e.g., in Excel format)
Automatically producing a neighbour plan as described in 15.8.1 Automatic Neighbour Allocation
Graphically and/or manually creating, editing and deleting a neighbour plan as presented in 15.8.2 Graphical
Neighbour Plan Editing
Various neighbour plans can be compared. The results of an automatic neighbour allocation can be compared with the
existing neighbour plan. As well, neighbour plans from external sources can also be compared with the existing neighbour
plan in Atoll.
15.8.1 Automatic Neighbour Allocation
Neighbour lists can be generated automatically in Atoll. For each cell, potential neighbours are ranked according to their
importance. The neighbour planning algorithm considers the following user-specified parameters:
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Hysteresis zone defined by a handover start and a handover end margin with respect to the best server preamble
signal strength
Maximum inter-site distance
Maximum number of neighbours
Minimum area covered (overlapping area between the reference cell and its potential neighbour).
Importance ranges for distance, coverage, adjacency, and co-site factors.
Neighbours can be automatically allocated based on the coverage overlap in terms of the preamble signal level or the
preamble C/(I+N).
Forcing “neighbour symmetry”, “adjacent cells as neighbours”, “co-site cells as neighbours“ and/or “exceptional neighbour
pairs” is possible with Atoll. The figure below displays the automatic neighbour allocation dialog box.
Figure 15.60 WiMAX automatic neighbour list generation
15.8.2 Graphical Neighbour Plan Editing
Neighbour plan can be graphically edited in Atoll. Clicking a transmitter on the map displays all its neighbour relations. All
types of neighbour relations (outwards, inwards or symmetrical) can be created, edited and/or deleted graphically. Such an
example is presented in the figures below.
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Figure 15.61 Graphical neighbour plan editing
Figure 15.62 Neighbour planning using a best server plot
15.8.3 Neighbour Consistency Check Tool
A neighbour relation audit is available in Atoll. This function enables you to determine inconsistencies in the current
neighbour plan. The figure below shows the neighbour relation conditions that can be verified using the audit.
Figure 15.63 Neighbour audit
WiMAX Automatic Frequency, Preamble Index, and Zone Permbase Planning
The Atoll WiMAX AFP (Automatic Frequency Planning module) enables you to automatically configure network parameters
such as the frequency channels, preamble indexes, and permbases. The AFP can also perform fractional frequency planning
through automatic configuration of the segments during preamble index planning. The aim of the AFP is to allocate resources
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in a way that minimises interference following the user‐defined constraints. The AFP assigns a cost to each constraint and
then uses an iterative algorithm to evaluate possible allocation plans and propose the allocation plan with the lowest costs.
The AFP cost function comprises input elements such as interference matrices, neighbour relations, and allowed ranges of
resources for allocation.
The figure below presents the WiMAX AFP window.
Figure 15.64 WiMAX AFP
15.9.2 AFP Cost Components
The AFP cost components include relations and constraints. The AFP’s automatic planning algorithm can take the following
relations into account:
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Interference-based relations, i.e., cells that interfere each other
The probability of interference is extracted from interference matrices. One or more interference matrices can be
calculated using Atoll or imported from external files in standard TXT, CSV, and IM2 formats, in order to provide
the AFP with:
o The co-channel interference probability
o The adjacent channel interference probability
Neighbour cells
The importance of each neighbour relation is determined from the neighbour relation definition. The following
neighbour relations can be taken into account:
o First-order neighbours (direct neighbours)
o Second-order neighbours (neighbours of neighbours)
o Inter-neighbours (neighbours of a common cell)
Inter-cell distance
A minimum reuse distance can be defined per cell or globally for all the cells.
The AFP can take into account the following constraints:
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For automatic frequency allocation: Frequency channel collision and overlap
For preamble index allocation: preamble index collisions and other related collisions (segments, cell permbases),
preamble index allocation domain, effect of the frequency plan on preamble index allocation, etc.
For downlink and uplink zone permbase allocation: zone permbase collisions, zone permbase allocation domain,
etc.
The impact of each relation and constraint can be fine-tuned by the user by defined the associated weights. The figure below
shows the AFP constraint weights dialog box.
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Figure 15.65 User-defined AFP constraint weights
15.9.3 Automatic Preamble Index Planning
Atoll enables you to assign preamble indexes manually or automatically to any cell in the network. Atoll facilitates the
management of preamble indexes by letting you create groups of preamble indexes and domains, where each domain is a
defined set of groups. Atoll can automatically assign preamble indexes to cells taking into account the network’s frequency
plan, the selected cell permbase allocation strategy (free or same per site), allowed allocation domain, interference matrices,
reuse distance, and any constraints imposed by neighbours.
Once the allocation is complete, you can implement the proposed allocation plan, export the results to TXT, CSV, or XML
spread sheet files, audit the preamble indexes, analyse preamble index reuse and collisions on the map, and make an analysis
of preamble index distribution.
Figure 15.66 WiMAX preamble index planning
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Figure 15.67 WiMAX preamble index audit
15.9.4 Automatic Frequency Planning
Atoll enables you to assign frequency channels manually or automatically to any cell in the network. Atoll facilitates the
management of frequency bands and channels by letting you define these as needed. Atoll can automatically assign frequency
channels to cells taking into account the allowed frequency channels, interference matrices, reuse distance, and any
constraints imposed by neighbours.
Once the allocation is complete, you can implement the proposed allocation plan, export the results to TXT, CSV, or XML
spread sheet files, audit the frequencies, analyse frequency reuse and interference on the map, and make an analysis of
frequency distribution.
Figure 15.68 WiMAX frequency planning
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Figure 15.69 WiMAX frequency audit
15.9.5 Automatic Downlink and Uplink Zone Permbase Planning
Atoll enables you to assign downlink and uplink zone permbases manually or automatically to any cell in the network. Atoll
can automatically assign downlink and uplink zone permbases to cells taking into account the allowed allocation domain,
interference matrices, reuse distance, and any constraints imposed by neighbours.
Once the allocation is complete, you can implement the proposed allocation plan, export the results to TXT, CSV, or XML
spread sheet files, audit the downlink and uplink zone permbases, analyse zone permbase reuse on the map, and make an
analysis of zone permbase distribution.
15.9.6 Frequency, Preamble Index, and Zone Permbase Plan Analysis
Cell Parameter Search Tool
A search tool is available in Atoll which enables you to search for frequencies, preamble indexes, segments, and cell
permbases. You can display the current allocation plan of the selected parameter on the map and highlight the transmitters
and their coverage areas respectively. The tool window is shown in the figure below.
Figure 15.70 WiMAX frequency search
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Cell Parameter Display on Map
You can display the frequency, preamble index, segment, cell permbase, and downlink and uplink zone permbase allocation
on transmitters by using the transmitters’ display settings. The figure below shows a preamble index plan displayed on the
map.
Figure 15.71 Preamble index display on map
Cell Identifier Collision Zones Prediction
You can display the preamble index, segment, cell permbase, and downlink and uplink zone permbase collisions on the map
