Measurement Module
Atoll 3.3.0
© Forsk 2015
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Slide 1
Training Programme
1.
SPM Calibration Concepts
2.
Guidelines for CW Measurement Surveys
3.
Working With CW Measurements
4.
Automatic Calibration Method
5.
Analysing the Calibrated Model
6.
Calibration Process Summary
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Slide 2
1. SPM Calibration Concepts
Purpose of Model Calibration
Introduction to the Standard Propagation Model (SPM)
Requirements
Quality targets
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Slide 3
Purpose of Model Calibration
The propagation model is the basis of cell planning in mobile networks
Reliability of cell planning is closely related to the propagation model accuracy
A good model calibration is therefore required
To obtain a propagation model consistent with the actual radio environment
To improve the accuracy of coverage predictions
To properly estimate interference
The model calibration process entails three main procedures:
Collecting CW (Continuous Wave) measurement data
• Site location
• Constructing test platform
• Drive test
Post-processing the CW measurement data
• Data filtering
Calibrating the model
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Slide 4
Introduction to the Standard Propagation Model (SPM)
Standard Propagation Model (SPM)
Macrocell statistical propagation model
Well suited for predictions in the 150 to 3500 MHz band
Based on empirical formulas + set of parameters
Lmodel  K1  K2 .logd  K3 .logHTxeff   K4 .Diffraction Loss  K5 .logd.logHTxeff 
 K6 .HRxeff   K7 .logHRxeff   Kclutter.f clutter  Khill,LOS
Numerous elements considered in propagation
Frequency
Distance between TX and RX
Area type (urban, suburban, rural, etc.)
Geography (relief, vegetation, climate, etc.)
Effective height of TX/RX antennas
Default values in new projects !
Calibration is essential to accurately estimate
• Coverage predictions
• Interference
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Slide 5
Requirements (1/2)
Accurate and recent geo data
DTM and clutter resolution ≤ 25m for urban areas
DTM and clutter resolution ≤ 50m for rural areas
Vector map with main roads
CW measurement surveys
Site selection (for each area type – frequency band)
• 8 recommended (6 minimum ) sites for calibration
• 2 sites for verification
Selection of different area types representative of the studied city
• All main clutter classes should be represented
CW surveys must be performed by stringently following guidelines
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Slide 6
Requirements (2/2)
Drive Test data
Possible but not recommended !
Conversion to CW measurements is needed
Downsides
Real network is measured  Interference
Several frequencies are measured
Directional antennas  Accuracy of pattern (only a few points are relevant)
Low sampling rate for each measured station (Lee criterion can’t be met)
Signal measured over a short distance from the transmitter (model will not be calibrated for interference
evaluation)
 It is not recommended to use Drive Test data to calibrate a propagation model !
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Slide 7
Quality Targets
Overall objective :
Minimize the error between the propagation model and the CW
survey data
Quality targets for calibration sites
Global mean error on calibration sites < 1 dB
Global standard deviation on calibration sites < 8 dB
Mean error on each calibration site < 2.5 dB
Standard deviation on each calibration site < 8.5 dB
Quality targets for verification sites
Global mean error on verification sites < 2 dB
Global standard deviation on verification sites < 8.5 dB
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Slide 8
Training Programme
1.
SPM Calibration Concepts
2.
Guidelines for CW Measurement Surveys
3.
Working With CW Measurements
4.
Automatic Calibration Method
5.
Analysing the Calibrated Model
6.
Calibration Process Summary
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Slide 9
2. Guidelines for CW Measurement Surveys
Site Preselection criteria
Survey route criteria
Radio criteria
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Slide 10
Site Preselection Criteria
Surrounding
Very representative of area type
Major clutter classes equally represented
No major obstruction within a radius of 150 to 200m from the CW sites
Low diffraction within a 10km radius (rural zones)
Enough roads all around the site
Inspection on site
Possibility to set up omnidirectional antenna
• No obstacle on any side
Panoramic photographs
Report site details: precise height, coordinates ...
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Slide 11
Survey Route Criteria
Distance
Up to noise floor of the receiver
• Rural ± 10kms / Suburban ± 2kms / Urban ± 1km
Equal number of samples near and far in all directions
Clutter
Routes through major clutter classes
Avoid forests and lakes between transmitter and receiver
Maps
Supply vector maps of survey routes to import in Atoll
Check that survey routes and roads (vector data or scanned maps) match !
