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Document Number: P/TR/005/O036/v5
This manual prepared by:
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UMTS Advanced Cell Planning and
Optimisation
O036
Contents
1
2
3
Introduction
7
1.1 Course Overview
7
Optimisation Overview
10
2.1 What is Optimisation?
10
Network Dimensioning and Planning
17
3.1 Introduction
17
3.2 Simulating the Effect of Imperfect Site Location and High
Sites 25
3.3 Provisioning for Asymmetric Traffic
32
3.4 Using More Appropriate Path Loss Models
36
3.5 Serving Very High Traffic Densities
42
3.6 Evaluating Simulator Results
45
3.7 Pilot Pollution
46
4
Simulation Examples
51
Site Location Issues
55
4.1 The Ideal Situation
55
4.1.1
5
7
58
4.2 Hot Spots
4.3 Site Density
4.4 High Sites
60
64
70
Factors Limiting Capacity
74
5.1
5.2
5.3
5.4
74
75
78
81
Cell Throughput
The Effect of Mobility on Capacity
Maximising Frequency Re-use Efficiency
Downlink Capacity and Orthogonality
5.4.1
6
Mis-placed sites.
Pilot SIR as an indicator of downlink capacity
85
5.5 The Noise Rise Limit
87
Antenna Selection
89
6.1 Antenna Gain & Coverage
6.2 Repeaters
6.3 Roll-out Optimised Configuration (ROC)
89
91
93
Soft Handover Issues
97
7.1 Macro-diversity & Maximal Combining Gain
7.1.1
Exercise 1
97
101
7.1.2
8
9
10
11
Exercise 2
102
Parameter Planning
107
8.1
8.2
8.3
8.4
107
108
110
111
Introduction
Pilot Channel Power
Maximum Power per User
Common Channel Powers
Multi-frequency Planning
112
9.1 Network Performance
112
Micro-cell Planning
114
10.1 Introduction
10.2 Micro-cells targeting hot spots
114
115
Coverage & Capacity
125
11.1
11.2
11.3
11.4
125
129
132
136
Introduction
Exercise Link Budgets
Downlink Limited
Predicting the Capacity of the Downlink
11.4.1
Example
12
Analysis, Prediction and Optimisation of Downlink
Capacity.
12.1 Analysis of Identical Users
12.1.1
Verification Using A Monte Carlo Simulator.
12.2 A Rapid Method for Estimating Downlink Capacity
12.2.1
12.2.2
12.2.3
13
14
101
7.2 Optimising Soft Handover Parameters
Isolated Cells
An Evenly Loaded Network
Uplink-downlink balance.
149
151
152
154
155
155
157
159
12.3 Interim Conclusion
12.4 Simulator-aided Prediction for Unevenly-loaded
Networks
12.5 Optimisation Issues
12.6 Conclusions
159
159
161
162
Masthead Amplifiers
177
13.1 Introduction
13.2 MHA example
177
178
Diversity Antennas
181
14.1 Introduction
181
14.2 Definition of Fading
182
14.3 Receive Diversity
183
14.4 Transmit Diversity
185
14.5 Multi-User Detection MUD
192
14.6 Predicting the Effect of Different Coverage and Capacity
Enhancement Devices
196
15
16
Smart Antennas
203
15.1 Introduction
203
Practical Simulation
211
16.1 Exercise using MHA’s
211
16.1.1
16.1.2
16.1.3
Network with no MHA’s
Insert MHA at centre of network
All sites with MHA’s
16.2 Downlink Limited case – MHA’s
16.2.1
16.2.2
Downlink limited case for network without MHA’s
MHA applied to all sites
16.3 Transmit Diversity
16.3.1
16.3.2
16.3.3
16.3.4
16.3.5
16.3.6
17
20
21
217
217
218
219
220
221
222
17.1 Customer Focus
17.2 Key Quality Indicators KQI’s
17.3 Key Performance Indicators KPI’s
223
224
225
Exercise 17.3
226
17.4 Measurements
226
Drive Test Measurements
236
18.1 The concept of Drive Testing
18.2 Test mobile Measurements
18.3 Interpretation of Measurements
236
238
241
Using Measurements to Validate Improvements
Comparing Uplink and Downlink Capacity
245
245
18.4 Using Measured Data
246
Cluster Identification
250
19.1 Procedure and Measurements
250
Scrambling Code Example
255
20.1 Case Study
255
Neighbour Planning
261
21.1 Neighbour Lists
261
21.1.1
21.1.2
21.1.3
22
215
216
223
18.3.1
18.3.2
19
215
Measuring Success
17.3.1
18
Voice Traffic – NO Tx diversity
64kbps Service – NO Tx diversity
Tx Diversity Voice Service
Tx Diversity 64kbps Service
Tx and Rx Diversity Applied – Voice Service
Tx and Rx Diversity Applied to 64kbps Service
212
213
214
Initial Neighbour List Generation
Optimisation of Neighbour lists:
Inter-freq & Inter-system Neighbour Planning:
263
264
266
Automation Topics
268
22.1 Modelling
22.2 Total Power Targets
268
271
23
24
Future Impact of Standards
273
23.1 Observations of Release 5 and beyond
273
From Initial Roll-Out to Mature Network
275
24.1 Introduction
24.2 Initial Roll-Out
275
276
24.2.1
25
The Initial Plan
276
24.3 Evolution of the Network
24.4 Concluding Remarks
277
288
Appendix
291
25.1 Amplificadores MHA
291
1 Introduction
1.1
Course Overview
The objective of this three day course is to provide delegates with
knowledge of optimisation methods and techniques which will enable
them to plan, improve and optimise UMTS 3g networks. Exercises and
examples via software and a state-of-the-art 3g simulator will be provided
to aid in the understanding of concepts and theories used in optimisation.
Introductory Session
Aims of Course
•
To deepen the understanding of UMTS networks so as to
plan a network with greater confidence and allow specific
required improvements to be targeted.
•
To be able to evaluate the benefits that can be obtained
from fitting capacity enhancing devices to the UMTS
infrastructure.
•
To attain an understanding of the optimisation procedures
available within UMTS.
The function and purpose of optimisation.
•
•
To understand how to maximise the benefit of making drivetest measurements.
•
The use of simulation to aid in optimisation.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
7
Introductory Session
Course Schedule
• A module may take more than one session
to complete.
• During each module, questions and
exercises are provided.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
8
2 Optimisation Overview
2.1 What is Optimisation?
Depending upon your position within your organisation this question will mean
quite different things. Whilst business is about making money, the engineer’s goal is
usually focused on network efficiency. These two issues are linked but the strategy
for change and time scales can be, and very often are, different.
Business will benefit if the quality of service experienced by customers improves. The
engineer should be focused on obtaining the maximum performance and hence
delivering the optimum customer experience from a given resource.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
10
Optimisation Overview
What is Optimisation ?
• Quality of Service
• Applications
• Network Coverage/Capacity
• Competitive Advantage
• Radio Propagation
• Measurement Signals
• UE
• UTRAN
Optimising a UMTS network is distinctly different from the optimisation
of a GSM network. The fact that we have a single frequency on a cell
layer poses challenges for the network planner. For example, it is no
longer possible to use a frequency plan to help reduce the impact of
poorly position sites. Further, there is no fixed capacity of a TRX in a
UMTS network. The throughput possible depends on the services being
utilised and the radio environment.
The high level of mutual interference between users and cells leads to a
trade-off between capacity and coverage. As use of the network
increases, so does interference. This higher level of interference reduces
the maximum path loss over which a connection can be satisfactorily
made. Optimising for coverage and optimising for capacity will entail a
different approach, both to planning and to infrastructure investment.
When optimising any network, it is vital that any improvements can be
confirmed by means of measurements made on the network. Feedback
from drive-test measurements and OMC reports must be incorporated
into a continuous cycle of optimisation and monitoring.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
11
Optimisation Overview
Why is Optimising different for UMTS ?
• Single Frequency
• Cannot frequency plan around problems
caused by “rogue” sites.
• Flexible structure sensitive to small changes
in performance
• Air interface performance directly affects
capacity and coverage.
Optimisation Overview
Air Interface affecting Network Performance ?
• Suppose we are able to reduce the target Eb/No on
the uplink by 1 dB.
• Capacity increased by 25%
• Range increased by
0.1
10
exponent
• (7% if exponent equals 3.5)
• Area increased by 14%
• So both Capacity and Coverage Increase
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
12
Optimisation Overview
Coverage/Capacity Trade-off ?
• We do not have to accept a 25% capacity increase and a 14%
coverage area increase. We could make capacity our goal. In
this case we could increase the Noise Rise limit by 1 dB, and
reduce Eb/No by 1dB
Loading Factor = 1 - 10
-NR
10
• The improvement in capacity depends on the pre-existing Noise
Rise Limit. ( Eb/No 4.8dB, voice 12.2kbps i=0.6)
Original
Noise Rise
Limit
Coverage
km2
Throughput
kbps
New Noise
Rise Limit
Throughput
kbps
Total
Capacity
Increase
1 dB
42.72
158.5
2 dB
366
131%
3 dB
32.84
390.4
4 dB
597.8
53%
7 dB
19.4
634.4
8 dB
841.8
33%
Optimisation Overview
Coverage/Capacity Trade-off ?
• We could make coverage our goal. In this case we could fix the
capacity, this will reduce the loading factor and reduce Eb/No by
1dB
NR = −10 × log(1 − η )
• The improvement in coverage depends on the pre-existing
loading factor. ( Eb/No 4.8dB, voice 12.2kbps i=0.6)
Existing
Loading
Factor
Noise
Rise
dB
Capacity
kbps
Coverage New
Loading
km2
Factor
New
Noise
Rise dB
Coverage
km2
Total
Coverage
Increase
40%
2.22
317.2
36.39
31.46%
1.64
44.79
123%
65%
4.56
512.4
26.75
50.83%
3.08
37.05
138.5%
80%
6.99
634.4
19.43
62.93%
4.31
31.52
162%
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
13
Optimisation Overview
Capacity/Coverage Enhancing Devices
• Because of facts such as this, devices to give improvements of a
few dB can be purchased.
• These include:
• Mast Head Amplifiers
• Diversity (uplink and downlink)
• Multi-User Detection
• Smart Antennas
• Any one device will usually give improvement in the uplink or the
downlink but not both.
• Important to be able to determine which direction is limiting network
performance.
• Improvement in performance must be predicted so that the best
way forward can be implemented.
Optimisation Overview
Measuring and Monitoring
• Any improvement in quality must be measurable.
• Improvement should be:
• User experience:
•
fewer blocked calls;
•
new services being offered;
•
greater coverage.
• Revenue generation:
•
greater network capacity;
•
higher revenue services offered.
• Optimisation is part of the overall quality cycle.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
14
Optimisation Overview
Course Structure
• How to Plan a Network - Effectively
• Getting the most out of a network with “conventional” equipment.
• Analysing and Comparing devices that will enhance
performance
• Selecting the item that will provide the most benefit.
• Network Measurements and Optimisation Procedures.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
15
3 Network Dimensioning and
Planning
3.1 Introduction
It is necessary to be able to apply all the understanding of the technology
and capacity, dimensioning and link budget calculations in a practical
situation. Accordingly, it is imagined that a network is to be planned
providing a certain capacity over a certain area. Initially, certain
parameters will be over-simplified when compared with what can be
expected to be encountered in practice. For example, the first assumption
is that the terrain is flat, the traffic distribution is uniform and that the
network will be offering only a single service. After dimensioning and
examining the predicted performance of such a network, the effects of
problems such as “high sites” and being unable to position base stations
exactly where required will be demonstrated. After that, more realistic
terrain data is introduced together with the need to be able to
accommodate varying traffic density.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
17
Planning a UMTS Network
Planning a UMTS Network
• We will assume that a coverage area is defined.
• We have mapping data.
• We have a traffic forecast (in this case a
single voice service with uniform distribution.)
Planning a UMTS Network
The Philosophy
• A strategy needs to be defined.
• For this environment, “continuous coverage for voice services” could
define the high level approach.
•
Other issues: Path Loss; Cell Range
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
18
Planning a UMTS Network
Link Budget
• Crucial to the planning process.
• Derived assuming a particular
Noise Rise.
• Combined with Path Loss model
to determine cell range.
Voice Service
Eb/No
Power Control
Shadow Fade
Rise
3 dB
Antenna Gain
Proc Gain
Mobile Tx Pwr
Cell Noise Floor
Max Path Loss
Range
5 dB
2 dB
4 dB
Noise
18 dBi
25 dB
21 dBm
-100 dBm
150 dB
2.35 km
Planning a UMTS Network
Iterative Spreadsheet Dimensioning
••• Keep
Re-calculate
Range
using
CarryCalculating
out linkrange
budget
to and
re-assessing
predicted
Noise
Rise.
Rise.
determineNoise
range
(remember
link budget assumes a NR)
• Finally, the iterations should
•• Re-assess
Assess loading
the loading
of cell of
and
the
converge so that the assumed
cell
predict
and Noise
re-predict
Rise.theThis
Noise
will
and predicted values of Noise
Rise.
differ from assumed Noise
Rise agree.
Rise.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
19
Planning a UMTS Network
Graphical Explanation
• Gathering More traffic increases Noise Rise and reduces Range.
• Increasing Range causes more traffic to be gathered.
Range/PathLoss
Intersection gives the
operating point
Number of active users
Planning a UMTS Network
A complication
• Noise Rise predicted from
estimated peak use of cell.
• Range calculated from average
number of users.
Range/PathLoss
Intersection gives the
operating point
• Additionally, soft capacity must be
Number of active users
considered.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
20
Planning a UMTS Network
Spreadsheet Method
• All relevant parameters (Eb/No, Tx Power etc.) known.
• From traffic forecast and coverage area, calculate density.
•
Make initial estimate of the number of “trunks” required per cell.
•
Estimate Noise Rise and hence “Cell Range 1”
•
Using Erlang B and considering soft capacity estimate Erlangs served.
•
Estimate area and hence “Cell Range 2”
•
Adjust number of trunks until “Range 1” = “Range 2”
Planning a UMTS Network
Spreadsheet Method
•
All relevant parameters (Eb/No, Tx Power etc.) known.
•
From traffic forecast and coverage area, calculate density.
Estimate Number of
Estimate Noise Rise
Simultaneous
Connections per Cell
Estimate Number of
Erlangs Served per Cell
From Traffic Density
forecast, estimate
No
cell range
Estimate Maximum
Estimate Maximum
Path Loss (using
Path Loss (Uplink)
Propagation model).
Path Losses Equal?
The method outlined above was used to dimension a network given the
following input parameters:
Voice Service
Data Rate:
12200 bps
Eb/No
5 dB
Power Control Margin
Antenna Gains
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
2 dB
18 dBi
21
“other to own” interference ratio
0.6
Shadow Fade Margin
4 dB
Coverage Area
1000 km2
Traffic to be Served
4000 Erlangs
Mobile Transmit Power
21 dBm
Cell Noise Floor
-102 dBm
Path Loss Model:
Loss = 137 + 35log(R) dB
The result is that 82 sites would be required. The Noise Rise limit should
be set to 3.9 dB in order to maintain continuous coverage.
Planning a UMTS Network
Example Output
• For voice service over an area of 1000 km2 offering 4000 Erlangs of Traffic:
• 82 sites with 246 cells were required.
• Noise Rise Limit of 3.9 dB was required to maintain
continuous coverage.
It is possible at this stage to place sites on a map such that continuous
coverage can be maintained. However, it is highly likely that the actual
location of sites will not be as required. Further, assumptions made when
creating the spreadsheet may not be accurate in practice. For these
reasons, and for other including those listed below, it is necessary to
utilise a planning tool that will consider practical variations from the
initial broad assumptions made.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
22
Planning a UMTS Network
The need for a tool
• If this can be done using a simple calculator, why do we need a planning tool?
•
•
•
We need to be able to simulate the effect of imperfections.
•
Sites not placed perfectly
•
terrain/environment factors
•
Uneven traffic distribution
Some parameters (for example interference ratio, i) have been assumed.
Mixed services will have different coverage areas.
• Planning tool can validate the strategy.
Planning a UMTS Network
Using the 3G Planning Tool
• The coverage area was filled with the correct number of sites and traffic
was spread across the region.
• Coverage was checked to be in accordance with requirements.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
23
Planning a UMTS Network
Summary of Initial Results
• Parameters:
•
•
•
•
Eb/No = 7 dB (Incorporating Eb/No and Power Control)
S.D. = 7 dB
4000 Terminals
NR limit 3.9 dB
• Results:
•
•
Coverage Probability 98.0%
Almost all failures due to Noise Rise
Planning a UMTS Network
Action taken
•
3.9 dB NR limit provides continuous coverage even when all cells are
simultaneously at their maximum load.
•
In reality not all cells would be
simultaneously at their maximum
loading. The neighbour can often
“assist” an overloaded cell.
•
•
Noise Rise limit can be raised.