using the cell identifier coverage prediction.
WiMAX Automatic Cell Planning
The Atoll WiMAX ACP (Automatic Cell Planning) module enables you to automatically determine the best WiMAX parameter
settings for your network. The aim of the Atoll ACP is to improve network quality in terms of both coverage and capacity. For
a comprehensive description of the Atoll ACP, see 17 Automatic Cell Planning (ACP) Features.
The Atoll WiMAX ACP is capable of optimising network parameters (antenna types, heights, azimuths, tilts, transmission
powers, etc.) based on the following WiMAX quality indicators:
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Signal level
Preamble C
Preamble C/N
Preamble CINR
Overlap
Best server distance
1st-Nth difference
WiMAX Co-planning With Other Radio Access Technologies
Atoll supports co-planning of WiMAX networks with other radio access technologies. For more information, see 11 Multi-RAT
Features.
Additionally, Atoll models the effect of interference from coexisting WIMAX (or OFDM) networks. This feature enables
studying the effect of interference on the WiMAX network from other parts of the same WiMAX network and from the WiMAX
(or OFDM) networks of other operators. The figure below shows the specific “Transmitter Type” parameter (Server and
Interferer or Interferer Only) required as input.
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Figure 15.72 Transmitter properties window
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16 Measurements and Drive Test Data Features
The Atoll Measurements module is an optional module available for all mobile radio access technologies in Atoll. The Atoll
Measurements module is capable of processing two different types of measurement data:
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CW (continuous wave) measurements
Dedicated continuous wave transmitters are set up for collecting signal strength measurements during
measurement campaigns, usually for the purpose of calibrating propagation models.
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Drive test data
Drive test campaigns are carried out on live networks by making test calls and recording relevant information, such
as signal strength and signal quality values for the serving and neighbour cells, and messages exchanged between
the mobile and the network. These data are usually collected for the purpose of radio network optimisation.
CW Measurements
CW measurements can be imported, displayed, analysed, processed, and used for propagation model tuning in Atoll. Atoll
allows importing CW measured data in various formats including MS Excel, ASCII text, MSI Planet, and CSV. More than one
survey paths can be simultaneously loaded into a project. During the import process, the corresponding transmitter ID and
frequency are assigned to each of the survey files. Import configurations can be saved in Atoll for convenience.
Imported measurement data can be processed in Atoll. This processing includes graphic filtering by range, signal strength,
clutter types, number of measurement points, and antenna azimuths. This is presented in the figure below.
Figure 16.1 CW measurement processing
Atoll is also capable of generating detailed reports on the comparison between measured and predicted values. This report
includes the standard deviation, mean, repartition law, and other statistical information. Statistics are also provided per
clutter type. The figure below shows an example of a visual comparison between measured and predicted data.
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Figure 16.2 Prediction – measurement comparison
Atoll also includes a feature for smoothing measurement values which allows reducing the effect of fading on the measured
values. Measurement smoothing is carried out using a sliding window to reduce the variations in the measured values.
Drive Test Data
Drive test data can be imported, displayed, analysed, filtered, and used for path loss matrix tuning in Atoll. Atoll allows
importing drive test data in various formats including TEMS (FMT and PLN), ASCII text, DAT, and CSV. Moreover, other specific
formats, generic or proprietary, can also be imported in Atoll. More than one survey paths can be simultaneously loaded into
a project. File import configurations can be saved in Atoll for convenience. Drive test data can also be exported from Atoll to
files in MapInfo, ArcView and Atoll formats.
At the time of import, Atoll identifies serving and neighbour cells by decoding the cell identifiers (BSIC/BCCH, scrambling
codes, PN offsets, physical cell IDs, preamble indexes, etc.). Atoll is also capable of decoding call events. The decoding is
performed automatically during the file import. The figure below gives an example of a TEMS PLN file imported in Atoll with
decoded call events.
Figure 16.3 Call event decoding from a TEMS file imported in Atoll
Imported drive test data can be filtered by clutter type, distance, or serving cell. In addition, any user-defined filter parameter
can be added through a query function. Drive test data can be displayed in Atoll using any parameter from the imported data.
Parameter information can be presented in three different ways:
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On the map window: The link between a measurement point and its serving cell and neighbours (if available) is
drawn in real-time as the mobile moves along the drive test path.
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In the drive test data table: All parameters can be visualised.
In the drive test data analysis tool: a graph shows the selected parameters of the drive test data.
These three display modes are interactively linked with each other. As the cursor is moved along the data path, the mobile
follows its drive test path and the corresponding record in the drive test data table is highlighted. An example of this feature
is presented in the figure below.
Map window
Serving cell
Test mobile
Data record
Drive test data table
Analysis tool
Parameter values
Figure 16.4 Drive test data display
Propagation Model Calibration
CW measurement data can be used for manual tuning of the propagation models through the propagation model editor, or
for assisted calibration or automatic optimisation using the automatic propagation model calibration routine. This module
determines the optimum propagation model parameters using a Minimum Root Mean Square algorithm. An example of
automatic calibration window is shown in the figure below.
Figure 16.5 Automatic propagation model calibration
Figure 16.6 Assisted propagation model calibration
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Path Loss Tuning
Drive test data and CW measurements can be used in Atoll to improve the accuracy of calculated path loss matrices
(propagation results) of individual transmitters and repeaters. Atoll applies global and localised corrections to the calculated
values depending on the number of measurement points taken into account and the distance between the measurement
point and the pixel being corrected. The interpolation is based on the points located inside a predefined ellipse oriented
towards the transmitter. A weighting factor is applied based on the radius of each ellipse and the distance to the
measurement point.
Catalogues of measurement paths intended to be used for path loss tuning can be created and shared among users.
Figure 16.7 Measurement based path loss tuning on coverage: before (left) and after (right)
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17 Automatic Cell Planning (ACP) Features
The Atoll ACP (Automatic Cell Planning) module enables radio network design engineers to optimise their network settings
for improving network coverage and capacity.
The Atoll ACP is an optional module available for the following technologies:
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5G NR
LTE/LTE-Advanced
NB-IoT
UMTS/HSPA
GSM/GPRS/EDGE
CDMA2000
LPWA
Wi-Fi
WiMAX
The Atoll ACP can be used to optimise parameters of installed antennas (patterns, heights, azimuths, and tilts) and cell
transmission powers. The ACP can take into account various standard and user-defined optimisation objectives, such as
coverage, capacity, throughput, service quality, interference, and EMF exposure levels at building facades. Moreover, the
ACP is capable of taking different building floors into account for evaluating the optimisation plans with multi-storey buildings.
The ACP can also be used during the pre-design stage of a network for automatic site placement and candidate site selection