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Slide 12
Radio Criteria (1)
Frequency
3 contiguous unused channels for GSM
1 unused carrier for UMTS
Only one channel must be measured
Interference must be checked before each drive
Equipment data
Antenna patterns + downtilt + azimuth (if not perfectly omnidirectional)
Antenna height + transmit power + transmission gain (antenna) and losses (feeder)
Receiver height + sensitivity + reception gain and losses
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Slide 13
Radio Criteria (2)
Signal measurement
Lee criterion: at least 36 samples over 40λ (for f ≥ 900 MHz)
• Maximum vehicle speed depends on equipment’s sampling rate
Sampling Rate
at 900 MHz
Sampling Rate
at 2100 MHz
(samples per second)
(samples per second)
45
100
60
68
150
90
90
200
120
113
250
150
Max. Speed (km/h)
Averaging samples over 40λ aims to remove fast fading effect !
Measurements after averaging
At least 5000 points per site
Typical number: between 10000 and 20000 points
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Slide 14
Training Programme
1.
SPM Calibration Concepts
2.
Guidelines for CW Measurement Surveys
3.
Working With CW Measurements
4.
Automatic Calibration Method
5.
Analysing the Calibrated Model
6.
Calibration Process Summary
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Slide 15
3. Working with CW Measurements
Creating a CW measurement path
By copying – pasting X,Y, measurement
By importing any ASCII format file
• Standard import as in Excel
• Option of importing any additional information
related to CW measurement points
• Definition and storage of import configurations
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Slide 16
3. Working With CW Measurements
CW Measurements: Table
List of all measurement points with their attributes and additional information
Coordinates of
points
Altitude, Clutter
classes and
heights, Distance,
etc. read from the
Geo data
Signal
Measured
values
Standard content management and tools (filters, copy-paste, etc...)
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Slide 17
3. Working With CW Measurements
CW Measurements: Properties
For
predictions
along
the
CW
measurement path, you can either use
Existing path loss matrices or recalculate
them by choosing a specific Propagation
model
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The points can be displayed according
to any data contained in the
measurement Table
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Slide 18
3. Working With CW Measurements
CW Measurements: Calculations and Statistics
To calculate the
predicted signal level
of the reference
(and any other
optionally added)
transmitter along
the considered path.
Note: This can also
be run from top
folders.
To compare statistics
between measured and
predicted signal levels.
Note: This can also be
run from top folders.
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Slide 19
3. Working With CW Measurements
CW Measurements: Filter (at Folder level)
Distance, Measurements
values and Azimuth
filtering
Advanced filter on additional
survey data
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Clutter Classes filtering
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Slide 20
3. Working With CW Measurements
CW Measurements: Filtering Assistant and Filtering Zones
Tool to filter the data
path in an more
advanced way than in
the Filter dialogue
available at the folder
level (previous slide)
Tool to exclude some points from the measurement path
according to a drawn polygon (all points within the polygon
will be filtered out)
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Slide 21
3. Working With CW Measurements
BEFORE
CW Measurements: Smoothing
Create a sliding window to smooth the
measured signal strength
AFTER
Smoothing can be used to limit fading effect
Smoothing keeps the number of measurement points unchanged
Smoothing cannot be used to average gross CW measurements
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Slide 22
3. Working With CW Measurements
CW Measurements: Synchronise the Table, the Map and the CW Measurements Tool
Synchronisation:
- Map
- Table
- CW Measurements Tool
Measured signal level
Analysis of a
specific CW
measurement
path
Predicted signal level
Display of any
attribute related
to a given path
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Slide 23
Training Programme
1.
SPM Calibration Concepts
2.
Guidelines for CW Measurement Surveys
3.
Working With CW Measurements
4.
Automatic Calibration Method
5.
Analysing the Calibrated Model
6.
Calibration Process Summary
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Slide 24
4. Automatic Calibration Method
CW measurements pre-processing
Calibration / verification stations
Initial model
Calibration wizard
Final model
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Slide 25
CW Measurements Pre-processing
Correspondence between Measurements and Geo data
Projection checking
• Check that CW measurements and roads (from vector maps) match
Routes checking
• Check that CW measurements respect planned survey routes
Surrounding checking
• Check, with panoramic photographs, that there is no obstacle
• Option of setting an angle filter to avoid attenuation due to obstacles
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Slide 26
CW Measurements Pre-processing
Filtering
Available at the Folder level for each site
Will be applied to all the measurement paths in that folder
Distance,
Measurements values
and Azimuth filtering
Advanced filter on additional
survey data
© Forsk 2015
Clutter
Classes
filtering
Will permanently remove
the points outside the filter
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Slide 27
CW Measurements Pre-processing
Distance filtering (Min Distance / Max Distance)
Typical min value: 200 m (not representative of mean propagation)
Typical max value: 10 km (rural area)
Signal filtering (Min Measurement / Max Measurement)
Filtering out the measurements above the receiver overload: typical value -40 dBm
Filtering out the measurements below the “receiver sensitivity + target standard deviation”
typical value: -120 + 8 = -112 dBm
• In order to avoid noise saturation effect in statistical results
Azimuth filtering
To remove points in a certain angle
Filtering assistant
In addition to the Filter located at the Folder level, you can define more precise filtering depending on the
CW measurement file
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Slide 28
CW Measurements Pre-processing
Filtering assistant (1/2)
Display of M = f ( 10log(D) )
Possibility to keep
the selected points
or to exclude them
Selection rectangle  simultaneous Signal/Distance filtering
Signal/Distance
filtering
according to the
selection
rectangle
Selection
Rectangle
Azimuth
filtering on the
measurement
points
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Slide 29
CW Measurements Pre-processing
Filtering assistant (2/2)
Remaining points after the
Distance, Signal level, Azimuth
and Clutter classes filtering
Remove all previous filters applied
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Slide 30
CW Measurements Pre-processing
Final filtering (1/2)
Display each CW measurement according to their Measured signal level
Check that propagation loss is spatially homogeneous
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Slide 31
CW Measurements Pre-processing
Final filtering (2/2)
Removing which points?