Noise Rise was raised to 5 dB.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
24
Planning a UMTS Network
Summary of Results
• Parameters:
•
•
•
•
Eb/No = 7 dB (Incorporating Eb/No and Power Control)
S.D. = 7 dB
4000 Terminals
NR limit 5.0 dB
• Results:
•
•
Coverage Probability 99.7% (c.f. 98.0%)
Even split of failures between NR and UL Eb/No
Planning a UMTS Network
Next Step
• As Noise Rise limit was raised without any apparent gaps in coverage
appearing, it should be possible to raise the amount of traffic served.
• Traffic spread raised to 4600 terminals.
• Results:
•
•
Coverage Probability 98.7% (c.f. 99.7%)
83% NR and 17% UL Eb/No.
3.2 Simulating the Effect of Imperfect Site
Location and High Sites
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
25
Planning a UMTS Network
Simulating the Effect of Problems
• Imperfect location of sites.
• 50% of sites moved randomly by
up to 1 km from ideal position.
• Gaps appear in coverage.
Planning a UMTS Network
Summary of Results
• Parameters:
•
•
•
•
•
Eb/No = 7 dB (Incorporating Eb/No and Power Control)
S.D. = 7 dB
4600 Terminals
NR limit 5.0 dB
Results:
•
•
•
Coverage Probability 97.5% (c.f. 98.7%)
78% NR and 22% UL Eb/No
Uneven distribution of failures
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
• Results:
•
“Problem area” gives 95%
coverage probability (c.f. 97.5% for
whole area).
26
Planning a UMTS Network
Action taken
•
•
Antennas were re-pointed in an attempt to restore coverage.
•
Problem is uneven distribution of load
due to improper placement of sites.
Those sites with largest area suffered
Noise Rise failures.
•
NR failure occurs if more than approx.
29 terminals attempt to access a cell.
Average is 19 terminals.
Improvement was marginal (96.0% c.f. 95.8%)
Planning a UMTS Network
Problems caused by High Sites
• 15% of sites made “high sites” with a
path loss 10 dB less than that of
“normal” sites at a given range.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
27
Planning a UMTS Network
Problems caused by High Sites
• Uneven loading causes
disastrous results.
• Coverage probability
reduced from 98.7% to
78.6%.
Planning a UMTS Network
Problems caused by High Sites
• Probability of NR failure
very high in high site area.
• FRE for high site ~ 48%
(63% average)
• Throughput for high site ~
26 E (18 E average)
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
28
Planning a UMTS Network
Action taken
• Excess coverage area reduced by down-tilting the antennas of the
high-sites.
•
•
Result:
Coverage probability increased to 95.1% (c.f. 78% before
down-tilting and 98.7% with “perfect” sites).
Planning a UMTS Network
Alternative Action
•
Instead of down-tilting, reduce pilot power of high sites by 10 dB to equalise service areas.
•
•
Result:
Problem made worse! This is because terminals still caused Noise Rise even though they
were not connected. Reduction of High Site service area causes an increase in Mobile Tx
power hence aggravating the problem.
Pilot Power scaled to equalise service areas. Pilot Power Equal
Mobile Connects to Low Site - Tx Power increased
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
Mobile Connects to High Site
29
Planning a UMTS Network
Alternative Action
• Increased NR Limit of High Site by 10 dB
• Decreased Max Tx power, Common Chan power and Pilot power by
10 dB.
•
•
Result:
•
High NR experienced by High Site but continued to perform
satisfactorily.
•
Detecting the existence of High Sites is crucial.
A dramatic improvement. Performance of network
indistinguishable from ideal case.
Planning a UMTS Network
Spotting a High Site
• Examining the Best Server by
Pilot array is informative.
• Spreading a traffic terminal and
examining traffic captured is
possibly more informative as it
considers traffic distribution.
•
•
•
•
•
•
•
•
•
•
•
•
•
Site35C:
Site36A:
Site36B:
Site36C:
Site37A:
Site37B:
Site37C:
Site38A:
Site38B:
Site38C:
Site39A:
Site39B:
Site39C:
18.0946
18.2301
19.5065
18.4447
13.9719
14.4915
18.2414
37.0476
38.7644
36.72
10.6173
18.9417
10.1203
– High Site
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
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Planning a UMTS Network
High Sites - a final word
• There is no single definition of a high site.
• Do not think that it is “wrong” to place UMTS base stations on
hilltops.
• High sites tend to gather uplink interference generated by other
users.
• Problems occur as area becomes more heavily loaded (if the traffic
is reduced from 4000 terminals to 2000 terminals, coverage is
excellent even with “untreated” high sites).
• If coverage area is very lightly loaded - no problem.
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
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3.3 Provisioning for Asymmetric Traffic
It is common to find that the downlink is not being required to transmit at
full power. In fact there is often about 10 dB extra power capacity on
average in the downlink direction. This can be utilised to service
asymmetric (downlink only) traffic requirements. It is possible to
estimate the amount of traffic possible by attempting to establish
approximate values for Noise Rise before at the current average base
station transmit power (as obtained from the cell reports) and at the
maximum transmit power. Then the extra loading possible can be
determined.
Because no two mobile stations are likely to experience exactly the same
Noise Rise, the approximate values of traffic calculated should be
validated by using a planning tool with a UMTS simulator.
In the case being studied it was noted that the Uplink was approximately
had a 60% loading factor on average. Because of the effect of
orthogonality, it is expected that the loading on the downlink for the same
amount of traffic would be approximately 40%. Thus the mobile stations
could expect to experience a Noise Rise of 2.2 dB on average. It is noted
that the average base station transmit power was 34 dBm. The maximum
power available is 42 dBm. We need to be able to establish the Noise Rise
that would be caused if the transmit power rose to 42 dBm given that a
transmit power of 34 dBm causes a Noise Rise of 2.2 dB. The necessary
equations are:
Noise Rise increase on downlink on increasing Node B transmit power from B dBm to C
dBm
(
New Noise Rise = 10 log 10 1 + 10 (C − A ) / 10
) where
⎛ 10 B 10 ⎞
⎟ where X is the noise rise in dB with transmit
⎜ 10 X 10 − 1 ⎟
⎠
⎝
A = 10 log10 ⎜
power B dBm.
The above equations suggest that the new Noise Rise will be 7.1 dB (a
loading factor of 80%). Thus the loading factor on the downlink can be
expected to increase from 40% to 80% if the transmit power is increased
UMTS Advanced Cell Planning and Optimisation
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from 34 dBm to 42 dBm. This represents an increase in downlink traffic
by a factor of 2.
This prediction was verified by simulating an additional load on the
downlink only equal to the original load. The simulator reported no
significant effect on the existing traffic due to the extra load.
Planning a UMTS Network
Further Work: Adding traffic onto the
downlink
• Examining the Simulation Reports
reveals that the average Node B
Tx Power is approximately 34
dBm.
• The maximum Tx power is 42
dBm.
• This extra power can be used to
send uni-directional data.
Planning a UMTS Network
Further Work: Adding traffic onto the
downlink
• Amount of extra data possible depends on the effect that increasing the
transmit power will have on Noise Rise at the mobile.
NR at 34 dBm
NR at 42 dBm
Increase in throughput
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Planning a UMTS Network
Further Work: Adding traffic onto the
downlink
• Calculations suggest that increasing Tx power to 42 dBm will move NR on the
downlink from 2.2 dB to 7.1 dB. An increase in loading factor from 40% to
80%.
• This suggests an additional load equivalent to the voice service can be added
in the downlink only with no detriment to the existing services.
• This additional load could be made up of any number of combinations of
terminals throughputs and Eb/No requirements.
• To keep things simple another 4613 terminals of 12200 bits per second in the
downlink only were added.
Result confirms expectations. Coverage probability for existing voice service
reduces from 98.7% to 98.4% with error causes divided evenly amongst Ec/Io,
Eb/No and NR. Downlink only service enjoyed 99.2% probability with error
causes divided between DL Eb/No and Ec/Io.
Planning a UMTS Network
Further Work: Mixed Services
• More than one service sharing the resource has implications for trunking
efficiency and hence dimensioning.
• Campbell’s Theorem allows us to estimate the aggregate effect of a mixture of
services.
• As an example 2000 Erlangs of voice and 1000 Erlangs of a symmetrical CS
data service with 50 kbps throughput and 2 dB Eb/No would have require the
same resource as the 4613 Erlangs of voice.
• Simulator confirms this.
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Planning a UMTS Network
Campbell’s Theorem Example(1)
• Consider 2 services sharing the same resource:
•
•
Service 1: uses 1 trunk per connection. 12 Erlangs of traffic.
Service 2, uses 3 trunks per connection. 6 Erlangs of traffic.
• In this case the mean is:
α = ∑ γ i bi ai = ∑ Erlangs × ai = 1× 12 + 3 × 6 = 30
• The variance is:
ν = ∑ γ i bi ai2 = ∑ Erlangs × ai2 = 12 × 12 + 6 × 32 = 66
Planning a UMTS Network
Campbell’s Theorem Example(2)
• Capacity Factor c is:
c=
ν 66
=
= 2.2
α 30
• Offered Traffic for filtered distribution:
Offered Traffic =
α 30
=
= 13 .63
c 2 .2
• Required Capacity for filtered distribution at 2% GoS is 21
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Planning a UMTS Network
Campbell’s Theorem Example(2)
• Required Capacity is different depending upon target service for GoS (in
service 1 Erlangs):
•
Target is Service 1 C1=(2.2 x 21) + 1 = 47
•
Target is Service 2, C2=(2.2 x 21) + 3 = 49
• Different services will require a different capacity for the same GoS. In other
words: for a given capacity, the different services will experience a slightly
different GoS.
Planning a UMTS Network
Calculating the Relative Amplitude
• What is the resource?
•
•
•
Bitrate - no…
Loading of individual user - yes…
Calculate traffic analysis using the ratio of single channel loading for different
services
• Loading is affected by bitrate and Eb/N0
Relative amplitude =
bit rate for service ×
Eb
bit rate for amplitude 1×
Eb
N0
for service
N0
for amplitude 1
3.4 Using More Appropriate Path Loss Models
The path loss model used so far is too simple to be realistic. More widely
used models reduce to similar equations if the height of the mobile is
fixed and, also, the terrain is flat. However, incorporation of the more
sophisticated models is essential if terrain height variations are to be
considered.
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A typical “Okumura-Hata” style of equation was used to predict the path
loss over a terrain that included substantial variations in height. The
variation in height caused coverage gaps to appear in the shadows of the
hills. These were filled by the provisioning of additional base stations
such that almost 95% of the areas covered to the required level of 146 dB
path loss. It was found that some of the base stations fell into the category
of “high site” and caused excessive blocking. The level of blocking could
be reduced by careful re-pointing of the antennas.
Planning a UMTS Network
Incorporating more sophisticated Path Loss
Models
• “Cost 231 - Hata”
Loss = k1 + k 2 log (d) + k3 hms + k 4 log(hms ) + k5 log(heff ) + k 6 log(heff ) log(d )
= (k1 + k3 hms + k 4 log(hms ) + k5 log(heff ) ) + (k 2 + k 6 log(heff ) )log(d )
• If hms is fixed then variations are only dependent on heff. Using
typical default parameters:
Antenna Ht
15
20
25
30
Model
140.0 + 32.3 log(d)
138.2 + 31.5 log(d)
136.9 + 30.8 log(d)
135.8 + 30.3 log(d)
Planning a UMTS Network
A More Challenging Terrain
154 km2. Heights vary from zero to 135 m a.s.l.
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Planning a UMTS Network
The Challenge
•
•
•
•
•
•
Challenge is to serve 2000 Erlangs of demand for voice service.
Even spread of traffic across the whole area.
13 E/km2
With 20 m antenna heights, initial calculation suggests 25 sites.
Max path loss should be 146 dB, range 1.8 km.
Peak Noise Rise will be 8.7 dB.
Planning a UMTS Network
Placing the Sites
• Due to irregular outline, 31 sites were required to provide
continuous coverage at a range of 1800 metres.
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Planning a UMTS Network
Coverage Analysis
• Initial site placing leads to 80% of
area being covered to required
level.
• UMTS simulation suggests
coverage probability of 87% with
failures split between uplink
Eb/No and Noise Rise.
Planning a UMTS Network
Increasing Percentage Coverage
• Adding four more sites (35 in
total) resulted in 94.3% coverage
based on pathloss and 92%
coverage probability from UMTS
simulator.
• Again failures split between
Eb/No and Noise Rise.
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Planning a UMTS Network
Analysing Reason for Eb/No Failures
Coverage
Eb/No Failures
• Eb/No failures follow high path loss areas. If the path loss is too great the
required Eb/No cannot be achieved.
Planning a UMTS Network
Analysing Reason for NR Failures
Coverage
Strongest Pilot
• Noise Rise failures concentrated on High Sites. An example is shown.
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Planning a UMTS Network
Action taken to decrease NR failures.
For the cell being
investigated:
Coverage
• Starting statistics: Throughput 382 kbps
(approx 31 connections); 20 blocked
connections due to NR.
• Action: Height reduced to 10 m; antenna
down-tilted by 3 degrees.
• Result: Throughput 294 kbps; 0.65
blocked connections due to NR; no
noticeable increase in failures on
neighbouring cells.
Planning a UMTS Network
Covering an Urban Area.
• 2000 Erlangs over 154 km2 is not a very
big density.
• New challenge is to serve 2000 Erlangs
of voice service generated by users within
an area of 2.36 km2.
• This Urban area is not flat (zero to 50 m
a.s.l.) or regularly shaped, posing
significant challenges.
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3.5 Serving Very High Traffic Densities
In practice, it is possible to encounter traffic densities far in excess of the
13 Erlangs per km2 examined in the last simulation. Accordingly, a small
(2.4 km2) urban area was investigated with a view to servicing 2000
Erlangs of voice traffic: a density of approximately 800 Erlangs per km2.
The main finding was that the “other to own” interference ratio tends to
be much higher when the cells are packed closely together. Rather than
the assumed value of 0.6, values of 1.5 were encountered. This reduces
the capacity per cell. Lowering the antenna heights and down-tilting
helped improve the situation but not to the extent where the assumed
value of 0.6 was realised. Thus it seemed impossible in the first instance
to service the level of traffic with the number of cells first calculated. The
network provided good coverage for 1600 terminals as opposed to the
required 2000 terminals. Increasing this level to 2000 would entail restarting the dimensioning exercise assuming a more realistic value for the
interference ratio (unity being a suggested value for such situations).
This is another example of a simulation tool being required to validate
spreadsheet calculations.
Planning a UMTS Network
Spreadsheet Dimensioning.
• Initial dimensioning exercise predicts that
coverage can be achieved by 22 sites
each of range 240 metres.
• Low path loss means that very high (20
dB+) Noise Rise can be tolerated.
• Cell capacity effectively become Pole
Capacity.
• Coverage prediction suggests that path
loss will not be a problem.
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Planning a UMTS Network
UMTS Simulation.
• Only 65% Coverage Probability achieved.
• All failures due to Noise Rise.
• Estimation of Pole Capacity of a cell is
erroneous.
• Cell Reports indicate very low FRE
(~40%) suggesting a value for the
interference ratio, i, of 1.5 (c.f. 0.6
assumed).
• Increasing FRE is crucial to increasing
Coverage Probability
capacity.
Planning a UMTS Network
Optimisation Procedures.
• Lowering antenna heights and making the
downtilt as high as 10 degrees improved
matters.
• Coverage probability now 86% (c.f. 65%).
• FRE still only 50%.
• Initial estimate of 32 Erlangs per cell
unachievable in first instance.
• Reduce traffic to more “realistic” levels.
Coverage Probability
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Planning a UMTS Network
Optimisation Procedures.
• Reduced traffic from 2000 to 1600
terminals.
• Coverage probability increased to 96%.
• Majority of failures due to one apparent
“high site” that could probably benefit
from further attention.
• 25 Erlangs per cell would appear to be
the limit in this situation (average load
84%).
Coverage Probability
Planning a UMTS Network
Conclusions.
• Spreadsheet dimensioning is an appropriate initial step.
• Planning Tool needed to form strategy; analyse coverage; spread traffic;
conduct detailed analysis; perform quantitative sensitivity analyses;
predict the effectiveness of optimisation techniques.
• Control of cell antenna radiation is crucial to achieving designed capacity.
In particular “high sites” can dramatically reduce the capacity of a
network.
• It becomes more difficult to achieve high Frequency Re-use Efficiency as
cells are packed closer together.
• Problems only become apparent as system becomes heavily loaded.
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3.6 Evaluating Simulator Results
When examining the prediction made by a simulator it is important to be
clear regarding exactly what you are simulating. Essentially, a Monte
Carlo style of static simulator will provide a prediction of the outcome of
attempts to establish a connection to the network. Noise Rise failures
generally indicate a failure to connect because of over demand. It is very
useful to gain an estimate of the likelihood of a call being dropped once a
connection has been established.