and to carry out initial antenna selection and optimisation for new sites before implementation.
All of the above-listed features are available for single-RAT as well as multi-RAT networks for simultaneous optimisation for
multiple technologies.
Figure 17.1 ACP multi-RAT (GSM/UMTS/LTE) optimisation process
The ACP optimisation process is based on flexible and user-definable directives. These optimisation directives may include a
number of weighted criteria dependent on clutter data, radio access technologies, KPIs, traffic data, etc. The ACP also enables
comprehensive analyses of proposed optimisation plans. Multiple “what if?” scenarios can be generated, stored, and
compared in order to make informed decisions on the definitive optimisation plan.
The ACP can use calibrated propagation models as well as path loss results tuned using drive test measurements. Moreover,
the network optimisation process in the ACP can also take into account multiple indoor floor levels in addition to the outdoor
ground level.
The Atoll ACP includes full multi-technology support for combined multi-technology optimisation. The ACP takes into account
the interaction and co-existence of different technology networks in the optimisation process and proposes combined
optimisation plans for the entire multi-RAT network. Multi-technology optimisation results can be simultaneously displayed,
analysed, and implemented within Atoll.
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Figure 17.2 Atoll ACP implementation plan analysis
Automatic Cell Planning Scenario Definition
The Atoll ACP features are available in Atoll through a dedicated folder in the Network explorer. The ACP folder provides a
unique access for creating, storing, analysing, and implementing network optimisation scenarios. Different ACP scenarios can
be created for analysing various network reconfiguration options and site selection alternatives. Each scenario is an
independent data object containing the scenario input as well as the resulting implementation plans.
ACP optimisation scenarios can store multiple implementation plans, can be shared and exchanged between users and
different Atoll sessions through comprehensive configuration files, and new ones created based on existing scenarios.
Figure 17.3 The ACP folder
The ACP folder also enables to define global settings for the ACP optimisation process and user preferences. The ACP global
settings allow defining the ACP path loss matrix storage folder and provide the possibility to choose a calculation preference
between speed and precision. The figure below shows the ACP global settings window.
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Figure 17.4 Atoll ACP global settings window
The aim of the automatic cell planning algorithm is to find the optimum network parameters that satisfy user-defined
coverage, quality, capacity, throughput, and EMF-exposure objectives within user-defined geographic zones. The Atoll ACP
can propose solutions based on different rules and can take weighting maps, population and traffic data, as input in order to
steer the cell planning algorithm towards the most appropriate solution that caters for both high density and low density
regions.
The Atoll ACP is designed to work with multiple geographic zones as well as vectors such as roads and railway tracks. It can
be provided with multi-technology optimisation targets and objectives that need to be treated by optimising network
parameters. Network reconfiguration and site selection can be performed simultaneously with full interaction between both
processes. The following sections provide an overview of the above-mentioned elements of the overall ACP workflow.
17.1.1 Optimisation Targets
The ACP can work with multi-technology optimisation targets ranging from network layers to optimise, the geographic zones
to optimise as well as those used to evaluate the various objectives, and the cost-related parameters. Each geographic zone
can be assigned a relative weight which is taken into account by the ACP when optimising the network.
Network Layers
The Atoll ACP enables you to automatically and simultaneously optimise multi-technology networks. Multiple heterogeneous
technology layers can be taken into account in the optimisation process as needed. The figure below shows the ACP
optimisation layer selection window.
Figure 17.5 ACP optimisation layers
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Working Zones
You can define different geographic zones in the Atoll ACP for evaluation of the ACP objectives and for the definition of the
network elements that can be reconfigured. Multiple zones can be provided as input with relative priorities. The figure below
shows the ACP zones definition window.
Figure 17.6 ACP zones definition
Cost Control
The Atoll ACP enables you to provide estimates of the required costs or effort related to each type of modification that can
be carried out by the ACP during the optimisation process. You can also define the maximum number of allowed changes for
each type of modification. Multiple site cost classes can be defined and assigned to existing and candidate sites. These flexible
parameters enable the Atoll ACP to rank the network reconfiguration changes in the order of their cost. The figure below
shows the ACP cost control definition window.
Figure 17.7 ACP cost control definition window
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Optimisation Constraints
The Atoll ACP enables you to impose a global constraint on the maximum number of active sites that the ACP must propose
at the end of the optimisation process. The figure below shows the ACP constraint definition window.
Figure 17.8 ACP constraint definition window
Multi-Storey Optimisation
The Atoll ACP can be provided with 3D optimisation targets using multi-storey calculations. The multi-storey optimisation
targets are based on 3D building data within given optimisation zones where ACP optimisation objectives are evaluated on
multiple floors. The figure below shows the Atoll ACP multi-storey optimisation target definition window.
Figure 17.9 Atoll ACP multi-storey optimisation target definition window
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Figure 17.10 Multi-storey optimisation results example
EMF Exposure Optimisation
In addition to radio network quality indicators, regulatory constraints such as EMF exposure level can also be taken into
account in the Atoll ACP optimisation process. The Atoll ACP uses a dedicated propagation model, based on propagation
classes, for EMF exposure analysis in 2D and 3D for building facades. The figure below shows the Atoll ACP EMF exposure
level optimisation target definition window.
Figure 17.11 Atoll ACP EMF exposure level optimisation target definition window
17.1.2 Optimisation Objectives
The Atoll ACP can work with multi-technology coverage, quality, throughput, and capacity-oriented optimisation objectives.
Each objective is defined by one or more radio quality indicator (SS-RSRP, RSRP, RSCP, Ec/Io, etc.) and a surface area coverage
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requirement for a target geographic zone. An objective can be associated with one or more technology layers, assigned a
user-defined importance, and a geographic weighting map based on, for example, population or traffic data.
You can define as many objectives as needed. It is also possible to combine optimisation objectives using logical expressions
(AND, OR, etc.). The figure below shows an example of ACP objective definition.
Figure 17.12 Atoll ACP optimisation objectives
Objectives based on certain radio quality indicator (BCCH signal level, co-channel CINR, RSCP, Ec/Io, RSRP, RSRQ, RS CINR,
and PDSCH CINR) can also use a progressive threshold function. Progressive thresholds enable the ACP to assess the objective
quality more finely. Using progressive thresholds, variations in the radio quality indicator values are converted into variations
in the objective quality rather than a simple function representing whether the objective has been achieved or not. This
allows the ACP make more intelligent decisions by evaluating the amount of improvement compared to the extent of quality
degradation that any parameter change may bring.
Radio Quality Objectives
The Atoll ACP can work with multiple radio quality indicators. Network optimisation objectives are based on radio quality
indicator criteria. The following radio quality indicators are supported by the ACP:


5G NR
o SS-RSRP
o SSS C/N
o SSS CINR
o PDSCH CINR
o RLC peak throughput
o Overlap
o Best server distance
o 1st-Nth difference
LTE/LTE-Advanced
o Signal level
o RS C
o RS C/N
o RSRP
o RS CINR
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o RSRQ
o RSSI
o PDSCH CINR
o RLC peak throughput
o Overlap
o Best server distance
o 1st-Nth difference
o PUSCH signal level
NB-IoT
o NRS C
o NRSRP
o NRS CINR
o NRSRQ
o NPUSCH C
o 1st-Nth difference
UMTS/HSPA
o RSCP
o Ec/Io
o RSSI
o HS-PDSCH Ec/Nt
o RLC peat throughput
o Overlap
o Best server distance
o 1st-Nth difference
GSM/GPRS/EDGE
o BCCH signal level
o Co-channel CINR
o Overlap
o Best server distance
o 1st-Nth difference
CDMA2000
o Signal level
o Ec/Io
o Overlap
o Best server distance
o 1st-Nth difference
LPWA
o Number of redundant servers
o Signal level
o C
o C/N
o CINR
o Overlap
o Best server distance
o 1st-Nth difference
Wi-Fi
o Signal level
o C
o C/N
o CINR
o Overlap
o Best server distance
o 1st-Nth difference
WiMAX
o Signal level
o Preamble C
o Preamble C/N
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Preamble CINR
Overlap
Best server distance
1st-Nth difference
Throughput Objective
The Atoll ACP is capable of maximising the throughput offered by the network by distributing multi-technology traffic among
various network layers according to their coverage footprints and priorities. This allows the ACP to find the best
implementation plans that ensure optimum end-user throughputs in the network. The figure below shows the Atoll ACP
throughput objective definition window.
Figure 17.13 Atoll ACP throughput objective definition window
Load Balancing Objective
The Atoll ACP is capable of performing capacity-driven optimisation where actual network traffic data is used for calculating
the distribution of traffic load among multi-technology layers and services. This feature enables the Atoll ACP to drive the
optimisation process towards solutions that provide best-suiting network configurations for network traffic and load
conditions. The figure below shows the Atoll ACP load balancing objective definition window.
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Figure 17.14 Atoll ACP load balancing objective definition window
Optimisation Zones and Weighting Maps
Multiple geographic zones can be provided to the Atoll ACP as optimisation target zones. These zones may include vector
objects such as roads and railway tracks. Each ACP optimisation objective may be assigned to a given geographic zone
Moreover, optimisation target zones may be created from clutter class data as shows in the figure below.
The Atoll ACP can also be provided with weighting maps, based on population and traffic data, for each objective in order to
steer the optimisation process towards solutions that are targeted to improve high density regions.
Figure 17.15 ACP optimisation zone and weighting map selection dialog boxes
17.1.3 Cell Parameter Reconfiguration
The Atoll ACP is capable of working with the following cell parameters in order to optimise the user-defined radio network
coverage, quality, and capacity objectives:

Site/sector deactivation
The ACP can automatically detect sectors and sites that do not contribute sizeable in the overall network coverage
and quality. The ACP may propose to remove such sectors and sites in order to improve the overall cost while
maintaining a certain level of network quality.

Cell transmission power
The ACP can automatically adjust the transmission powers of cells. Cell powers may be increased to enlarge the cell
service areas or decreased to improve the interference levels in the network. This parameter is mostly managed as
a remote adjustable parameter which does not require a site visit. Minimum and maximum allowed power values
can be defined for each cell individually.
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Antenna type
The ACP can automatically find the best suited antenna model for any sector depending on the antenna sharing
and management constraints provided to the ACP.

Antenna height
The antenna height can be adjusted in order to improve cell coverage footprints. Minimum and maximum allowed
antenna height values can be defined for each sector individually.

Antenna azimuth
The antenna azimuth can be adjusted in order to direct the cell transmission and reception towards the surface and
traffic to cover. Minimum and maximum allowed antenna azimuth values can be defined for each sector.

Antenna tilt (electrical as well as mechanical)
The antenna tilt can be adjusted in order to improve cell coverage overlaps and interference levels. The electrical
tilt is usually considered to be remotely manageable and not requiring a site visit for modification. Minimum and
maximum electrical and mechanical tilt values can be defined for each sector individually.

Repeater amplifier gain
The repeater amplifier gain can be adjusted in order to improve cell coverage. Minimum and maximum gain values
can be defined for each repeater individually.
Any repeaters and remote antennas associated with the cells being optimised are also taken into account. As well, co-located
transmitters are automatically linked to share the same antenna and parameters. All the network configuration parameters
can be defined directly in the corresponding windows and imported from external files containing these parameters in a
tabulated form. This enables sharing and exchanging ACP reconfiguration parameters among Atoll sessions and users.
Figure 17.16 ACP site reconfiguration parameters window
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Figure 17.17 ACP sector and cell reconfiguration parameters window
17.1.4 Site Selection
The Atoll ACP enables you to automatically select sites to activate in order to match the required objectives. The ACP proposes
various types of site selection:

Current site selection
Current site selection consists in activating or deactivating existing sectors and sites according to the required
coverage, quality, and capacity objectives. Sectors and sites that do not provide considerable improvements in the
overall network radio objectives may be deactivated in order to reduce the overall network cost.