• Sudden drop of signal level
• Suspicious areas (
Waveguide effect!)
How?
• Delete from the CW measurement table
• Draw Filtering zones
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Slide 32
Calibration / Verification Stations
Calibration stations
Stations so that measurements cover the whole area
Avoid keeping stations with a lot of common points
Verification stations
Stations so that measurements are inside covered area (not at edges!)
Major part of their covered areas are also covered by calibration stations
How many ?
If 7-8 measured stations:
• 6 for calibration; 1-2 for verification
If < 7 measured stations:
• All stations used for calibration
• Verification performed with same stations
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Slide 33
Initial Model
General SPM formula
Ki values
Lmodel  K1  K2 .logd  K3 .logHTxeff   K4 .Diffraction Loss  K5 .logd.logHTxeff 
 K6 .HRxeff   K7 .logHRxeff   Kclutter.f clutter  Khill,LOS
Let K6 = 0
Others will be calibrated
Effective antenna height
Choose method according to terrain relief
Modify height from transmitter properties
Can be selected by the calibration process
Recommendation if terrain is hilly:
“Enhanced slope at receiver” method
Hilly terrain correction “1-YES”
Recommendation if terrain is flat:
“Height above average profile” method
Hilly terrain correction “0-NO”
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Slide 34
Initial Model
Max distance
Forced to 0 during calibration
If >0 no continuity ensured
KClutter
= 1 is recommended
Multiplying factor of clutter losses
Minimum loss
= Free space loss
Avoid unrealistic values
Profiles
Radial optimisation
• Quicker
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Slide 35
Initial Model
Heights of Clutter taken or not into account in Diffraction:
If you have a Clutter Heights file
• Then put “1-YES” in the box
If you only have a Clutter classes File
• 2 approaches:
• If Clutter Classes file has a very fine resolution
• You can put “1-YES” and the tool will take into account
the average heights defined in your clutter classes file
• You should keep all the losses per clutter class to Zero
• If Clutter Classes file resolution is low
• Do not take into account the average heights defined in
your clutter classes file (“0-NO”), but instead add a Loss
per Clutter class type
Receiver on top of clutter
By default “No”
Only useful for fixed receivers
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Slide 36
Initial Model
Clutter Classes Losses can be calibrated
You need to define the Max distance from the Receiver (towards the Transmitter) for which the different
clutter classes will be considered (typically 5X the clutter resolution)
Choice between 4 types of Weighting functions (Uniform, Triangular, Logarithmic, Exponential)
n
f clutter    Li w i
i 1
wi=f(d'i)
Uniform
Triangular
Logarithmic
Exponential
wi
d'i
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Slide 37
Initial Model
Reference model
Create a Reference model containing all the previous settings
Duplicate this Reference model for each calibration, and give it a relevant name
When duplicated, choose an appropriate name and pay specific attention to:
• Methods used for Diffraction and Effective Antenna Height calculation
• Value of Kclutter
• Hilly terrain correction
• Heights of Clutter considered or not in Diffraction
• Clutter Range and associated Weighting function
Start from the Reference model for each calibration trial
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Slide 38
Calibration Wizard
Automatic calibration overview
Algorithm based on solving a least-squares problem
Calculation of the best solution in terms of root mean square :
RMS 
δ M
2
2
Simple, fast and reproducible procedure
First Step
Selection of calibration stations
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Slide 39
Calibration Wizard
Second step (1/2)
Selection of the Parameters to calibrate
Possibility to modify their ranges
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Slide 40
Calibration Wizard
Second step (2/2)
Recommended ranges
Constant
Min
Max
K1
0
100
K2
20
70
K3
-20
20
K4
0
1
K5
-10
0
K7
-10
0
It is recommended to leave K6 to 0
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Slide 41
Calibration Wizard
Final step
Display of “Before” and “After” parameters values and statistics (Mean error, Standard Deviation, RMS)
Commit will update the model you are calibrating with the new values of Ki, height and diffraction
methods as well as the Clutter Losses
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Slide 42
Final Model
Extrapolate non-calibrated clutter losses (1/2)
Non-calibrated clutter classes must not have their clutter losses left to 0
• Could lead to high error where these classes are present
Must be extrapolated from
• Calibrated clutter losses (from other propagation model)
• Typical losses (here centred on the Urban class)
© Forsk 2015
Clutter class
Typical loss
Dense Urban
from 4 to 5
Woodland
from 2 to 3
Urban
0
Suburban
from -5 to -3
Industrial