If the network becomes “under stress” from overloading, or capacity
being reduced due to external interference, there are various load control
measures that can be introduced. These include tolerating a lower Eb/No
value and also reducing the bit rate provided on a particular service.
Simulations of network performance with these lower quality targets
should be made and evaluated.
In these circumstances the lower values of Eb/No and bit rate should
result in Noise Rise failures being eradicated. The location of areas where
the likelihood of failure is high should then be identified. These will
generally be areas where the path loss to the best server is too high to
allow the required Ec/Io and Eb/No conditions to be met. Their
seriousness can be evaluated and remedial action taken.
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Planning a UMTS Network
Evaluating Simulation Results
• The simulator provides a
prediction of the outcome of
attempts to establish a
connection to a network.
• Of special interest is the
probability of a call being
dropped.
• Load control in times of stress will involve reducing Eb/No and reducing
bit rates. The performance of the network under such circumstances
should be evaluated.
Planning a UMTS Network
Evaluating Simulation Results
• With reduced Eb/No and bit rates
(e.g. Eb/No 2 dB below target and
voice bit rate reduced to 7.95
kbps), Noise Rise failures should
be extremely rare (ideally zero).
• Eb/No and Ec/Io failures will
probably be confined to small
“problem areas” which will usually
be related to high path loss.
Location of Failures
3.7 Pilot Pollution
The term “pilot pollution” is used in various texts to describe a number of
related yet distinct problems. Essentially, they all relate to the situation
where a similar path loss exists from a mobile to many (four or more)
cells. It is possible under such circumstances for the total received power
to be so high that Ec/Io failures are recorded due to the high level of Io.
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Planning a UMTS Network
Pilot Pollution
• If a mobile experiences comparable path loss to a number of cells,
problems can arise through no single cell dominating.
• Problems include: low Ec/Io; low capacity on downlink; frequent
updates to membership of the active set.
The value of Ec/Io at a point depends on the pilot power of the best
server, Pp, the other power transmitted by the best serving cell, T1 (that
will benefit from orthogonality α), the link loss to best serving cell, LL1,
the transmit powers of interfering cells (T1, T2, T3 etc..) and the link loss
to these interfering cells (LL2, LL3, LL4 etc.).
⎛
⎞
PP
⎟
⎜
Ec
1
LL
⎟
= 10 log⎜
(
)(
)
1
−
1
−
α
T
P
T2
T3
I0
⎜
P
+ PN +
+
+ .... ⎟⎟
⎜
⎝
⎠
LL 2 LL3
LL1
dB
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Planning a UMTS Network
Ec/Io
Pilot Power: 33 dBm
“Interference” Power: 40 dBm
Noise Floor: -99dBm
Link Loss 130 dB
• In the above situation the pilot power would be received at a level of •
97 dBm.
Total of interference plus noise would be -89.5 dBm giving a value for
Ec/Io of -7.5 dB.
Planning a UMTS Network
Ec/Io
Pilot Power: 33 dBm
“Interference” Power: 40 dBm
Link Loss 130 dB
Link Loss 131 dB
Interference Power: 42 dBm
• The power from a neighbouring site would add to the total
interference and noise power. In the above situation this total power
would become -86.2 dBm and Ec/Io would be reduced to -10.8 dB
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Planning a UMTS Network
Ec/Io
• If the mobile has a low loss path to many base stations, the value of
•
Ec/Io could become so low that the pilot cannot be detected, making
communication impossible.
-15 dB is a typical minimum usable value for Ec/Io.
More likely is the situation arising where downlink throughput is
severely limited by the interference. A quick analysis of the approximate
3840
expression for the pole capacity in the downlink direction
Eb
(1 − α + i )
N0
demonstrates that the value of parameter, i, is crucial. If the cell has a
similar path loss to many cells, then values of i as large as five can be
encountered thus reducing the capacity possible on the downlink at those
regions suffering from the interference.
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Planning a UMTS Network
Downlink Capacity
• The Pole Capacity in the Downlink Direction is approximately
kbps.
3840
Eb
N0
(1 − α + i )
Planning a UMTS Network
Downlink Capacity
• In the situation above it is possible for the value of i to be as high as
4, thus reducing the downlink capacity. Network capacity may
become downlink limited.
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Simulation Examples
Planning a UMTS Network
Simulation Examples
• A small network of 7 omni-directional sites was loaded with traffic.
For a mean of 200 voice terminals 100% success rate was achieved.
Planning a UMTS Network
Simulation Examples
Ec/Io failures
•
Removing the central site caused pilot pollution in the central area
resulting in Ec/Io failure (coverage probability now 78%).
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Planning a UMTS Network
Simulation Examples
•
Increasing the pilot power from
33 dBm to 38 dBm resulted in
Ec/Io failures being eradicated
but downlink Eb/No failures now
occur in the same region.
Downlink Eb/No failures
Planning a UMTS Network
Identifying Problem Areas.
Active Set Size: 7 cells
•
Active Set Size: 6 cells
With a SHO margin of 5 dB, the mean size of the active set was
determined for the 6-cell and 7-cell configurations.
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Planning a UMTS Network
Identifying Problem Areas.
Active Set Size: 7 cells
Active Set Size: 6 cells
•
The maximum active set size was 3 with the 7-cell configuration but as high as
6 in the 6-cell case.
•
This indicates the number of cells with a low loss path to a mobile.
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4 Site Location Issues
4.1 The Ideal Situation
The uniformly loaded network is the easiest to plan for and presents us with
something of a starting point from which we can examine issues that make planning
more difficult. Even with an evenly loaded network, an initial assessment has to
made regarding the traffic density. The coverage/capacity trade-off is well known.
The initial decision may be to provide coverage for a low capacity and then increase
capacity as demand picks up. Capacity can be increased either by building new sites,
introducing extra carriers or by utilising an appropriate capacity-enhancing device
such as diversity. The following table shows how the area of coverage of a typical cell
will reduce compared to the area when five voice connections are maintained. The
area of coverage for five connections is regarded as 100% for comparison purposes.
Number of voice connections
5
10
20
30
40
50
60
Coverage Area
100%
95%
85%
74%
61%
45%
24%
Assumptions: Uplink Pole Capacity corresponds to 65 connections. Propagation
exponent is 3.5.
Once the coverage area required and the traffic density to be serviced has been
decided, it is relatively straightforward to plan the network, the main issue being
gaining permission to place sites where you need them. It is worth pointing out,
however, that the coverage area prediction method and link budget are slightly
different from the GSM case. Consider the “classic” method of determining
maximum path loss given the existence of shadow fading. In a GSM situation we
would decide on an area coverage probability required (usually 90% - 95%) and then
add an appropriate margin, knowing the propagation exponent and the standard
deviation of shadow fading. This will then allow a target path loss to be determined
whereby the probability of the actual path loss being sufficiently low to allow a
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connection to be made is equal to the required probability. However, in UMTS
systems the phenomenon of Noise Rise will affect the link budget. It is normal to add
a Noise Rise (or “interference”) margin into the link budget. It is also usual to set this
to the limit for a particular cell. This means that the calculations made will result in a
path loss being output that will give a 90% connection (uplink Eb/No) probability
even if the cell is fully loaded. At lower loading levels the probability will be greater.
Thus, if an average probability is required, a lower value of Noise Rise should be
used. This value of Noise Rise could be equal to that produced under “average”
rather than “peak” loading conditions. The difference that this will produce will
again depend on the desired capacity of the cell. The table shows the difference
between peak and average Noise Rise and, further, provides an estimate in the
difference this would make in the estimate of coverage area.
Peak Noise Rise
2 dB
5 dB
10 dB
Average Noise Rise
1.3 dB
3.4 dB
5.8 dB
% coverage area difference
9%
19%
43%
Assumptions: NR caused by voice traffic on cell with pole capacity of 65 connections.
Cell provisioned for average traffic on a 2% blocking probability. Propagation
exponent assumed to be 3.5.
Site Location Issues
The Uniform Network
• An ideal situation.
• Issues
• Capacity/Coverage
Trade-off
• Ability to place sites
where they are
required.
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Site Location Issues
Capacity/Coverage Trade-Off
≈
• Uplink Pole Capacity in kbps
3840
⎛ Eb ⎞(1 + i ) )
⎜ N ⎟
0⎠
⎝
• Typical values give a pole capacity
(voice 12200 bps, Eb/No 4.8 dB, i= 0.6)
as approximately 65 voice connections
(100% activity).
Number of
Connections
• Taking the coverage possible for 5 voice
connections as a reference it is possible
to compare coverage for other
capacities.
5
100%
20
• Try the calculator, record area for 5
users, then increase users and note area
reduction.
85%
50
45%
Site Location Issues
Dimensioning Procedures for UMTS
P(connect)
50%
75%
• General Rule is to add in a slow
fading margin.
• In UMTS a NR margin must
also be included.
0
P(connect)
x0 - α
76%
90%
Point Location Probability
– the probability of being
able to connect at this
point
Area Location Probability
– the probability of
connecting in the area of
interest
5.6
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x0 - α
• Result will be that coverage
probability is achieved at NR
limit.
• At lower values of NR,
coverage is better than
calculated.
• Perhaps coverage probability
should be calculated at average
cell loading levels.
57
Site Location Issues
Dimensioning Procedures for UMTS
• Ratio of Peak to Average Noise Rise is not constant.
• If voice traffic (pole capacity 65 connections as before)
is considered with an Erlang B distribution, differences
in coverage area predictions can be calculated for
different values of NR limit.
Peak Noise
Rise
Resulting
Area
Average
Noise Rise
using
Erlang B
Resulting
Area
Area
Increase
2 dB
37.47
1.3 dB
40.99
9%
5 dB
25.24
3.4 dB
31.37
24%
10 dB
13.07
5.8 dB
22.72
74%
Breathing
4.1.1 Mis-placed sites.
An evenly loaded network is fairly straightforward to provision with evenly spaced
sites. A problem arises if you are not able to place the sites where you would like
them to be. In this situation a particular cell may have a coverage area larger than the
average. Consider the example where a cell must increase its range from 1300 metres
to 2000 metres (a 50% increase). This increase would raise the path loss at the cell
edge by approximately 6 dB. This would reduce the probability of connection at the
cell edge from an initial value of, typically, 75% to less than 50% when the noise rise
experienced on the cell is close to the limit. Action that can be taken would be to
reduce the Noise Rise limit. Perversely, this reduces the capacity of the cell when its
coverage area has been increased but it would increase the probability of connection
at the cell edge. Additionally, it would be possible to offer reduced bitrate services at
the cell edge. With voice services, that would lead to an increase in the maximum
path loss tolerated of up to 4 dB.
Another possibility to consider is the use of an active repeater station.
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Site Location Issues
Mis-placed Sites
• If sites cannot be placed
exactly as required, the
coverage area of some sites
will increase.
•Location Probability ~75%
• 50% range increase leads to
path loss increase of ~ 6 dB.
• ( 35 * log ( 1.5 ) = 6.2 dB )
•Location Probability ~ 50%
• Location probability will
reduce, possibly to less than
50%.
Site Location Issues
Mis-placed Sites: possible action
• Coverage helped by reducing NR limit.
• This will reduce capacity of the cell.
• Reduction of bit rate of services offered
• 12200 bps reduced to 4750 bps gives a 4 dB benefit.
• Deploy a repeater station.
• Repeaters can improve coverage to remote parts of the cell.
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4.2 Hot Spots
The fact that a single frequency is used to provide continuous coverage in
a UMTS system means that cells act together much more intimately than
in a GSM system for example. One object of system optimisation can be
thought of as the minimisation of transmit powers. That will lead in turn
to a minimisation of interference and therefore a maximisation of
capacity. If hotspots exist, the impact on the network is very dependent
on their location within the network.
As an example let us suppose that a hotspot exists that demands services
on the uplink that will generate a 3 dB noise rise on that uplink. If the
background noise level is -102 dBm, the power from the users will also
equal -102 dBm. However, the transmit power of the users, and hence the
amount of inter-cell interference generated will be dependent on the
location within the cell. We will consider a simplified situation where the
hotspot is only 100 metres from the serving cell and 2000 metres from the
nearest neighbour. The difference in path loss has been measured to be 45
dB. That means the neighbouring cell will experience an interference
level of -147 dBm. This would cause a noise rise of only 0.0001 dB
(equivalent to a loading factor of 0.003% - negligible). However, if the
hotspot was in a location where the path loss to the neighbouring cell was
only 4 dB more than that to the serving cell, the power level at the
neighbouring cell would be -106 dBm and the noise rise generated would
be 1.5 dB which is equivalent to a loading factor of approximately 30% definitely not negligible.
Enhancement techniques such as uplink diversity and mast head
amplifiers will be examined in detail later in this course. Suffice to say at
the moment that they improve coverage and will allow the noise rise limit
to be increased whilst maintaining the cell range. It is understandable
tempting to employ such techniques on a cell that has a hotspot.
However, this can lead to worse consequences for neighbouring cells.
Suppose the hotspot was such that it generated a noise rise of 8 dB at the
serving cell and path loss to the “victim” neighbour was only 4 dB greater
than that to the serving cell. The signal level received at the neighbouring
cell would be -98 dBm, generating a noise rise of 5.5 dB. This may well be
above the noise rise limit of this cell. That means that adjacent cell
interference alone has effectively fully loaded the neighbouring cell
making it incapable of accepting any more traffic.
As a final note, it is worth remembering that, in sectored sites, the cell
edges do not necessarily occur at large distances from the cell.
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The location of hot spots within cells and in relation to other cells requires
understanding. Techniques for handling these hot spots therefore varies
depending upon the location of own cell base station and neighbouring
base station location.
Accommodating Hotspots
Traffic Hotspots
• In a UMTS network the
affect of a hotspot
depends on its location in
relation to the network
cells.
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Accommodating Hotspots
Traffic Hotspots: an analysis
• In a UMTS network the
affect of a hotspot
depends on its location in
relation to the network
cells.
• Thermal Noise Power = -102 dBm
• Power from Hotspots = -102 dBm
• NR = 3 dB
• Noise Power= -102
dBm
• Power from
Hotspots = -147 dBm
• Negligible
interference
•PL=100 dB
•PL=145 dB
Accommodating Hotspots
Traffic Hotspots: an analysis
• Thermal Noise Power = -102 dBm
• Power from Hotspots = -102 dBm
• NR = 3 dB
• In a UMTS network the
affect of a hotspot
depends on its location in
relation to the network
cells.
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• Noise Power= -102 dBm
• Power from Hotspots =
-106 dBm
• NR = 1.5 dB (loading
factor of 30%)
•PL=121 dB
•PL=125 dB
62
Accommodating Hotspots
Traffic Hotspots: an analysis
• Suppose the serving
cell employs, for
example, uplink
diversity and then
allows the NR to
reach 8.6 dB.
• Thermal Noise Power = -102 dBm
• Power from Hotspots = -94 dBm
• NR = 8.6 dB
• Noise Power= -102 dBm
• Power from Hotspots =
-98 dBm
• NR = 5.5 dB
(loading factor of 72%)
•PL=121 dB
•PL=125 dB
• Interference is now
very damaging.
Accommodating Hotspots
Traffic Hotspots: sectored sites
• A hotspot located near to the
edge of a cell has a more
serious effect than one with a
very dominant serving cell.
• In sectored sites, note that cell
edges can be located near to
the site.
• Soft or softer handover will
improve the situation.
• A “badly”
located
hotspot
• A “nicely”
located
hotspot
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4.3 Site Density
Many ballpark figures are quoted regarding the capacity of a UMTS cell.
This has affected the configuration offered by vendors when supplying
Node Bs. Perhaps a cell is configured such that its hardware will
accommodate 32 simultaneous voice connections. If this is accepted for
the moment, the factor that limits the user density that can be served then
becomes cell density. The problem is that, as we increase the site density
of a site, cell interference increases. If the pole capacity of a cell is
considered as equal to that given by the expression 3840
(Eb
N 0 )(1 + i )
kbps, the parameter i tends to increase with site density. This is due to
two main reasons:
Employing “normal” levels of down-tilt leads to the main beam
penetrating neighbouring cells.
The dual-slope nature of the “signal strength vs. distance”
characteristic makes the propagation exponent lower the shorter the
distance.
Antenna downtilt. Suppose that the general rule was to down-tile
antennas by 2 degrees. That will lead to the main lobe of the antenna
being directed towards the ground at a distance approximately equal to
30 times the antenna height. The strength of the signal in the horizontal
direction will be a few dB less than the main lobe (the exact value will
depend on the vertical beamwidth of the antenna). This helps to reduce
interference between cells. If the cells are packed more closely together,
the main lobe of the antenna will penetrate adjacent cells.