Current candidate selection
Current candidate site selection consists in activating or deactivating sectors and sites that are currently not used
by the network. Sites that are currently deactivated are taken into account by the ACP as potential candidates for
activation if needed according to the required coverage, quality, and capacity objectives.

New candidate selection
New candidate site selection consists in adding new sites to the network if new sites are required for improving the
defined coverage, quality, and capacity objectives. In addition to site selection from among a list of candidates, the
station template associated with different candidate sites may also be automatically reconfigured by the ACP to
provide the best default settings for each new site.
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Figure 17.18 ACP new candidate site selection setup window
17.1.5 Antenna Management
The Atoll ACP can work with multi-band multi-technology antennas. It can also be used to select the best-suited antenna for
multi-technology sites providing dedicated antenna patterns for the operating frequencies of corresponding technologies.
The Atoll ACP enables you to define physical antenna models that support multiple patterns, group them as needed, and
define constraints on their selection as needed.
The figures below show the antenna definition and grouping windows for the case of a multi-technology network with
antenna sharing sites.
Figure 17.19 Atoll ACP antenna management window – Physical antennas
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Figure 17.20 Atoll ACP antenna management window – Pattern grouping
The Atoll ACP supports advanced optimised antenna masking methods for adapting path loss values to different antenna
patterns.
Automatic Cell Planning Results
Comprehensive optimisation results are provided at the end of each ACP run in the form of a detailed implementation plan.
This implementation plan can be reviewed before actual implementation with the help of features described in this section.
17.2.1 ACP Optimisation Process
While running, the Atoll ACP optimisation progress window displays the ACP process in real-time. It shows the improvements
brought about by various modifications made in the network parameters in the form of graphs and statistics. This window
also displays the gains in various objectives in the form of predictions.
The figure below shows an example of the ACP progress window.
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Figure 17.21 Real-time ACP optimisation progress view
17.2.2 ACP Implementation Plan
Once the ACP process is complete, comprehensive optimisation results are provided in an ACP implementation plan. The ACP
implementation plan presents the changes ordered from the most to the least beneficial, allowing implementation of a subset
of the proposed changes as needed.
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The results of any ACP scenario include the following:

Statistics:
This tab provides global statistics and an overview of the solution proposed by the ACP. Statistics are provided for
the target zone and defined objectives.
Figure 17.22 ACP optimisation plan statistics

Sectors:
This tab lists all the changes proposed by the ACP to different parameters of sectors of various technologies.
Figure 17.23 ACP optimisation plan
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Graph:
This tab displays the evolution of the ACP optimisation process.
Figure 17.24 ACP optimisation process evolution

Quality:
This tab displays the improvements brought about by the ACP to various quality indicators in the form of coverage
predictions.
Figure 17.25 ACP quality indicator improvement maps

Capacity:
This tab displays the improvement in load balancing corresponding to the ACP optimisation plan.
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Figure 17.26 ACP load balancing improvement

Throughput:
This tab displays the improvement in throughput provision corresponding to the ACP optimisation plan.
Figure 17.27 ACP throughput improvement

Change Details:
This tab provides the list of proposed changes in the order of improvement provided by each. The ACP allows you
to find the best compromise between the number of changes and the corresponding improvement.
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Figure 17.28 ACP change details by quality improvement

Commit:
The final list of changes can be reviewed before implementation. It is possible to commit the results to the Atoll
document and rollback if needed.
Figure 17.29 ACP results to implement in the network
17.2.3 ACP Coverage Predictions
The ACP enables you to display optimisation results in the form of coverage predictions in the map window. This allows you
to view, compare, and visually analyse the results. When several coverage predictions are available, it is possible to
automatically display one prediction after the other, hence animating the prediction plot display on the map, at a user-defined
speed using the slideshow function.
Various types of ACP coverage predictions are available:

Objective analysis predictions
The objective analysis predictions enable you to display the whether or not the defined objectives were met in the
initial coverage or in the final coverage. An objective analysis prediction displays the variation between the initial
coverage and the final coverage, i.e., whether the objective was met in the initial coverage, in the final coverage, in
both, or in neither. For a multi‐storey optimisation, you can display the prediction on the ground level, the lowest
values over all the storeys calculated, or the values for a specific storey.

Capacity analysis predictions
The capacity analysis predictions allow you to display the throughput gain and relative cell capacity load compared
to average cell load. This allows you to view throughput improvements as well as overloaded and underloaded cells.
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Technology layer predictions
Multiple coverage predictions are available for various technology layers and objectives.