from -5 to -3
Open in urban
from -6 to -4
Open
from -12 to -10
Water
from -14 to -12
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Slide 43
Final Model
Extrapolate non-calibrated clutter losses (2/2)
Centre clutter losses
• Relative difference between clutters kept unchanged
• Use K1 to balance
Example:
After calibration, model centred on suburban:
K1=17.4
Losses: Dense Urban = 6.5
Wood = 5.7
Urban = 3.5
Suburban = 0
After centring, new values:
K1=20.9
Losses: Dense Urban = 3
Wood = 2.2
Urban = 0
Suburban = -3.5
Apply scaling factor
• Adapt typical losses (or calibrated ones coming from other model) to the calibrated model
-12
Open
-8
Extrapolated
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C
0
e
n
t Urban
r
e
d 0
calibrated
4.5
Typical Losses
Dense Urban
“MyModel” Losses
3
calibrated
Define Scaling Factor
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Slide 44
Training Programme
1.
SPM Calibration Concepts
2.
Guidelines for CW Measurement Surveys
3.
Working With CW Measurements
4.
Automatic Calibration Method
5.
Analysing the Calibrated Model
6.
Calibration Process Summary
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Confidential – Do not share without prior permission
Slide 45
5. Analysing The Calibrated Model
Statistics (1/2)
Apply the new calibrated propagation model to your CW sites
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Slide 46
5. Analysing The Calibrated Model
Statistics (2/2)
Check the Quality Targets (Std Deviation and Mean Error values) on the Calibration and Verification sites
Statistics available
• Globally,
• per Clutter class,
• per Transmitter, and per Measurement path
Possibility to run the Statistics
on all the Measurement paths,
or on specific ones
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Slide 47
5. Analysing The Calibrated Model
Correlation (to be checked on the Calibration sites)
Through the Assisted Calibration Wizard
Displays, for each parameters to be calibrated (K1, K2, K3, etc.), the correlation of the variables log(D),
log(Heff), Diff, etc. with the global Error
Check if the Correlation values are between -0,1 and +0,1
The calibration wizard will attempt
to bring the correlation as close to
zero as possible. The results will
be a correction value that will be
added or subtracted to the initial
Ki value in the model
Commit will apply the Correction values to the corresponding Ki values
Notes: This will not take into account the Ki Ranges
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Slide 48
5. Analysing The Calibrated Model
Display Error
Recalculate the Predicted signal values (P) according to the calibrated propagation model
Display the Error (P – M) between the CW Measurements values (M) and the Predicted values (P)
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Slide 49
5. Analysing The Calibrated Model
Display CW Measurements & associated Signal Level study
Use the same shading on both displays to be able to compare them
For each site, one by one  Check the global behaviour of calibrated model
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Slide 50
5. Analysing The Calibrated Model
CW measurement and Profile windows
Analysis along the path
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Slide 51
Training Programme
1.
SPM Calibration Concepts
2.
Guidelines for CW Measurement Surveys
3.
Post-process the CW Measurements Data
4.
Automatic Calibration Method
5.
Analysing the Calibrated Model
6.
Calibration Process Summary
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Confidential – Do not share without prior permission
Slide 52
Calibration Process Summary
Before starting...
Check Geographical Database quality & accuracy (DTM, clutter, vectors...)
Define environments (hilly, flat / urban, rural...) to specify the required number of propagation models to
be calibrated
Measurements preparation
Sites selection
Survey roads
Fulfil radio criteria
Make & Average measurements
Create Transmitters used for measurements in the Atoll document
With exact configuration (coordinates, antenna type & height, EIRP, losses)
Analyse & Filter measurements ( Pre-processing)
Keep representative points and remove suspicious ones
Choice of calibration / verification sites
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Slide 53
Calibration Process Summary
Run the automatic calibration
Display statistics and compare results with target values (Std deviation and Mean error)
for calibration sites: Global and Individual checking
for verification sites: Global checking
Extrapolate non-calibrated clutter losses
Analyse calibrated model
Display statistics
Check correlation
Maps displaying Error(P-M), Measurements & Signal Level Study, etc.
Apply the calibrated model
Apply resulting standard deviation per clutter in the clutter class description
Apply the calibrated model to network’s transmitters (Transmitter Properties\Propagation tab)
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Slide 54
Thank you
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Slide 55