Dual slope propagation Characteristic. It has been found that for a
particular environment and site configuration the path loss can be
approximated by the expression k1 + k 2 log d where d is the distance in
kilometres and k1 and k2 are constants for a particular environment and
configuration. The parameter k2 is related to the propagation exponent
and is crucial in determining the level of inter-cell interference. The lower
the value of k2 the worse the inter-cell interference. In a GSM network
that delivers a typical C/I value of 10 dB when the value of k2 is 35 (an
exponent of 3.5), the value of C/I will reduce to approximately 7 dB if the
value of k2 reduces to 25 (an exponent of 2.5). In a UMTS network, the
value of the relative interference parameter I, will increase if the exponent
reduces. A typical value for I in an evenly loaded network is 0.6 for an
exponent of 3.5. For an exponent of 2.5, it can exceed 1.
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The fact is that signal strength is more accurately modelled by a dualslope graph where k1 and k2 have two different values: “near” and “far”.
The value of k2NEAR will be less than that of k2FAR. The point of transition
between the two values is referred to as the knee of the graph. The
distance at which the knee occurs depends upon the height of the cell
antenna (it increases with antenna height). Typically, the knee could be
expected to occur at about 500 metres for an antenna height of 15 metres
and 1100 metres for an antenna height of 30 metres. This means that the
more densely you attempt to pack the sites, the lower the exponent and
the worse the inter-cell interference.
Action that needs to be taken to minimise the adjacent cell interference
includes reducing the cell height (to make the distance to the knee
smaller) and to down-tilt cell antennas, quite severely.
When sites are densely packed, coverage becomes a secondary issue
because of the small cell boundaries. The capacity of the cell effectively
equals its pole capacity. Crucial in this pole capacity is the value of intercell interference. If the cell range is 100 metres and the cell antenna height
is 15 metres, a down-tilt of 8.5 degrees will point the main lobe at the edge
of the cell. Additional down-tilt will reduce the signal strength at the cell
edge but will have the advantage that it will also reduce the amount of
interference gathered from adjacent cells. Down-tilts of greater than 10
degrees can be expected in such circumstances.
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Increasing Site Density
Increasing Site Density: Problems
• What is the capacity of a UMTS
Cell?
• “Ballpark” figures suggest that
approximately 32 simultaneous
voice connections can be
accommodated. ( 100% voice
activity )
• This has influenced the
hardware configuration of cells.
• But, how densely can sites be
packed?
32
32
32
32
32
32
32
32
32
32
32
32
32
32
32
32
Increasing Site Density
Increasing Site Density: Problems
• As sites become more
densely packed, inter-cell
interference increases.
32
32
•i ~ 0.6
32
• Frequency reuse efficiency,
FRE, decreases
• Two main reasons:
• Using “normal” levels of
down-tilt leads to the main
beam penetrating
neigbouring cells
• The dual-slope nature of
path loss against distance.
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32
32
32
32
32
32
32
•i ~ 1.0
32
66
Increasing Site Density
Antenna Down-tilt
Large cells: low level of inter-cell interference
• For a given level of
down-tilt, the level of
inter-cell interference
will increase when the
cell size reduces.
Small cells: high level of inter-cell interference
Increasing Site Density
Dual-Slope Characteristic
Loss (dB)
Far slope
Break point
Near slope
distance
• Propagation exponents quoted usually refer to the “far” slope.
• The exponent near to the base station is usually considerably
less (2.0 being a typical value).
• Remember that up until now we have had 3.5
• Pathloss = 137 + 35 x log (R)
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Increasing Site Density
Dual-Slope Characteristic
• The lower the value of the
exponent, the greater the
penetration from one cell
into the next.
Exponent i
• Generally, the lower the
exponent, the greater the
value of i.
2
1.5
2.5
1.1
3
0.75
3.5
0.53
4
0.38
• For an evenly loaded
network:
i ≈ 6× 2
-exponent
Increasing Site Density
Dual-Slope Characteristic
• The position of the break
point is influenced by the
height of the base station.
BS height (m)
• The higher the base station,
the greater the distance.
30
20
• At 2 GHz, the distance to
the breakpoint is
approximately
10
Distance to
Break point (m)
300
600
900
30 × hBTS
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Increasing Site Density
Dual-Slope Characteristic
• Increasing the exponent reduces interference and
increases network capacity.
• Reducing antenna height will lead to an increase in
the exponent. “Far value” of exponent typically (urban
environment)
4.5 − 0.66 × log10 (hBTS )
• Also reducing antenna height brings the “break point”
closer to the BTS. (break point ~ 30 x hBTS )
• Down-tilting antennas will also reduce mutual
interference.
Increasing Site Density
Implications for Increasing Site Density
• As site density increases, interference will increase.
• Reducing Base Station height and down-tilting antennas
will help to reduce this.
• For very small cell ranges, the amount of down-tilting will
be severe.
•At a range of 100 metres, a 15 metre mast
will have to be down-tilted by 8.5 degrees to
point at the cell edge.
• tan-1(15/100) = 8.5o
•Additional down-tilting will reduce field
strength at the cell edge but also reduce
mutual interference.
•Vertical beamwidth of antenna is significant.
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Increasing Site Density
Vertical Antenna Beamwidth
• Sectored antennas with a typical horizontal beamwidth of
85 degrees can have a variety of vertical beamwidths.
• A high gain (e.g. 18 dBi) antenna will have a vertical
beamwidth of only about 3 degrees.
• A lower gain (e.g. 13 dBi) antenna will have a vertical
beamwidth of about 12 degrees.
• Lower gain antennas are likely to cause fewer problems
when severely down-tilted.
18 dBi antenna
13 dBi antenna
4.4 High Sites
A high site is a site that has a lower path loss at a particular distance than
is “normal” for cells in the network. If GSM legacy is used for
establishing a UMTS network any GSM umbrella site is likely to act as a
high site in a UMTS network. Remember that it is not possible to
frequency plan your way out of trouble in a UMTS network. You cannot
isolate a rogue site by allocating a separate carrier to it. The fact that the
path loss is lower to a high site means that it will tend to dominate a
network unless action is taken. When a mobile selects a cell it measures
the pilot channel power. The high site will have a larger area of coverage
than its neighbours if they are all transmitting the same pilot channel
power. That will lead to the cell becoming overloaded very quickly with
its Noise Rise limit being reached. Further, the neighbouring cells will be
affected by downlink interference generated by the high site.
Many of the problems associated with a high site can be reduced by
careful parameter planning. Sometimes, however, the results can be a
little strange. It is tempting to reduce the pilot power of the high site in
order to reduce its traffic. However, this would lead to mobiles
increasing their transmit power as they connect to cells with a higher path
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loss. In this way, the high site in particular would experience a higher
noise rise than if it actually served the traffic. One aspect that must be
considered is, because the path loss is low, the noise rise limit can be
raised whilst still maintaining coverage. If this is done, the pilot power
can be reduced without severe consequence. The same argument can be
used to allow the reduction in downlink power (total cell power and
control channel power). This will reduce the downlink interference
experienced by neighbouring cells.
The presence of the high site remains undesirable however. It will be
operating very near its pole capacity with the value of inter-cell
interference reducing this pole capacity to modest levels. Additionally,
because of its high position, the propagation exponent is likely to be low
with the result that mutual interference is further enhanced. It is clear
that controlling the radiation from the cells is crucial in getting the
maximum performance from a network. The performance of a network
containing a high site may be improved by careful down-tilting of the
antennas.
Summarising, the following parameters on a high site can be modified to
improve the network performance
Noise Rise Limit
Cell Power
Pilot Channel Power
Common Channel Power
Increase
Decrease
Decrease
Decrease
Antennas
Consider Down-tilting
The amount of increase or decrease that should be made is approximately
equal to the amount by which the path loss at a particular distance is
lower than “normal”. However, this is not a constant and some
experimentation will be necessary in order to determine the optimum
solution.
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High Sites
High Sites
• The higher the site:
• The lower the loss to a particular point (offset ~ 14 log10[hBTS])
•Remember that it is the “effective height” of the BTS that is
considered.
• The lower the propagation exponent (offset ~ 0.66 log10[hBTS])
• Result:
• High Sites suffer interference on the uplink and generate
interference on the downlink.
High Sites
High Sites
• An umbrella site from a legacy GSM network will generally act as a
high site.
• You cannot frequency plan your way out of trouble in a UMTS
network.
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High Sites
High Sites
• Lower path loss can be rectified by either
• Inserting extra loss
• Parameter planning: pilot power, noise rise limit, downlink Tx
power.
• The lower exponent causes greater problems; careful control
of radiation (e.g. by down-tilting) can help with mutual
interference.
• An “untreated” high site will cause severe problems with
localised capacity reductions of 50% to be expected.
• Note that high sites cause capacity rather than coverage
problems.
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5 Factors Limiting Capacity
5.1 Cell Throughput
Capacity Limiting Factors
Factors Limiting Capacity
•
Cell Throughput is given by the simplified expressions for pole
capacity in kbps multiplied by the loading factor η
3840
Eb
N0
(1 + i )
3840
Eb
•
N0
•Uplink
×η
(1 − α + i )
×η
•Downlink
Crucial parameters are Eb/No, inter-cell interference i, α
orthogonality and η loading factor (which is affected by the
Noise Rise limit).
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5.2 The Effect of Mobility on Capacity
Achieving a high capacity from a UMTS cell is dependent upon being able to deliver
acceptable levels of BER whilst operating at low Eb/N0 values. The use of a fast,
closed-loop power control technique allows the average value of Eb/N0 to be very
near to the minimum acceptable. Typically, the power transmitted in each direction
(although it is uplink capacity that is most affected by this technique) can be adjusted
by 1 dB every 0.67 ms (1500 Hz). Thus fades of up to 1500 dB/s can be compensated
for. The intention is that this will allow the receiver to experience a constant signal
level even when the channel is experiencing “fast fading”: that is, the mobile is
moving through a multipath interference pattern with a spatial period of the order of
a wavelength (15 cm).
Capacity Limiting Factors
Factors Limiting Capacity: Eb/N0
•
High capacity levels depend on low levels of Eb/No being
used. ( Note BER must be acceptable ).
•
Achieving this relies on accurate, fast power control to
compensate for fast fading.
•
Fast fading occurs as a mobile moves through an
interference pattern.
•
Interference patterns develop due to reflections.
•
Repetition distance depends on angle between incident
and reflected waves.
λ
2
× cos(θ )
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θ
75
Capacity Limiting Factors
Factors Limiting Capacity: Eb/N0
⎛ E1 + E 2 ⎞
20 log⎜
⎟
⎝ E1 − E 2 ⎠
E1
λ
2
× cos(θ )
•
This is difficult to estimate, for a 6 dB
reflection loss the notch depth will be
approximately 10 dB.
•
Fast power control is intended to
compensate for the fastest fading incidents
at the steepest slope.
E2
⎛ 1 + 10− dBdiff / 20 ⎞
⎟
Notchdb = 20 × log⎜⎜
− dBdiff / 20 ⎟
−
1
10
⎝
⎠
Naturally, if the gradient of the notch in the direction of travel is very
steep and the mobile is very fast moving, power changes at the rate of
1500 dB/s may not be sufficient to compensate for fluctuations in the
channel. For example, it is possible for the standing wave pattern to have
a gradient in excess of 100 dB/m. In such circumstances, the speeds
greater than 15 m/s, 55 km/h, will cause problems.
These problems manifest themselves in the form of fluctuations in the
received signal power. The result is that a margin has to be built in to
ensure an acceptable value of BER is maintained. This leads to an
increase in the value of the target Eb/N0 and hence to a reduction in
capacity. The increases required can be substantial, with 6 dB being
thought to be typical for a mobile moving at 120 km/h. In terms of the
impact on network resources. A 6 dB increase in the average level of
Eb/N0 will lead to the capacity requirements of a connection rising by a
factor of 4. Thus, the network capacity would reduce to only a quarter of
the original value if all the mobiles start moving at a high speed through a
strong interference pattern.
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Capacity Limiting Factors
Factors Limiting Capacity: Eb/N0
•
If the mobile cannot respond to power control commands,
the UE will notice a variation in the received signal.
•
This will lead to BER variations that will cause the network
to require a higher target Eb/No (a “fast fading margin” or
“power control margin” will be required).
•
The effect can be to increase the target Eb/No from a
normal value of perhaps 4 dB to 10 dB or more for fast
moving mobiles.
•
This will reduce the capacity of a cell from typically 32
simultaneous connections to only 8 – a dramatic reduction.
•
Lesson: the multipath environment and user mobility can
affect the target Eb/No and hence cell capacity.
Capacity Limiting Factors
Factors Limiting Capacity: FRE
•
Frequency re-use efficiency is the name given to the
proportion of received power that comes from a cell’s own
users rather than from all users including other cells.
FRE =
i=
1
intra cell
1
=
=
inter cell
1+ i
intra cell + inter cell
1+
intra cell
1
−1
FRE
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5.3 Maximising Frequency Re-use Efficiency
Frequency Re-use Efficiency is a key indicator of how well the available
spectrum is being used. It shows the percentage of power that is received
at the cell (excluding thermal noise) that comes from users of that cell.
Any cell has a limit to the amount of Noise Rise that will be tolerated
before new admission attempts are refused. Out of cell power will cause
noise rise just as much as in-cell power. Interference from outside the cell
will therefore reduce the capacity of that cell. In fact the Frequency Reuse Efficiency factor (FRE) indicates the fraction of cell resource that is
available for users of that cell. For an evenly loaded network, a value of
65% is thought to be typical.
In a UMTS network, the problem is made worse by the fact that mobiles
near the edge of a cell will be both transmitting at near maximum power
and also in a location where the path loss to the adjacent cell is a
minimum.
Unevenly loaded networks yield surprisingly low values of FRE. If areas
of high traffic density are near the edge of a cell, they will produce high
levels of interference leading to a reduction in the capacity of
neighbouring cells. Similarly, a cell providing coverage over a large
geographic area that is surrounded by smaller cells serving areas of high
user density will experience high levels of interference with the result that
its capacity is adversely affected.
The most effective methods of increasing FRE are: down-tilting cell
antennas where appropriate and planning the location of Node Bs to try
and ensure that they are placed as close as possible to any predicted
traffic hotspots.
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Capacity Limiting Factors
Factors Limiting Capacity: FRE
•
The ideal situation is where the receiving antenna can only
“see” its own users but not those of other cells. ie FRE = 1
•
The power from neighbouring mobiles close to the cell
border cause the biggest problems.
High power mobiles close to
Cell border cause FRE reduction
Capacity Limiting Factors
Factors Limiting Capacity: FRE
•
A large cell serving a low subscriber density surrounded by
several smaller cells serving high subscriber densities will
experience a low value of FRE.
A Large cell will experience low FRE
Because it is surrounded by
many users of other cells
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Capacity Limiting Factors
Factors Limiting Capacity: FRE
•
Hotspots near the cell border will cause more problems that
evenly distributed neighbouring cells
Hot spots near cell border cause
FRE reduction
•
A quantitative analysis is not always possible. A simulator
is extremely valuable in helping to develop a feel for the
seriousness of potential problems.
Capacity Limiting Factors
Factors Limiting Capacity: FRE
• Increasing FRE: the main weapon is to down-tilt
antennas.
• This is most effective when there is a large angle
between the line from the antenna to the cell edge
and the horizontal.
• In the case of large cells, planning to avoid hotspots
near the cell border will reduce the incidence of low
FRE.
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5.4 Downlink Capacity and Orthogonality
The parameter known as “orthogonality” describes the amount of
mutual interference that will be experienced between users of the same
cell.
The fact that downlink transmissions within a cell are
synchronised means that the OVSF codes used provide interference
rejection that is not possible on the uplink. In fact, an isolated cell with
perfect orthogonality will have an infinite pole capacity (although the
need for multiple scrambling codes would compromise this). The
amount of interference rejection decreases in multipath environments.
We shall now analyse two situations in which only orthogonality is
changed. The effect on downlink power requirements and downlink
capacity will be examined.
Capacity Limiting Factors
Factors Limiting Capacity: Orthogonality
• Dramatic effect on downlink capacity.
Pole Capacity =
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3840
Eb
N0
(1 − α + i )
81
Capacity Limiting Factors
Factors Limiting Capacity: Orthogonality
• Example: Eb/No = 4 dB, i = 0.6, 12200bps
Orthogonality
0
0.2
0.4
0.6
0.8
1.0
Pole Capacity
963
1100
1284
1541
1926
2568
Pole Capacity
(kbps)
2000
1000
Orthogonality
0
0.5
1
Capacity Limiting Factors
Factors Limiting Capacity: Orthogonality
•
The Loading factor deliverable on the downlink depends upon
the link loss, maximum transmit power and noise performance
of the mobile.
•
Example: Tx Power 43 dBm; Noise Floor of Mobile -100 dBm.