EMF exposure predictions
The EMF exposure predictions contain predictions enabling you to analyse EMF exposure.
Figure 17.30 ACP coverage predictions
ACP coverage predictions can be exported to raster format files and analysed using histogram functions.
17.2.4 ACP Implementation Plan Comparison
The ACP enables you to run multiple optimisation scenarios and compare their results within Atoll. A comparison between
two implementation plans provides a global comparison between the objective improvements of both plans as well as a
comparison between the numbers and types of changes proposed by each plan. The figure below shows an example of a
comparison between two ACP implementation plans.
Figure 17.31 Comparison of ACP implementation plans
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18 Automatic Frequency Planning (AFP) Features
The Atoll AFP (Automatic Frequency Planning) module enables radio network design engineers to automatically plan and
allocate cell parameters to optimise network coverage and capacity. The Atoll AFP is an optional module available for the
following technologies:
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5G NR
LTE/LTE-Advanced
NB-IoT
GSM/GPRS/EDGE
Wi-Fi
WiMAX
Atoll 5G NR AFP
The Atoll 5G NR AFP module can automatically allocate physical cell IDs and PRACH root sequence indexes according to the
defined interference and collision-based optimisation targets. The AFP can work with user-defined constraints and costs
based on interference matrices from various sources, neighbour relations, and distance. The AFP fully supports multi-band
networks using different carrier widths. The Atoll 5G NR AFP can automatically plan physical cell IDs taking into account
various network planning constraints.
For more information on the 5G NR AFP features, see 5.10 5G NR Automatic Physical Cell ID and PRACH RSI Planning.
Atoll LTE AFP
The Atoll LTE AFP module can automatically allocate frequencies, physical cell IDs, and PRACH root sequence indexes
according to the defined interference and collision-based optimisation targets. The AFP can work with user-defined
constraints and costs based on interference matrices from various sources, neighbour relations, and distance. The AFP fully
supports multi-band networks using different carrier widths.
The Atoll LTE AFP can automatically plan physical cell IDs taking into account various network planning constraints such as
the PSS ID collision, eNode-B-based SSS ID allocation, uplink demodulation reference signal sequence collision, cell-specific
reference signal collisions, collisions of PCFICH (physical control format indicator channel) resource element groups, etc.
For more information on the LTE AFP features, see 6.14 LTE/LTE-Advanced Automatic Frequency, Physical Cell ID, and PRACH
RSI Planning.
Atoll NB-IoT AFP
The Atoll NB-IoT module adds NB-IoT-specific features to the AFP. The Atoll LTE/NB-IoT AFP is capable of combined LTE and
NB-IoT physical cell ID planning. Automatic PCI/NPCI planning using the Atoll LTE/NB-IoT AFP takes into account relations
between LTE and NB-IoT cells in order to determine PCI/NPCI collisions. In inband deployment configuration, the AFP can also
allocate the same PCI/NPCI to inband LTE and NB-IoT cells for which the flag “same NPCI as LTE PCI” has been set. Moreover,
the LTE/NB-IoT AFP can also carry out automatic frequency planning for NB-IoT cells. This can be particularly useful in
standalone NB-IoT deployments.
For more information on the LTE/NB-IoT AFP features, see 7.8 NB-IoT Automatic Frequency and Narrowband Physical Cell ID
Planning.
Atoll GSM AFP
The Atoll GSM AFP module is based on sophisticated optimisation techniques and includes combined automatic as well as
interactive frequency planning (IFP) and optimisation of TRX allocation vs. interference conditions. It can automatically
allocate frequencies, frequency hopping parameters (MAL, HSN, MAIO), and BSIC, etc. The Atoll GSM AFP module can
combine and use interference matrices based on predictions and live network statistics from the OAM. It can also calculate
and take intermodulation interference into account.
The Atoll GSM AFP includes support for frequency bands, carriers, layers, border constraints, and frequency hopping
parameters (MAL, HSN, MAIO). It allows setting up vendor-specific requirements, and user-defined constraints and costs.
For more information on the GSM AFP features, see 9.9 GSM/GPRS/EDGE Automatic Frequency Planning.
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Figure 18.1 GSM AFP optimisation process (left), IFP interference analysis (top), implementation plan analysis (right)
Atoll Wi-Fi AFP
The Atoll Wi-Fi AFP can automatically allocate frequencies according to the defined interference and collision-based
optimisation targets. The AFP can work with user-defined constraints and costs based on interference matrices from various
sources, neighbour relations, and distance. The AFP fully supports multi-band networks using different carrier widths.
For more information on the Wi-Fi AFP features, see 14.8 Wi-Fi Automatic Frequency Planning.
Atoll WiMAX AFP
The Atoll WiMAX AFP can automatically allocate frequencies, preamble indexes, segments, and permbases according to the
defined interference and collision-based optimisation targets. The AFP can work with user-defined constraints and costs
based on interference matrices from various sources, neighbour relations, and distance. The AFP fully supports multi-band
networks using different carrier widths.
For more information on the WiMAX AFP features, see 15.9 WiMAX Automatic Frequency, Preamble Index, and Zone
Permbase Planning.
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19 Automatic Site Positioning (ASP) Features
The Atoll ASP (Automatic Site Positioning) module enables radio network pre-design analyses for greenfield deployments and
allows estimating the network deployment cost. It can be used to evaluate the number of sites required to cover any given
area and compare various possible deployment options and technical alternatives. The Atoll ASP also enables network
expansion planning. You can study additional sites taking into account the current network coverage.
The Atoll ASP is an optional module available for the following technologies:



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


5G NR
LTE/LTE-Advanced
NB-IoT
UMTS/HSPA
GSM/GPRS/EDGE
CDMA2000
WiMAX
The Atoll ASP can take into account multiple design strategies: hexagonal design based on inter-site distances and smart
design based on calculated site coverage footprints. The Atoll ASP provides flexible user-defined objectives and rules. Site
deployment plans can be based on multiple coverage targets over different zones (e.g., urban, suburban, rural zones), as well
along roads and railways. Moreover, surface-wise coverage objectives can be weighted according to traffic and population
data in order to fine-tune the site positioning algorithm.
Figure 19.1 Atoll ASP design strategies and objectives
For each site positioning scenario, the Atoll ASP provides an intelligent implementation plan, comprehensive results and
statistics. It allows you to select the best sites to deploy, i.e., those that provide the highest gains, and analyse the
improvement according to the number of sites.
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Figure 19.2 Atoll ASP results
Automatic Site Positioning Scenario Definition
The Atoll ASP features are available in Atoll through a dedicated folder in the Network explorer. The ASP folder provides a
unique access for creating, storing, analysing, and implementing ASP scenarios. Different ASP scenarios can be created for
analysing various greenfield deployment options and technical alternatives. Each scenario is an independent data object
containing the scenario input as well as the resulting implementation plan.
Figure 19.3 The ASP folder
The aim of the automatic site positioning algorithm is to find the optimum number of sites, and there ideal locations, required
to cover user-defined geographic zones. The Atoll ASP can propose solutions based on different design methods (based on
inter-site distance or based on coverage footprints). It can take population and traffic data as input in order to drive the site
positioning algorithm to match high and low density regions.
The Atoll ASP is designed to work with multiple geographic zones as well as vectors such as roads and railway tracks.
Objectives can be defined for each geographic zone and vector separately. As well, finely tuned site-deployment strategies
can be created by defining clutter-related preferences.
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Figure 19.4 The ASP setup dialog box
19.1.1 Design Methods
ASP scenarios can be based on the following design methods:


Hexagonal design
Smart design
Using the hexagonal design method, the ASP determines the site locations to cover user-defined zones based on the intersite distances defined for each zone.
Figure 19.5 ASP scenario configuration based on the hexagonal design method
Using the smart design method, the ASP determines the site locations to cover user-defined zones based on actual coverage
footprints of sites. The ASP calculates path losses for each deployed site and its coverage area based on calculated signal
levels compared with signal-level-based design objectives (minimum required signal level per zone and per clutter class).
Multiple signal-level based design objectives can be created as required.
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Figure 19.6 ASP scenario configuration based on the smart design method
Figure 19.7 Example of difference between hexagonal design and smart design methods
19.1.2 Population- and Traffic-driven Site Positioning
The ASP site positioning algorithm is by default based on surface area-wise calculations. For each new proposed site, it
determines the amount of coverage improvement brought about. In addition to covered surface, site positioning may also
be based on population data or network traffic data.
When population or traffic data is provided to the ASP, it also calculates the amount of improvement brought about by each
new site in terms of the population or traffic covered by it. This enables the ASP algorithm to adapt to the actual requirements
of the network being deployed.
Figure 19.8 Example of a site deployment scenario adapted to traffic density
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19.1.3 Site Deployment Objectives
The Atoll ASP enables you to define different objectives and rules for different site deployment zones. You can create and
use as many site deployment zones (polygons as well as vectors for roads and railway tracks) as needed. It is possible to
define a site template and an objective for each zone separately. Moreover, within each zone, site positioning criteria can be
defined per clutter class.
Figure 19.9 Site deployment configuration
Coverage-based objectives, used for the smart design method, can be created as needed. Each objective is a combination of
a required signal level and a surface-wise target. Coverage-based design objectives may also be fine-tuned per clutter class.
Figure 19.10 Site deployment objective definition
Automatic Site Positioning Results
Each site positioning scenario in the Atoll ASP provides an intelligent implementation plan, comprehensive results, and
statistics. It allows you to select the best sites to deploy, i.e., those that provide the highest gains, and analyse the
improvement according to the number of sites.
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The results of any ASP scenario include the following:

Statistics:
This tab provides global statistics and an overview of the solution proposed by the ASP. Statistics are provided for
each zone and vector processed by ASP. In addition to the overall statistics, site statistics are also listed.
Figure 19.11 Site positioning result statistics

Implementation plan:
The implementation plan includes the list of proposed sites to be deployed in the order of coverage improvement
provided by each additional site. The ASP allows you to find the best compromise between the number of sites to
deploy and the corresponding coverage improvement.
Figure 19.12 Site deployment plan in the decreasing order of improvement

List of sites to deploy:
The final list of new sites and parameters can be reviewed before implementation. It is possible to commit the
results to the Atoll document and rollback if needed. The path loss matrices, calculated by the ASP for the smart
design method, can also be copied along with the list of new sites.
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Figure 19.13 List of sites to deploy
Once the ASP results are committed, these can be analysed in Atoll.
Suburban area
Urban area
Railways
Downtown
Figure 19.14 Signal level coverage prediction based on an automatic site positioning scenario
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