{
}
Mobile Rx Power = 10 log 10(43− LL ) 10 + 10−100 / 10 dBm
⎧10(43− LL −orth ) 10 + 10 −100 / 10 ⎫
(143− LL −orth ) 10
NR = 10 log ⎨
+1
⎬ = 10 log 10
−100 / 10
10
⎩
⎭
1
η = 1 − (143− LL −orth ) 10
10
+1
orth = −10 log(1 − α )
{
•
Deliverable loading factor can be expected to exceed 75%.
•
Pole capacity is crucial.
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}
82
Capacity Limiting Factors
Factors Limiting Capacity: Orthogonality
•
Question:
•
Suppose a group of users of a 64kbps service in an isolated
cell experiencing a link loss of 138.4 dB are demanding a total
data throughput of 1.024 Mbps at an Eb/No of 4 dB.
•
What is the downlink loading factor at this throughput if the
orthogonality is i) 0.4 and ii) 0.8?
•
Further, what is the traffic channel power demanded and what
is the maximum throughput possible at that path loss if the
maximum traffic channel power is 42.7 dBm?
•
Assume a noise level at the mobile of -102 dBm before noise
rise.
Capacity Limiting Factors
Factors Limiting Capacity: Orthogonality
•
Answer:
•
At an orthogonality of 0.4, the pole capacity is 2568 kbps.
•
1024 kbps represents a loading factor of 39%.
•
Hence the Noise Rise would be approximately 2.1 dB.
•
The effective received traffic power would be -104.06 dBm
•
Actual received traffic power is 2.2 dB higher (-101.86 dBm)
indicating a transmit power of 36.5 dBm (link loss 138.4 dB).
•
42.7 dBm would be able to deliver almost 72% loading factor
and hence the throughput possible should be approximately
1846 kbps.
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Capacity Limiting Factors
Factors Limiting Capacity: Orthogonality
•
Answer (continued):
•
At an orthogonality of 0.8, the pole capacity is 7964 kbps.
•
1024 kbps represents a loading factor of 13%.
•
Hence the Noise Rise would be approximately 0.6 dB.
•
The effective received traffic power would be -112.2 dBm
•
Actual received traffic power is 7.0 dB higher (-105.2 dBm)
indicating a transmit power of 33.2 dBm (link loss 138.4 dB).
•
42.7 dBm would be able to deliver almost 35% loading factor
and hence the throughput possible should be approximately
2783 kbps.
Capacity Limiting Factors
Factors Limiting Capacity: Orthogonality
•
Orthogonality degradation is caused by a multipath radio
propagation environment.
•
Typically, it is of the order of 0.6 in an urban environment, higher
in rural environments.
•
In an isolated cell, an indication of the orthogonality can be
obtained by measuring the pilot SIR when the transmit powers of
all channels are known.
•
At low values of path loss, all interference power will be due to
interference from other channels.
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5.4.1 Pilot SIR as an indicator of downlink capacity
The power of the pilot channel does not vary with time. The value of the
ratio “Pilot to Noise plus Interference” (Pilot SIR) indicates the quality of
the downlink channel at a particular location. For example, if the pilot
SIR is – 6 dB then the SIR experienced by a traffic channel of the same
power as the pilot would also be -6 dB. If the required Eb/N0 for the
bearer carried on the traffic channel was, say, +4dB then a processing gain
of 10 dB would be needed. This limits the throughput to 384 kbps. The
value of the pilot SIR indicates the capacity of the downlink per unit
power (bits per second per milliwatt). The pilot SIR will vary with
location and with orthogonality and the amount of loading on the
network.
Capacity Limiting Factors
Factors Limiting Capacity: Pilot SIR
•
Although a minimum value of pilot SIR is a pre-requisite for any
communication between the UE and the Node B, its level will
indicate the quality of the user environment at any location.
•
The SIR of the pilot channel indicates the SIR (Ec/Io) of any
channel with the same transmit power.
•
If the target Eb/No of such a channel was known then the
required processing gain, and hence user bitrate, could be
determined.
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Capacity Limiting Factors
Factors Limiting Capacity: Pilot SIR
•
Example, at a particular location the pilot SIR is found to be -12 dB.
A service with a target Eb/No of 4 dB is to be delivered to a user at
this area. If the same power as the pilot is available for the traffic
channel then the processing gain necessary would be 16 dB. This
limits the throughput to 96 kbps.
•
R = W ×10 − PG /10
If the maximum channel power was 3 dB greater than the pilot
power then this throughput would increase to 192 kbps.
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5.5 The Noise Rise Limit
The Noise Rise Limit is part of the admission control strategy of the
network. It is imposed at the cell in order to maintain coverage and, as
such, features in the link budget at the cell planning stage. It has been
noted that, as a cell is only rarely at the noise rise limit, using the full
value of this limit can result in the over-dimensioning of a network given
a specified area coverage probability. Initial dimensioning can be
performed with link budgets calculated by reducing the actual NR limit
by 1 – 2 dB.
In general, the smaller the cell the higher the NR limit can be. In an
unevenly loaded network, this means that NR limits will vary from cell to
cell. Further, average values of NR will also vary. It should be
remembered that mobiles will attempt to connect with the cell for which
the pilot strength is the strongest. In order to optimise network
performance, the mobile should connect to the cell that will allow it to
transmit at the minimum power. The example given here shows the ideal
value of pilot power is greater for those cells with a lower NR limit. This
is an example of parameter planning within a UMTS network.
Capacity Limiting Factors
Factors Limiting Capacity: NR limit
•
NR limit appears in link budget and hence affects coverage prediction.
•
If a network is planned so that continuous coverage would be provided
with all cells simultaneously at NR limit, then probability suggests that
coverage is over-dimensioned.
•
Coverage can be planned for a NR value 1 – 2 dB below the limit.
•
Failures will then be split between Eb/No and NR.
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Capacity Limiting Factors
Factors Limiting Capacity: NR limit
Low NR
limit
High
NR limit
•
A small cell can have a higher
NR limit – lower path loss.
•
Cell selection determined by
Pilot power.
•
Boundary should be so that
mobile transmits with minimum
power.
Mobile at boundary
should require approx
equal Tx power to either
cell
Capacity Limiting Factors
Factors Limiting Capacity: NR limit
Low NR
limit
High
NR limit
•
Conditions on each cell vary.
•
E.g. if NR limit is 2 dB on large
cell, the average level of noise
rise could be 1.3 dB. NR limit
of smaller cell of 10 dB
suggests an average of 5.8 dB
•
Mobile at boundary
should require approx
equal Tx power to either
cell
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•
( Erlang B calculator).
Pilot powers should be set so
that large cell pilot power is 4.5
dB greater than that of the
smaller cell (all other things
being equal).
88
6 Antenna Selection
6.1 Antenna Gain & Coverage
It is common to sectorise the coverage at a site by means of employing
several directional antennas rather than a single, omni-directional
antenna. Directional antennas have a higher gain than an omni.
Sectorising also has the effect of introducing more cells per site and thus
makes the deployment of a cell more economic. The coverage range is
seen to increase by typically 50% for a 3-sector site and 80% for a 6-sector
site. However, that assumes that the noise rise limit is not adjusted. The
noise rise limit is crucial in implementing the “capacity/coverage tradeoff” in UMTS networks. It may be that, rather than increase the coverage,
site capacity should be increased by raising the noise rise limit. The
amount that this will increase the capacity depends on the setting of the
NR limit prior to it being increased as the relationship between
throughput and noise rise is non-linear.
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Antennas and Sectorisation
Antenna Gain and Coverage
Omni: typical gain 12 dBi
Three-sector antenna:
exponent Omni
6
sector
3
sector
3.0
100%
200%
158%
3.5
100%
180%
148%
4.0
100%
168%
141%
Typical gain 18 dBi
Relative range of different antennas
Six-sector antenna:
( g 2− g1)
R2
= 10 exponent×10
R1
Typical gain 21 dBi
Antennas and Sectorisation
Sectorisation and FRE
•
Sectorising sites results in greater cell overlap at low path loss
levels and hence reduces FRE (bad).
•
However for similar ranges, NR limit can be raised and cell
capacity can rise.
•
Depends on initial conditions. eg Eb/No 5.2dB, 12.2kbps
No of
sectors
FRE
i
Pole
Capacity
NR
limit
Throughput/
cell
NR limit
Throughput/
cell
Throughput/
site
1
65%
0.54
761 kbps
3 dB
378 kbps
10 dB
683 kbps
683 kbps
3
61%
0.64
715 kbps
9 dB
622 kbps
16 dB
695 kbps
2085 kbps
6
55%
0.82
644 kbps
12 dB
598 kbps
19 dB
634 kbps
3804 kbps
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6.2 Repeaters
The use of repeaters is a long-established method of extending the cell
coverage area. They are extensively used in GSM networks to fill gaps
in coverage. In a UMTS network they should be used with care.
Although they can increase coverage, and even lead to an improvement
in the frequency re-use efficiency, they can adversely affect the cell
capacity. This is because the presence of the repeater will inevitably
add noise to the channel. The result of this will be that the target
Eb/N0 will rise. An increase of Eb/N0 will lead to a reduction in
capacity.
Antennas and Sectorisation
Repeaters
•
Repeaters extend coverage. Gain provided in three ways:
•
Repeater antenna is Yagi directed at the cell (gain ~ 18 dBi)
•
Repeater antenna is elevated w.r.t. mobile antenna (gain estimated at 10 dB)
•
Repeater has an amplifier of gain ~ 70 dB
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Antennas and Sectorisation
Repeaters
•
Total gains typically 100 dB.
•
If path loss to a point is 10 dB more than maximum tolerated,
mobiles whose link loss to the repeater is less than 90 dB can
be served.
Antennas and Sectorisation
Repeaters and Noise
•
The repeater is an analogue device.
•
It will add to the noise in the system.
•
As the signal received at the cell is already “noisy” a higher target
Eb/No will be necessary.
•
This will reduce cell capacity.
•
Typical increase in required Eb/No is 1 dB but, if the cell employs
Rx diversity and the repeater does not, this figure can rise
dramatically (to perhaps 5 dB).
•
Effect on cell capacity depends on the number of mobiles utilising
the repeater.
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Antennas and Sectorisation
Repeaters and Noise
•
Repeaters are expected to be deployed in order to improve
coverage in rural areas
cell
•
Also, for providing coverage in locations such as within tunnels.
6.3 Roll-out Optimised Configuration (ROC)
The ROC configuration has been put forward by vendors as a low-cost
method of providing coverage whilst minimising infrastructure costs. It
is based on the assumption that uplink coverage is prioritised initially
over downlink capacity. The technique involves creating three-sectored
sites and then sharing the power of one power amplifier between the
three cells on the downlink. On the uplink, each cell has a separate
receiver thus providing the same capacity and coverage that would be
expected from a Node B with standard configuration.
The reduction in power available to each cell on the downlink leads to the
network capacity being approximately equal in the uplink and downlink
directions.
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Antennas and Sectorisation
Roll-out Optimised Configuration (ROC)
• Coverage, rather than capacity, will be the initial priority.
• Coverage is expected to be uplink limited.
• ROC provides a minimum configuration that can be
upgraded in a straightforward manner.
Antennas and Sectorisation
Roll-out Optimised Configuration (ROC)
•
ROC is based on a 3
sectored site.
•
3 TRXs are used in the
receive direction only with
only one TRX (and hence
only one PA) being used
on the downlink.
To Rx of TRX1
2
To Rx of TRX1
2
To Rx of TRX3
To Rx of TRX3
TRX1 PA
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Antennas and Sectorisation
Roll-out Optimised Configuration (ROC)
•
Uplink is the same as
normal 3-sectored site.
•
DL coverage is reduced.
To Rx of TRX1
2
To Rx of TRX1
2
To Rx of TRX3
To Rx of TRX3
TRX1 PA
Antennas and Sectorisation
Roll-out Optimised Configuration (ROC)
•
If PA is 20 W, only 6.7 W goes to each
antenna.
•
Of that 6.7 W, two-thirds will be for users
outside the sector.
•
Only 2.2 W is useful power.
•
Power for a user in any sector is
transmitted to all three sectors.
•
Example: Assume a user requires 0.25W,
then the site must send 3x0.25W to
provide power in the specific sector.
•
Therefore only 27 users can be provided
for, instead of the 80 expected.
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Wanted power for user
in this sector is also
transmitted to the other
two sectors.
95
Antennas and Sectorisation
Roll-out Optimised Configuration (ROC)
•
The effect on DL capacity depends
on the path loss.
•
For small values of path loss the
effect on DL capacity could be
small.
•
For large values of PL the
difference could be substantial.
•
A factor of 1:4 (ROC vs. 1+1+1) is
appropriate if coverage is planned
for 12.2 kbps voice.
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Boundary problems may
outweigh any saving
96
7 Soft Handover Issues
7.1 Macro-diversity & Maximal Combining Gain
Soft Handover is a necessity in any single-frequency cellular network. In
a multi-frequency technology, such as GSM, the possibility exists to
ensure that the “new” connection has a significantly lower path loss than
the “old” connection before handover takes place. In a single frequency
network, the resulting interference on the “new” cell would drastically
reduce the capacity of the network. Soft handover entails the mobile
simultaneously connecting with more than one cell. Although the most
significant purpose of introducing Soft Handover was to reduce uplink
interference, there are other beneficial effects. Firstly, when more than
one path is provided for the radio link, a diversity gain is obtained. There
is a low probability of both channels suffering a bad fade simultaneously.
Thus there is a reduced need for a margin to accommodate such fades. In
this way, the target Eb/N0 value can be reduced when in soft handover.
This is true of both the uplink and the downlink.
In addition to the diversity (or “macro-diversity”) gain afforded, the
receiver in the mobile (and the receiver at a Node B that is used when two
cells from the same Node B are in soft, or rather “softer” handover)
processes the multiple received signal to produce and output that is of
higher quality than any individual signal. The result on the uplink is that
the transmit power of the mobile can be substantially reduced when in
soft handover – having beneficial effects for coverage and interference.
On the downlink, providing additional handover channels places a power
burden on the cell. This is partially (but usually not fully) offset by
reduction in the target Eb/N0 value. The general conclusion is the Soft
Handover assists the uplink but places an additional burden on the
downlink. The amount of use made of soft handover affects the relative
capacities of the two directions.
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Soft Handover
Soft Handover
• As well as providing vital power control functionality, Soft Handover
improves the quality of the channel by means of two methods.
• Macro-diversity Gain
• Maximal Combining Gain
Soft Handover
Macro-Diversity Gain
• If the mobile communicates with
more than one cell, protection
against failure is provided as this
failure would have to occur on all
links to cause a call to drop.
25
20
15
• As the better quality link can be
selected, there is less variation in
overall channel quality.
10
5
0
• This leads to a reduction in Power
Rise – the increase in average
transmit power that occurs as a
mobile responds to power control
commands.
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Mobile Tx Pwr
Average
Non-fading
Power Rise
98
Soft Handover
Macro-Diversity Gain
• The reduction in Power Rise
helps to increase uplink
capacity as the average Tx
power is reduced.
25
20
15
10
5
0
-5
Mobile Tx Pwr
Average
Non-fading
Reduced Power Rise following Macro Diversity Gain
Soft Handover
Soft Handover – Combining the Signals
• On the Uplink there are two possible methods of combining the two
(or more) signals.
• When the two cells are on separate sites (conventional “soft”
handover), the RNC simply selects the better of the two signals.
• When the two cells are on the same site (“softer” handover),
maximal combining of the two signals can be implemented.
• Maximal combining leads to an output that is of better quality ( less
noisy ) than either of the individual signals.
• Maximal combining is implemented in the mobile to combine the
downlink signals.
• Macro-diversity gain and Maximal combining gain combine to
produce Soft Handover Gain.
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Soft Handover
Soft Handover – Maximal Combining
• Consider the case where two signals arrive at the inputs to a
combiner. One is “good” (e.g. Eb/No = 8 dB) and the other is “poor”
(Eb/No 1 dB).
•Eb/No 8
dB
•??
•Eb/No 1
dB
• It is possible to combine the signals such that the output has an
Eb/No greater than 8 dB. This requires correct (“maximal”) weighting
of the two signals.
Soft Handover
Soft Handover – Maximal Combining
• The Eb/No at the output when the inputs are maximally
combined is given by the simple formula.
⎛ Eb ⎞
⎛E ⎞ ⎛E ⎞
⎜⎜
⎟⎟ = ⎜⎜ b ⎟⎟ + ⎜⎜ b ⎟⎟
⎝ N 0 ⎠ out
⎝ N 0 ⎠1 ⎝ N 0 ⎠ 2
• It must be noted that Eb/No is quoted as a ratio (not in dB).
• 8 dB corresponds to 6.3 as a ratio.
• 1 dB is a ratio of 1.26.
• These sum to 7.56 which is 8.8 dB.
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7.1.1 Exercise 1
What Eb/No improvement is offered when two signals of equal quality
are combined ?
Answer :-
7.1.2 Exercise 2
What is the Eb/No at the output of a combiner if the input is composed of
two signals one with an Eb/No of 6 dB and the other with and Eb/No of 2 dB?
Answer:
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7.2 Optimising Soft Handover Parameters
Soft Handover
Optimising Soft Handover Parameters
• The parameter of most significance is the Soft Handover
“Add” and “Remove” Windows.
• They influence the number of terminals in soft handover.
• Generally, the larger the window is made, the lower the
loading on the uplink and the higher the loading on the
downlink.
• The path loss at the cell edge will influence the optimum
value of the SHO window.
• The lower the path loss the larger the value can be (as the
downlink will probably have plenty of spare power available).
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Soft Handover
Optimising Soft Handover Parameters
4 dB
window
2 dB
window
• The amount of improvement on the uplink and loading on the
downlink depends on the amount of soft handover gain
achieved.
Soft Handover
Optimising Soft Handover Parameters
4 dB
window
2 dB
window
• Suppose each terminal shown above represents a 64 kbps
4 dB Eb/No connection.
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Soft Handover
Estimating FRE
• Suppose the terminals are arranged in
groups of 4 with the path loss to the two
Node Bs changing in 1 dB increments.
4 dB
window
• The red terminals will each cause an
interference level 1 dB less than the wanted
signals: equivalent to the load of 3
terminals.
• The orange terminals will each cause an
interference level 3 dB less than the wanted
signals: equivalent to 2 terminals.
2 dB
window
• Total interference load: 5 equivalent
terminals. FRE = 62.5% (5/8)
Soft Handover
Estimating FRE and Loading
• Eb/No is 4 dB
4 dB
window
• Pole Capacity = 995 kbps
• Loading = 54% (NR=3.4 dB)
• On DL, if Link Loss = 125 dB, each
terminal will require approximately
15 dBm of power, a total level of 24
dBm traffic power.
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2 dB
window
104
Soft Handover
Estimating The Effect of SHO
• Assumptions:
• Window set to 4 dB.
4 dB
window
• SHO allows the UL Tx power to reduce by 1.5 dB
(Effectively making the Eb/No 2.5 dB).
• SHO allows the target Eb/No on the DL to be reduced.
This is assumed to be 2 dB (maximal combining on
downlink).
• BUT downlinks must service twice the number of
terminals (a 3 dB extra burden).
2 dB
window
• Summarising the effect: UL loading factor will reduce
from 54% to 38%. NR will reduce from 3.4 dB to 2.1
dB. Downlink Tx Power will increase by approximately
1 dB.
Soft Handover
Estimating The Effect of SHO
• If the window is set to 2 dB.
• The DL will only have to suffer an increase of 50% in
the number of terminals (to 12) and 8 of these will
benefit from SHO gain. Overall increase in burden
estimated to be 0.5 dB.
4 dB
window
• UL split between users with a target Eb/No of 2.5 dB
and those with 4 dB. Combined loading estimated to
be 27% + 19% = 46%
• Summarising the effect: UL NR will reduce from
3.4 dB to 2.7 dB.
2 dB
window
• Downlink Tx Power will increase by 0.5 dB.
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Soft Handover
Estimating The Effect of SHO: Conclusion
• Setting the window to the optimum size can
balance the uplink and downlink in a network.
4 dB
window
• Note that example here is with symmetrical
loading. Excessive SHO reduces the ability for
the DL to serve asymmetric users.
• Note also that SHO requires additional
hardware in the Node B to provide the
necessary bearers.
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2 dB
window
106
8 Parameter Planning
8.1 Introduction
The performance of a network can be influenced by the setting of
parameters, particularly at the Node B. This section reports on
recommended values for various parameters such as Pilot Power and
Synchronisation Channel power as a proportion of the maximum power
available from a cell. Additionally, the maximum power that a single
user is permitted to use influences the throughput available to such a user
and also ensures that a certain capacity is kept available.
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Parameter Planning
Parameter Planning
• We have already examined adjusting the Noise Rise limit and SHO
parameters.
• Probably the most significant parameter is the Pilot channel power.
• The pilot is vital to be able to synchronise the channel; sound the
channel; select the serving cell.
• Without pilot coverage, there is no coverage.
8.2 Pilot Channel Power
Parameter Planning
Parameter Planning: Pilot Channel
• However, there is no point in providing pilot coverage in
areas where it is not possible to establish a traffic channel.
• The pilot channel power needs to be decided in conjunction
with other cell parameters.
• Synchronisation channel power
• Maximum power
• Maximum power per user
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Parameter Planning
Parameter Planning: Pilot Channel
• Synchronisation channel power: this is the channel the
mobile initially locks onto. It makes sense for the cell with
the strongest SCH to also be the best pilot.
• Maximum power; pilot power is related to maximum cell
power – it is pointless using a large fraction of the total
available power in the pilot leaving little for the user
channels.
• Maximum power per user. This is again related to the pilot
power and dictates the maximum user data rate that can be
provided in different environments (experiencing different
levels of pilot SIR).
Parameter Planning
Parameter Planning: Pilot Channel
• Typical Values:
Maximum Power
43 dBm
Pilot Power
33 dBm
SCH Power (Prim/Sec-SCH)
28 dBm
Maximum power/user
30 dBm
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8.3 Maximum Power per User
Parameter Planning
Parameter Planning: Maximum power/user
• Suppose planning of pilot coverage aims for a minimum value
of pilot SIR to be -12 dB.
• SIR – Signal to Interference Ratio
• If the maximum power per user equals the pilot power then
the Ec/Io experienced in these areas will also be -12 dB.
Parameter Planning
Parameter Planning: Maximum power/user
• If required Eb/No is, for example, 4 dB then a processing
gain of 16 dB will be needed. This corresponds to a
throughput of approximately 96 kbps.
• Note that the throughput will be higher for the same transmit
power in regions with a better Ec/Io.
• If maximum power per user is reduced to, say 4 dB below
pilot, then maximum throughput will be reduced to 38 kbps at
the cell edge.
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8.4 Common Channel Powers
Parameter Planning
Parameter Planning: other parameters
• “Rules of Thumb” for other parameters to equalise coverage for all
vital channels.
P-CCPCH
-5 dB relative to pilot power
PICH
-8 dB relative to pilot power
AICH
- 8 dB relative to pilot power
S-CCPCH
-5 dB relative to pilot power
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9 Multi-frequency Planning
9.1 Network Performance
Multi-Frequency Planning
Using more than one Carrier Frequency
• Using more than one carrier on the Macro-cell layer will lead
to an improvement in Network Performance.
• By choosing the appropriate system parameters the Network
Planner can divide this resource between
• Capacity improvement
• Coverage improvement
• A combination of Coverage and Capacity improvement
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Multi-Frequency Planning
Capacity Improvement
• Using an extra carrier will allow double the number of
simultaneous connections to be made within a cell if all other
parameters (pilot power, noise rise limit etc.) are kept equal.
• This will lead to more than double the amount of subscribers
being serviced through the greater trunking efficiency
obtained.
• Example: each carrier can support 15 simultaneous
connections. A single carrier will service 9 Erlangs of
demand, two carriers will service 22 Erlangs of demand.
Multi-Frequency Planning
Coverage Improvement
• If capacity is not the main issue it is possible to improve
coverage by reducing the Noise Rise limit.
• Example:
• Noise Rise Limit 3 dB, loading factor 50%.
• Two carriers with a loading factor of 25% will carry the
same amount of traffic.
• 25% loading factor results in a 1.25 dB Noise Rise.
• A coverage improvement of 1.75 dB will result with the cell
servicing the same level of demand.
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10 Micro-cell Planning
10.1 Introduction
The use of hierarchical cell structures is well established within cellular
networks. In a network such as GSM, each layer would typically have
separate carriers allocated. A UMTS operator may have only 2 carriers
allocated and would therefore be very concerned about maximising the
capacity of each carrier. This may entail creating what would normally be
called a micro-cell but allocating it the same frequency as a macro-cell
layer. This section investigates the benefits possible in terms of network
capacity that come from introducing micro-cells.
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10.2 Micro-cells targeting hot spots
Micro-cell Planning
Micro-cell planning
• Micro-cells can provide coverage for areas of high subscriber density.
• They are usually targeted at “hot spots”.
• The micro-cell layer may not provide continuous coverage. In this
case continuous coverage is provided by the macro-cell layer.
Macro cell layer
providing
continuous
coverage
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Micro cells
serving hot
spots.
115
Micro-cell Planning
Micro-cell planning
Macro cell layer
providing
continuous
coverage
Micro cells
serving hot
spots.
• In this situation the micro-cell layer must be allocated a different
carrier frequency to the macro-cell layer.
• If they are allocated the same frequency, uplink interference on the
macro-cell will prevent coverage from being continuous.
Micro-cell Planning
Micro-cell planning
Power from mobiles served by
micro-cell generate Noise Rise on
the macro-cell if they share the
same frequency.
• As the path loss on micro-cells is small, they tolerate high Noise Rise.
• If the macro-cell uses the same frequency as the micro-cell, this Noise
Rise will appear on the macro-cell either triggering NR limit failures or
reducing coverage to a similar range to that of a micro-cell.
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Micro-cell Planning
Micro-cell planning
Small, “micro-cells” forming part
of the macro-cell layer.
• The capacity of the macro-cell layer can be maximised by making the
cells small. However, it is essential that these very small “macro-cells”
provide complete coverage.
• The larger macro-cells will probably experience a low FRE frequency
re-use efficiency (i will be large) leading to poor performance.
Micro-cell Planning
Micro-cell planning: explanation of low FRE
High subscriber density in
neighbouring cell leads to high
value of i, low FRE.
" other cell power"
" own cell power"
1
FRE =
1+ i
i=
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Micro-cell Planning
Macro-cell: micro-cell interference
Link loss to micro-cell on adjacent
carrier as low as 80 dB. 33 dB
protection insufficient to prevent NR
failure.
Link loss to serving macro-cell
approximately 140 dB. To maintain
required Eb/No, the mobile must
transmit at approximately +20 dBm.
• The so-called “near-far” problem includes the situation where a
mobile being served by the macro-cell layer gets very close to a
micro-cell on the adjacent carrier.
• Interfering ‘receive levels’ as high as -75 dBm are theoretically
possible.
• Dropped calls will result.
Micro-cell Planning
Solutions to Interference Problem
• You can physically prevent path losses as low as 80 dB occurring.
• You could perform hard handover to micro-cell layer.
• You could raise the Noise Floor of micro-cell receiver.
•
-85 dBm interference power is less serious if the noise
floor is -80 dBm.
•
Micro-cell link budgets will often be able to withstand a
Noise Rise of 15 dB above a noise floor of -80 dBm.
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Micro-cell Planning
Challenging the Assumptions
• Conventional wisdom suggests that micro-cells need a
separate layer (i.e. a separate carrier frequency) because:
• They serve a high user density
• They operate at high Noise Rise limits
•
Hence generate high levels of noise rise in
neighbouring cells
•
Hence would “wipe out” the macro-cell if it was
sharing the same frequency
Micro-cell Planning
Challenging the Assumptions
• Recent research work (“3g 2002”, IEE, London, May 2002)
suggests that it may sometimes be beneficial to employ a
micro-cell sharing the same frequency as a macro-cell.
• What has changed? What is the secret?
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Micro-cell Planning
Challenging the Assumptions
• Success of the frequency-sharing strategy depends on controlling
the pilot power of the micro-cell and macro-cell to balance the
loading of the two cells to the required level.
• For the strategy to be a “success”:
• Overall uplink power must be reduced for similar traffic loading.
• Capacity must be increased “significantly”.
Micro-cell Planning
Challenging the Assumptions
• Overall power reduction:.
Without a micro-cell, the power
levels will converge so that
satisfactory SNR is achieved.
With a micro-cell (at the same
frequency), the power levels of
mobiles near the new cell will reduce.
But how much extra capacity could
this generate?
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Micro-cell Planning
Can such micro-cells cope with “hotspots”
• The purpose of micro-cells is to service areas of higher than
normal traffic density.
Micro-cell Planning
Can such micro-cells cope with “hotspots”
• Consider a macro-cell whose noise rise limit is set so as to limit the number
of simultaneous voice connections to 30. This will service 22 Erlangs of
traffic.
• A hotspot of 10 extra Erlangs of traffic is produced by a small area.
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Micro-cell Planning
Can such micro-cells cope with “hotspots”
• Major issues:
•Micro-cell
• Pilot Power
• NR limit on Micro-cell
•Macro-cell
Micro-cell Planning
Major Planning Issues
• Pilot Power:
• Determines “capture area”.
• Mobiles at cell edge will transmit
different powers on either side of
“border”.
• Macro-cell mobile will cause more
NR on micro cell than it will on
serving cell.
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Micro-cell Planning
Major Planning Issues
• NR limit:
• NR limit can be increased so that
NR from adjacent cell does not
cause failures.
• Critical that it is not made so high
that Eb/No failures result or Tx
powers rise so as to cause NR
failures in macro-cell.
Micro-cell Planning
Critical Parameters
• Size and position of hotspot:
• Micro-cell traffic cannot approach that of macro-cell.
• Physical size of coverage of micro-cell should be kept
small for best performance.
• Physical distance between two cells helps with isolation.
• Tailoring of radio environment so that path loss increases
rapidly outside micro-cell coverage area helps considerably.
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Micro-cell Planning
Case Study Results
• Original Macro-cell 22 Erlangs : 0.25% failure
• Introduce 10 Erlang hotspot: 13% failure
• Cover hotspot with identical cell: 6% failure (only 1-2 extra
terminals served).
• Reduce pilot power of micro-cell by 10 dB, increase NR limit for
micro-cell by 10 dB: 0.8% failure.
Micro-cell Planning
Conclusions
• “Same frequency” micro-cells can service weak hotspots.
• This maximises the service achieved from a single carrier but:
• Service per cell drops significantly (e.g. 33% increase in
traffic served for 100% increase in cells).
• Cost of micro site is substantially cheaper
• If short on spectrum, ie only 1 carrier provides for growth in
traffic
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11 Coverage & Capacity
11.1 Introduction
Coverage versus Capacity
Introduction
• Coverage and Capacity
• What are the limiting factors ?
• How can you spot uplink limited coverage
• How can you tell downlink limited coverage
• Traffic Mix
• Application dependent ( will alter with time )
• High degree of data rate mixing
• UMTS is not optimised for voice
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Coverage versus Capacity
Techniques for improving coverage
• In general coverage is Uplink limited
• Downlink limited situations are possible for example:
• Asymmetric data rates +
•
Mast head amplifiers
•
Low base-station power
•
UL Diversity employed
•
Users positioned at high path loss
• Link budgets provide a method for calculating initial cell
range.
• Improving coverage may result in reductions in capacity
Coverage versus Capacity
Limiting Systems
• Uplink Limited
• Noise Rise failures, caused by the number of attached
mobile terminals
• Capacity fixed by Loading Factor
• Maximum coverage influenced by Noise Rise limit
• Uplink Eb/No failures
• Downlink Limited
• Downlink Eb/No failures
• Caused by the Node B power limit being reached
• Capacity variable due to mobile positions in cell
• Maximum uplink coverage defined by Noise Rise limit,
Eb/No, data rate and mobile transmit power.
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Coverage versus Capacity
Improving Coverage
• UpLink Limited Defined
• Combination of path loss, noise floor, feeder losses,
antenna gains, noise rise, processing gain, Eb/No, mobile
transmit power, result in the maximum path loss being
lower than that to the cell edge.
• Solution
• Improve uplink load equation (MHA; diversity;
reduce interference; reduce cell range)
• DownLink Limited Defined
• Total Node B power and/or maximum power per user is
insufficient to meet demand. Demand for power results
from: data rates; Eb/No; link loss; noise floor of mobile;
noise rise; interference.
• Solution
• Improve downlink load equation
• Improve downlink link budget
Coverage versus Capacity
Load Equation
• We will use separate Uplink and Downlink Load Equations
• Both Include
• Eb/No
• Processing Gain – eg 25dB for voice at 12.2kbps
• Activity Factor
• Inter-cell Interference
• Soft Handover Gain
• Specific to Downlink
• Orthogonality factor – typically 0.6
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Coverage versus Capacity
UpLink Cell Load
• Capacity Limited
• Capacity is directly proportional to maximum uplink cell load
•
Determined by Noise Rise limit
• Path Loss rises exponentially with cell load
• Pole Capacity is never reached due to finite power of mobile terminals
• 30% cell load is 1.5dB noise rise
• 70% cell load is 5.2dB noise rise
Coverage versus Capacity
UpLink Budgets
• Determine the allowed propagation loss for 3 different services.
• Speech at 12.2kbps
• Data 64kbps
• Asymmetric Data 64kbps Uplink, Data 384kbps Downlink
• Record your answers and settings in the tables provided
• Assume
• Maximum Transmit Power of 21 dBm
• Software handover gain of 2dB
• Loading factor of 50%
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11.2 Exercise Link Budgets
Coverage versus Capacity
Link Budget - voice
Parameter
UpLink
DownLink
kbps
Noise Figure
3.0
8.0
40.0
dBm
Interference
Floor
dBm
0.0
18.5
dBi
Rx Sensitivity
dBm
Body/Cable
Loss
3.0
2.0
dB
Rx Antenna
Gain
18.5
0.0
dBi
Processing
Gain
24.98
24.98
dB
Cable/Body
Loss
2.0
3.0
dB
Eb/No
6.0
7.0
dB
Fast Fade
Margin
3.0
0.0
dB
MDC gain
0.0
1.2
dB
Soft handover
gain
2.0
2.0
dB
Parameter
UpLink
DownLink
Bit Rate
12200
12200
Max Tx Power
21.0
Antenna Gain
Target Loading
%
Noise Rise
dB
Thermal Noise
-108.1
-108.1
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Allowed
Propagation
Loss
dB
dB
dBm
129
Coverage versus Capacity
Link Budget – 64kbps symmetric
Parameter
UpLink
DownLink
kbps
Noise Figure
3.0
8.0
40.0
dBm
Interference
Floor
dBm
0.0
18.5
dBi
Rx Sensitivity
dBm
Body/Cable
Loss
0.0
2.0
dB
Rx Antenna
Gain
18.5
0.0
dBi
Processing
Gain
17.78
17.78
dB
Cable/Body
Loss
2.0
0.0
dB
Eb/No
4.0
5.0
dB
Fast Fade
Margin
3.0
0.0
dB
MDC gain
0.0
1.2
dB
Soft handover
gain
2.0
2.0
dB
Parameter
UpLink
DownLink
Bit Rate
64000
64000
Max Tx Power
21.0
Antenna Gain
Target
Loading
%
Noise Rise
dB
Thermal Noise
-108.1
-108.1
dB
dB
Allowed
Propagation
Loss
dBm
Coverage versus Capacity
Link Budget - Asymmetric
Parameter
UpLink
DownLink
Bit Rate
64000
384000
Max Tx Power
21.0
Antenna Gain
Parameter
UpLink
DownLink
kbps
Noise Figure
3.0
8.0
40.0
dBm
Interference
Floor
dBm
0.0
18.5
dBi
Rx
Sensitivity
dBm
Body/Cable
Loss
0.0
2.0
dB
Rx Antenna
Gain
18.5
0.0
dBi
Processing
Gain
17.78
10.0
dB
Cable/Body
Loss
2.0
0.0
dB
Eb/No
4.0
1.0
dB
Fast Fade
Margin
3.0
0.0
dB
MDC gain
0.0
1.2
dB
Soft
handover
gain
2.0
2.0
dB
Target
Loading
%
Noise Rise
dB
Thermal Noise
-108.1
-108.1
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Allowed
Propagation
Loss
dB
dB
dBm
130
Coverage versus Capacity
UpLink Budgets
•
Determine the maximum number of users for the 3 services to provide for a
loading factor of approximately 50% in the uplink – integer number of channels.
•
Calculate the remaining throughput using eq1, determine how many further
speech channels could be allocated.
Remainingthroughput = ⎣ pole _ capacityuserbitrate × loading _ factor ⎦ − throughput
Availablespeech =
Remainingthroughput
userbitratespeech × activity _ factorspeech
eq1
•
Service
Record your answers in the table provided.
Eb/No (dB)
Activity
Inter-cell
Loading Factor
pole_capacity
kbps
Remaining
bits/s
Availablespeech
Speech
6
0.67
0.83
49.21%
531.55
4206
0
64kbps
4
1
0.83
44.12%
870.35
51172
6
384kbps
1
1
0.83
40.92%
1876.62
170311
20
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11.3 Downlink Limited
Coverage versus Capacity
Downlink Limited
• Increase cell loading = Increase in cell capacity
• Range of cell is reduced ( cell breathing )
• Power per user is less due to smaller path loss
• PNB = Pusers + Ppilot + Pcommon
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Coverage versus Capacity
Node B Transmit Power
•
The Node B must provide power for each active user in each
cell, including those connected in soft-handover.
•
The Node B must also support the pilot, control and
synchronisation channels
• If we assume 20% of the cell power is assigned to these
Node B Tx Power per cell per carrier
Application
37 dBm (5W)
Low capacity, mainly service coverage
40 dBm (10W)
Medium capacity, look at using 2 carriers at
10W instead of 1 carrier at 20W
43 dBm (20W)
Standard operation
46 dBm
High propagation loss scenarios
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Coverage versus Capacity
Propagation Loss v Cell Transmit Power
80
Number of Speech Users
70
60
50
Node B Power 37 dBm
Node B Power 40 dBm
40
Node B Power 43 dBm
Node B Power 46 dBm
30
20
10
0
140
145
150
155
160
165
170
Maximum Allowed Propagation Loss ( dB )
•Pilot set at 33dBm, Common Channel set at 33dBm
•Orthogonality set at 0.55, Inter-cell Interference set at 0.5, Eb/No set at 6.5 dB
Coverage versus Capacity
Propagation Loss v Cell Transmit Power
80
Number of Speech Users
70
60
50
Node B Power 37 dBm
Node B Power 40 dBm
40
Node B Power 43 dBm
Node B Power 46 dBm
30
20
10
0
140
145
150
155
160
165
170
Maximum Allowed Propagation Loss ( dB )
Power (dB)
Users
•
If we assume that path loss is 150dB
37
30
•
Number of users for each power level is
40
60
43
68
46
72
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Coverage versus Capacity
Required Tx Power v Number of Speech Users
Eb
N
η DL = ∑ ν j ×
j =1
W
60
58
No
× (1 − α + i j )
56
54
52
Rj
50
•
Note as loading factor, η, tends to 1,
Node B power tends to infinity
TxPower ( dBm)
48
46
145dB
150dB
155dB
160dB
44
42
40
•
36dBm pilot + common power
38
36
34
N rf × W × L × ∑ν j ×
j =1
TxPower =
1 − η DL
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W
32
No
Rj
30
30
32
34
36
38
40
42
44
46
48
50
52
54
56
58
60
62
64
66
68
70
72
74
N
Eb
Numberof SpeechUsers
+ pilot + common
135
11.4 Predicting the Capacity of the Downlink
Coverage versus Capacity
An example: Predicting Downlink Capacity
• If a single extra user is
•Actual Traffic Power: 36 dBm
•Maximum: 42 dBm
introduced, and this new user
demands downlink data, it is
possible to predict the amount
of power required to deliver a
certain amount of data.
• This is an iterative process
and the result will depend on
•Actual Traffic Power: 38 dBm
•Actual Traffic Power: 34 dBm
•Maximum: 42 dBm
•Maximum: 42 dBm
the specific user environment.
• Is it possible to predict the
extra downlink capacity of a
cell in general?
Coverage versus Capacity
Predicting Downlink Capacity
• The Noise Rise
experienced by a mobile
depends on the
throughput, the pole
3840
capacity and the loading
factor.
• However, pole capacity
and loading factor are
parameters that are
specific to a particular
Eb
N0
(1−α +i)
user.
• The general expression
for pole capacity is given
here.
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Coverage versus Capacity
Predicting Downlink Capacity
• If general values for
orthogonality and i are
assumed (e.g. both
equal to 0.6) then the
3840
pole capacity can be
estimated for a given
value of Eb/N0.
• If Eb/N0 is 5 dB (3.16 as
a ratio) then the pole
capacity would be 1214
Eb
N0
(1−α +i)
kbps.
• If the throughput was half
of this then the Noise
Rise experienced by a
typical user can be
estimated to be 3 dB.
Coverage versus Capacity
Predicting Downlink Capacity
• So, cells serving 50
voice terminals at an
Eb/N0 value of 5 dB
could be expected to
generate a Noise Rise
of 3 dB on the
downlink.
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Coverage versus Capacity
Predicting Downlink Capacity
• In order to answer the question
“How much extra capacity is
available?” it is necessary to
know how much power is
available.
• Suppose serving these users
required a traffic power of 37
dBm from a maximum available
of 42 dBm.
Coverage versus Capacity
Predicting Downlink Capacity
• The question now
becomes: “If 37 dBm
Noise Rise vs. Throughput
rise, how much noise
rise (and hence
loading factor) will 42
Noise Rise
produces 3 dB of noise
20.00
18.00
16.00
14.00
12.00
10.00
8.00
6.00
4.00
2.00
0.00
What will be the
increase in
throughput?
1 2
dBm produce?”.
3
4
5
8
9 10 11 12 13 14 15
Throughput (x100kbps)
37 dBm produces
3 dB NR
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Series1
How much NR will
42 dBm produce?
138
Coverage versus Capacity
Predicting Downlink Capacity
• The analysis involves
imagining that the cell
User Power B dBm
transmits not only user
power but also some
Noise Power A dBm
“Noise Power” and the
Σ
mobile exists in a
• For example, if the Noise
noise-free environment.
Rise was 3 dB and the User
Power transmitted was 37
dBm then the Noise Power
would also be 37 dBm.
Coverage versus Capacity
Predicting Downlink Capacity
User Power B dBm
Noise Power A dBm
• Generally:
Σ
⎡ (user power )10 ⎤
10
⎥ dBm
A = 10 log ⎢
NR
⎢
10 − 1 ⎥
⎣ 10
⎦
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Coverage versus Capacity
Predicting Downlink Capacity
User Power increased
User Power C dBm
Noise Power A dBm
• If the user power is
increased, the new
Noise Rise can found.
Σ
(C −A) ⎤
⎡
10 dBm
NR = 10 log⎢1 + 10
⎥
⎣
⎦
Coverage versus Capacity
Predicting Downlink Capacity
• Noise Rise leads to loading
factor which leads to
throughput.
⎡ (user power )10 ⎤
10
⎥ dBm
A = 10 log ⎢
NR
⎢
⎥
10
−1 ⎦
⎣ 10
(C−A) ⎤
⎡
10 dBm
NR = 10log⎢1 +10
⎥
⎣
⎦
η = 1 − 10
throughput =
UMTS Advanced Cell Planning and Optimisation
©AIRCOM International Ltd 2003
− NR
10
3840
Eb
N0
(1 − α + i )
η
140
Coverage versus Capacity
Predicting Downlink Capacity
⎡ (user power )10 ⎤
10
⎥ dBm
A = 10 log ⎢
NR
⎢
⎥
10
−1 ⎦
⎣ 10
• In the example discussed.
•
37 dBm of user power
produced 3 dB noise rise.
(C−A) ⎤
⎡
10 dBm
NR = 10log⎢1 +10
⎥
⎣
⎦
• 42 dBm of user power would
therefore produce 6.2 dB of
NR.
η = 1 − 10
• Loading factor is now 76%
• Potential throughput is now
922 kbps at Eb/N0 of 5 dB.
throughput =
− NR
10
3840
Eb
N0
(1 − α + i )
η
Coverage versus Capacity
Predicting Downlink Capacity
• This extra capacity of 315 kbps at an
Eb/N0 of 5 dB can be used to deliver a
Extra Capacity
315 kbps at 5 dB
Eb/No
much higher throughput at a lower
Eb/N0.
• For example, if the extra capacity was
used by a packet bearer that required
an Eb/N0 of only 1 dB, 790 kbps would
be achievable.
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Extra Capacity
790 kbps at 1 dB
Eb/No
141
Coverage versus Capacity
Predicting Downlink Capacity
• This extra capacity of 315 kbps at an
Eb/N0 of 5 dB can be used to deliver a
Extra Capacity
315 kbps at 5 dB
Eb/No
much higher throughput at a lower
Eb/N0.
• For example, if the extra capacity was
used by a packet bearer that required
an Eb/N0 of only 1 dB, 790 kbps would
be achievable.
Extra Capacity
790 kbps at 1 dB
Eb/No
Coverage versus Capacity
Summarising……….
• Extra capacity has been predicted by
Extra Capacity
315 kbps at 5 dB
Eb/No
making general assumptions, in
particular regarding a global value of
the pole capacity on the downlink.
• Method requires validation.
• Enterprise 3G, AIRCOM’s UMTS
planning tool was used to verify the
Extra Capacity
790 kbps at 1 dB
Eb/No
method.
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Coverage versus Capacity
Verifying……….
• Enterprise 3G will predict the
Extra Capacity
315 kbps at 5 dB
Eb/No
performance of the network under a
particular definable load by simulating
the action of the network as mobile
users request a service and succeed
or fail as appropriate.
• Critical parameters such as downlink
traffic channel power are recorded for
Extra Capacity
790 kbps at 1 dB
Eb/No
each cell in the network.
Coverage versus Capacity
Verifying………
• A network was dimensioned and fully
loaded with symmetric voice traffic.
• Throughput per cell approximately
220 kbps
• Estimated Noise Rise on downlink is
2.2 dB.
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Coverage versus Capacity
Verifying………
• Report shows that downlink traffic
channel power is about 34 dBm.
• Maximum traffic power of 42 dBm can
lead to a 7.1 dB downlink noise rise.
• Throughput on downlink can be
doubled.
Coverage versus Capacity
Verifying………
• The simulator was run once more
having added the appropriate amount
of downlink only traffic.
• Simulation supports analysis. Traffic
was served and downlink traffic power
was at near-maximum value.
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Coverage versus Capacity
Contemplating………
• The input parameters were:
Downlink Tx
Power 37 dBm
• Maximum Traffic Channel Power
• Estimate of Pole Capacity
• Report of throughput and traffic
channel power for a known amount
of symmetric traffic.
• It is this last requirement for which
Downlink Tx
Power 42 dBm
Enterprise 3G simulation functionality
is needed. Could we estimate this…?
Coverage versus Capacity
Further Analysis………
• Factors that affect the amount of
Downlink Tx
Power 37 dBm
downlink power required for a given
amount of traffic:
•Pathloss
•Antenna Characteristics
•Pilot and Common channel powers
•Orthogonality
Downlink Tx
Power 42 dBm
•Out of Cell Interference
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Coverage versus Capacity
Further Analysis………
• Determining the power required for
Single user: easy
one particular user is relatively
straightforward.
• Determining the power required for
Evenly spread users:
not so easy
users evenly spread across the
coverage area is more difficult.
• Determining the power required for
users unevenly spread across the
coverage area is next to impossible.
Unevenly spread
users: very difficult
Coverage versus Capacity
The evenly loaded cell………
• The big question is “is there a magic
location such that the downlink power
is the same as if all mobile were
located at that point?”.
• What is the path loss to this point?
• The problem is that path loss is not the
High Path Loss,
High Interference
Low Path Loss,
Low Interference
only variable. Interference also varies
significantly.
Magic Location
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Coverage versus Capacity
The evenly loaded cell………
• A rule of thumb.
• The “magic spot” has a path loss 4 dB
less than the cell edge.
• Where did this figure come from?
High Path Loss,
High Interference
•Analysis making suitable
Low Path Loss,
Low Interference
assumptions plus…
•Experimentation using the
Enterprise 3G simulator!
• Either way the simulator is invaluable.
Magic Location
Coverage versus Capacity
An example………
• Suppose the link loss to the cell edge is
135 dB.
• The link loss to the magic spot is 131 dB.
• Common Channel plus pilot power is 36
dBm; Noise Floor is -102 dBm;
Magic Location
orthogonality is 0.6.
• What Noise Rise can be produced by a
traffic channel power of 42 dBm?
• Solution: equivalent “noise plus
interference” = -97.2 dBm.
• Received Traffic Channel Power = -89
dBm. Noise Rise = 5.6 dB. Loading
Factor = 72%.
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Coverage versus Capacity
Another example………
• Suppose the link loss to the cell edge is
145 dB.
• The link loss to the magic spot is 141 dB.
• Common Channel plus pilot power is 36
dBm; Noise Floor is -102 dBm;
Magic Location
orthogonality is 0.6.
• What Noise Rise can be produced by a
traffic channel power of 42 dBm?
• Solution: equivalent “noise plus
interference” = -99.5 dBm.
• Received Traffic Channel Power = -99
dBm. Noise Rise = 1.6 dB. Loading
Factor = 31%.
Coverage versus Capacity
The Story so Far
• It is possible to make “ball park” estimates of the capacity on the
downlink.
• The first step is to estimate a nominal pole capacity
3840
Eb
N0
(1−α +i)
• Then estimate the noise rise that can be produced at the “magic spot”.
• Hence deduce loading factor.
• This is a useful “first pass” planning calculation to perform.
• However, it does not consider an unevenly loaded network, nor does it
help us optimise network performance.
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11.4.1
Example
As an example, consider the situation where a network has been
dimensioned such that the link loss to the edge of each cell is 133 dB. All
sites have three sectors. The pilot and common channel powers are to
represent 20% of the total cell power. Estimate the pole capacity for an
Eb/N0 value of 4 dB assuming that i = 0.5 and α = 0.6.
Further, estimate throughput possible on the downlink per cell (for an
Eb/N0 value of 4 dB) if the total cell power is a) 43 dBm and b) 37 dBm.
Assume that the noise floor of the mobile is -101 dBm.
Solution. Pole Capacity =
3840
Eb
N0
(1 − α + i )
=1700 kbps
For a sectored cell “magic spot” has a link loss of approximately 126 dB.
If total power is 43 dBm, then Common plus pilot will be approximately
36 dBm. This will be received at a level of -90 dBm but will have an
effective level of -94 dBm (due to orthogonality). If this is added to the
noise floor of the mobile, the overall level of noise plus interference will
be -93.2 dBm. The cell will have 42 dBm available for traffic power. In
order to estimate the Noise Rise produced, the effective power will be 38
dBm which will be received at a level of -88 dBm. The Noise Rise will be
approximately 6.3 dB which corresponds to a loading factor of 77%
allowing the throughput to be estimated at 1300 kbps.
If total power is 37 dBm, then Common plus pilot will be approximately
30 dBm. This will be received at a level of -96 dBm but will have an
effective level of -100 dBm (due to orthogonality). If this is added to the
noise floor of the mobile, the overall level of noise plus interference will
be -97.5 dBm. The cell will have 36 dBm available for traffic power. In
order to estimate the Noise Rise produced, the effective power will be 32
dBm which will be received at a level of -94 dBm. The Noise Rise will be
approximately 5.1 dB which corresponds to a loading factor of 69%
allowing the throughput to be estimated at 1170 kbps.
The difference may not be regarded as dramatic. The effect would be
more noticeable at higher levels of path loss.
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12 Analysis, Prediction and
Optimisation of Downlink
Capacity.
Analysis of the downlink of a UMTS network is significantly more
challenging than that for the uplink. When the capacity in terms of
simultaneous users is calculated, it is usual to refer to “identical users”.
For users to be identical on the uplink they should have the same bitrate
and E b N 0 . On the downlink, the users should additionally experience
identical link loss, out of cell interference and orthogonality. Further,
there is no noise rise limit on the downlink. Rather, the downlink
transmit power can be thought of as capable of delivering a particular
loading factor.
Nevertheless, the situation where the downlink of a cell is capable of
accommodating a greater throughput than the uplink is expected to be
typical. This is largely due to two factors: more power is usually available
on the downlink; orthogonality provides greater interference reduction on
the downlink. This paper presents an analysis of the downlink that
allows rapid estimates of downlink capacity to be made for dimensioning
purposes. An initial analysis involving identical users is extended to one
for an evenly loaded cell and, further, to an evenly loaded network.
Unevenly loaded networks are tackled by explaining how a report from a
Monte Carlo simulation at one level of loading can be used to estimate the
maximum loading sustainable on the downlink. Additionally, it is
explained how a report on the quality of the pilot signal at various
locations can be used as an indication of the ease with which particular
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data rates can be achieved at that location. This has implications when
maximising cell capacity for a particular traffic distribution.
12.1 Analysis of Identical Users
As an example of a cell that is fully loaded with symmetric traffic,
consider a cell with a noise rise limit of 3 dB and an out of cell to in cell
interference ratio, i, of 0.6. This cell is loaded with traffic with an E b N 0 of
6 dB. The pole capacity is approximately 600 kbit/s which, with the
loading factor of 50% imposed by the noise rise limit, means that the
uplink capacity will be 300 kbit/s. This can be taken to be equivalent to
approximately 25 simultaneous full rate voice connections. The cell range
on the uplink is influenced by the transmit power. If the uplink power is
assumed to be 24 dBm (per user) and the noise figure of the receiver is 3
dB, then the 25 dB processing gain available will result in the maximum
link loss (which is defined as the difference between the transmitted and
received power levels) tolerated being 148 dB, assuming a thermal noise
level of –108 dBm.
In determining the downlink transmit power required to match the
uplink loading, it is necessary to make assumptions regarding the value
of the pilot power, and of other downlink common channels, as well as
link loss, out of cell interference, orthogonality and noise figure of the
mobile receivers. The relevant equations are:
PRcom =
PR int =
(N − 1)Puser (1 − α )
PTcom (1 − α )
; PRoth =
;
LL
LL
(PRcom + PRoth )i
(1 − α )
;
Eb
Puser
W
=
N 0 L L (PN + PRcom + PRoth + PR int ) R
where L L is the link loss; PN is thermal noise power; PTcom is the
transmitted power of common channels (including pilot); Puser is the
transmitted power for an individual traffic channel (considered the same
for each user); PRoth is the interference power experienced by one user as a
result of power being transmitted to (N-1) other users; PRcom is the
received level of common channel power having been effectively reduced
due to orthogonality (factor α ); i is the out of cell to in cell interference
ratio.
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The total transmit power needed to deliver the required E b N 0 to N users
is then given by (NPuser + PTcom ) . It is now possible to determine the total
transmit power required to service N simultaneous connections or,
alternatively, to predict the maximum number of connections that can be
serviced by a given maximum transmit power.
The following table shows how the total transmit power for 25 voice
connections and the maximum total number of possible equivalent
channels for a transmit power of +43 dBm vary with link loss assuming
α = 0.6; i = 0.6; E b N 0 = 6 dB; mobile receiver noise figure = 6 dB; common
channel power = 36 dBm.
TABLE 1 – Variation of Downlink Power and Capacity with Link Loss
Link Loss
(dB)
Total Tx
Power for
25 user
channels
(dBm)
110
125
140
145
150
37.62
37.69
39.33
41.63
45.26
Maximum
total capacity
for Tx Power
of 43 dBm
(identical
user
channels)
64
64
49
33
16
It is seen that, for low values of link loss, there is not much variation of
required transmit power or downlink capacity. However, as the link loss
reaches levels where significant traffic channel power is required to
overcome thermal noise, the capacity then decreases dramatically as link
loss rises.
A similar analysis can be undertaken to show the effect of different levels
of orthogonality and out of cell interference.
This straightforward analysis provides a useful insight to the way in
which downlink capacity is influenced by the parameters discussed.
However, the fact that the users are all assumed to be identical leads to
questions being asked regarding the general applicability. It is largely for
this reason that the Monte Carlo analysis method has become ubiquitous.
But this tool has a danger of encouraging a “try it and see” approach,
rather than a methodical approach to dimensioning or initial planning of
the downlink. Even if the users are evenly distributed, a Monte Carlo
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simulator would still be used. A method of predicting the downlink
capacity in the evenly loaded case would be of interest as would that of
predicting the extra downlink capacity if it is to be distributed
proportionately to an existing symmetric loading.
12.1.1
Verification Using A Monte Carlo Simulator.
In order that confidence could be placed in the prediction method
described, and in the Monte Carlo simulator within the AIRCOM 3g
planning tool, firstly 25 users were placed at a position where the link loss
was 140 dB. The cell was kept isolated (i = 0) in order to maintain control
over the situation so that a comparison could be made under controlled
conditions. The orthogonality factor was set to 0.6. It was found that 34
dBm of traffic power was required to maintain an Eb N 0 value of 7 dB at
12.2 kbit/s if the noise figure of the mobile receiver was 4 dB. This agrees
exactly with the prediction by the simpler method. The Monte Carlo
simulator was then used to predict the downlink power required when
the traffic was evenly spread over a cell coverage area. It was found that,
if traffic was spread uniformly over an area with a maximum link loss of
144 dB, the downlink traffic power required was again 34 dBm. Figure 1
shows the coverage area with the link loss being indicated in 1 dB steps
up to a maximum of 144 dB. Thus the effect on the downlink of a group
of users all at a link loss of 140 dB was the same as that evenly spread
with link losses varying from very small values to 144 dB. It is as though
the “typical user” was positioned at a loss 4 dB from the edge of the cell.
In both cases the Monte Carlo simulator agreed with the simple
prediction method in predicting that 42 dBm (the maximum available
traffic power) would service 85 similar downlink channels. Thus the two
configurations (all at 140 dB path loss or spread up to a maximum link
loss of 144 dB) again produced the same loading on the downlink. This
was verified at an orthogonality of zero, where 37.0 dBm of traffic power
was required to accommodate 25 12.2 kbit/s users and 42 dBm was
capable of servicing 46 users.
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Coverage area of test cell with link loss shown varying in 1 dB steps.
12.2 A Rapid Method for Estimating Downlink
Capacity
12.2.1
Isolated Cells
By including the power of the wanted signal with the noise rise, it is
possible to develop a very rapid calculation method for the capacity on
the downlink. Such an approximation is reasonably valid if the capacity
is to be shared amongst many users, each with a modest throughput
(rather than very few users each with a large throughput). The relevant
equations are:
3840
Eb
Pole Capacity, PC =
N0
Potential Noise Rise, NR=
(
capacity = PC 1 − 1
Then:
=
NR
(1 − α + i )
kbit/s
PT max (1 − α + i ) + PN L L
PN L L + PTcom (1 − α + i )
)
PT max − PTcom
3840
.
kbit/s
E b N 0 PT max (1 − α + i ) + PN L L
where PT max is the maximum total transmit power of the cell. The
advantage of the approximate method is that it allows the rapid
production of graphs that demonstrate the effect of BTS power, link loss,
orthogonality and out of cell interference on the capacity of the downlink.
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The effect of link loss on capacity. Figure 2 shows the effect of link loss
for various BTS powers. It is assumed that the out of cell interference
ratio, i, = 0.6. The orthogonality factor = 0.6, Eb N 0 = 5 dB. The level of
common channel power is assumed to be 7 dB less than the maximum
power. It can be seen that there is a definite maximum capacity
regardless of power level. This maximum capacity is reached when
thermal noise is negligible compared with the power received from the
network. Then:
NR =
PT max
PTcom
and
⎞
⎛
P
⎜1 − Tcom ⎟
⎟
⎜ P
(1 − α + i ) ⎝ T max ⎠
3840
Eb
Capacity =
N0
kbit/s
If PTcom is taken to be 7 dB below PT max then the above equation can be
further simplified to give
⎞
⎛
P
⎜1 − Tcom ⎟
⎟
⎜ P
(1 − α + i ) ⎝ T max ⎠
3072
Eb
Capacity =
N0
kbit/s.
Capacity (kbit/s)
1200
1000
800
600
400
200
0
120
130
140
150
160
Link Loss (dB)
+37 dBm
+40 dBm
+43 dBm
+46 dBm
The effect of link loss on downlink capacity for various values of BTS
power.
The effect of varying orthogonality is now ined for the same conditions
excepting that link loss is now fixed at 145 dB and orthogonality is varied
between zero and unity. It is noted that variation of orthogonality has the
most marked effect when the BTS power is high. At lower levels of BTS
power, thermal noise (which is not affected by orthogonality) dominates
the mobile receive power.
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Capacity (kbit/s)
1200
1000
800
600
400
200
0
0
0.2
0.4
0.6
0.8
1
Orthogonality
BTS Power: 37 dBm
40 dBm
43 dBm
46 dBm
The effect of orthogonality on downlink capacity for various values of
BTS power.
Capacity (kbit/s)
Finally, the effect of varying the out of cell interference ratio, i, keeping
link loss fixed at 145 dB and the orthogonality fixed at 0.6 was examined.
Again, the effect was most noticeable when the BTS transmit power was
high. It can be seen that out of cell interference and the value of
orthogonality both have a significant impact on the cell capacity.
1400
1200
1000
800
600
400
200
0
0
0.4
0.8
1.2
1.6
2
Out of Cell Interference
BTS Power: 37 dBm
40 dBm
43 dBm
46 dBm
.
The effect of out of cell interference ratio, i, on downlink capacity for
various values of BTS power.
12.2.2
An Evenly Loaded Network
The analysis has been conducted for various values of orthogonality
factor, α , and out of cell interference ratio, i. However, both of these
values have been assumed to be constant. In practice, the value of i in
particular will vary dramatically across the network, from very low
values close to the BTS to values typically approaching 2 at the edge of
the cell. This is in contrast to the uplink where each cell will experience
similar levels of out of cell interference, typically in the region of 0.6.
When the method for identical users was checked against an evenly
loaded isolated cell, it was found that the loading on the downlink was
approximately equal to that caused by identical users each with a link loss
4 dB less than the cell edge. The question can be extended to ask “is there
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an aggregate average value of i that can be used to rapidly estimate
downlink load and capacity?”. The cause of out of cell interference in both
directions is overlap of the radiation patterns of antennas on
neighbouring cells. Further, the users at the cell edge are the principal
producers of uplink interference and victims of downlink interference
respectively. To gain confidence in any value being taken as appropriate
for use in the prediction equations, the Aircom Enterprise 3g Monte Carlo
simulator was again used. A network was created such that 82 sites (246
cells) covered an area of 1000 km2. The link loss to the cell edge was 133
dB. The maximum downlink capacity with a maximum transmit power
of 43 dBm was found to be 460 kbit/s at a value of Eb N 0 of 7 dB. In
comparing this prediction with that made using the rapid calculation
method with an assumed link loss of 4 dB below the maximum value,
agreement was achieved if a value for i of 0.85 was taken. This agreement
held up well for various values of loading and link loss.
This allows a rapid approximate method to be developed whereby the
downlink capacity of a cell can be estimated for initial dimensioning
purposes. Given the maximum BTS power, the link loss to the cell edge,
orthogonality, the noise factor of the mobile receiver, NF, and the
required Eb N 0 value of the service:
Capacity =
3840
Eb
N0
⎞
⎛
PT max − Pcom
⎟
⎜
−
15
⎜ (NF )L × 6 × 10
+ PTcom (1.85 − α ) ⎟⎠
L
⎝
If typical values of orthogonality (= 0.6), PTcom (= PT max 5) and NF (= 4) are
put into the equation
2458 PT max
Capacity =
Eb
N0
(2.4 × 10
−14
L L + PT max
)
kbit/s
2458
Eb N 0 kbit/s at negligible levels of link
This tends to a maximum of
loss. The level at which link loss becomes significant in reducing capacity
depends on BTS power as illustrated in figure 2.
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12.2.3
Uplink-downlink balance.
The approximate equation for maximum throughput on the downlink is
remarkably similar to the pole capacity on the uplink. The fact is that it is
possible to achieve higher levels of loading factor under typical (uplink
limited) link loss values on the downlink. This situation may well change
as cells become more densely packed within a network and uplink noise
rise limits are increased to levels of 10 dB or more. Then the uplink and
downlink capacity would be more nearly equal. Features such as uplink
diversity and the implementation of mast-head, low-noise amplifiers
further favour the uplink.
12.3 Interim Conclusion
Equations have been developed that will allow the capacity of a network
in the downlink direction to be estimated for dimensioning purposes.
Analysis has been limited to situations where the geographic distribution
of users has been assumed to be uniform. The next section demonstrates
how reports from a Monte Carlo simulation can be used to estimate the
downlink capacity for an unevenly loaded network.
12.4 Simulator-aided Prediction for Unevenlyloaded Networks
As an example of the different experiences of users on the downlink,
consider the situation where users are divided into two groups: one
group of 12 users with a link loss of 120 dB and an out of cell interference
ratio of 0.3; the other group of 12 users with a link loss of 140 dB and an
out of cell interference ratio of 1.0.
An analysis reveals that the users closer to the downlink transmitter (120
dB link loss) would each require a user power 17.6 dBm whereas 22.0
dBm is required by each user at 140 dB link loss. The fact that users are at
different link losses and experience different levels of out of cell
interference leads to the different users experiencing a different noise rise.
The users near to the transmitter would experience a noise rise of 2.1 dB
whereas the users at 140 dB link loss would experience a noise rise of 1.4
dB. Note that noise rise is defined as the rise in effective noise level due
to the presence of traffic channel power. The contribution to the overall
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interference level due to common channel power (that is at a constant
level) is considered to be part of the original noise level and not part of
the noise rise. The crucial question regarding the capacity on the
downlink is very much dependent on the environment of the individual
users. In the above situation, a total transmit power of 43 dBm would
accommodate an extra 53 users if they were at a link loss of 120 dB but
only an extra 24 users if they are at a link loss of 140 dB. If the increase is
evenly divided between the two categories, an extra 32 users can be
accommodated.
The analysis of this, still over-simplified, scenario is not without difficulty
and is not in "closed form”. For more general situations where traffic
densities are declared on the basis of land usage (clutter categories), a
Monte Carlo simulator would be used. However, there is a tendency to
predict capacity on a “trial and error” basis, which is somewhat time
consuming and generally unsatisfactory.
A procedure is now reported whereby the capacity can be rapidly
estimated from the results of one simulation. It relies on an estimation of
⎛ 3840
kbit/s ⎞⎟
⎜
Eb N 0 (1 − α + i )
⎝
⎠.
the pole capacity of the cell
The value of i should
be estimated from the static analyser or, alternatively, a general value of
0.85 used. A single simulation will result in a report of the throughput.
This can be described as a loading factor that can in turn be used to
predict the noise rise experienced by a representative user on the
downlink. It is then possible to predict the noise rise that would be
produced if the maximum traffic power were applied to the downlink.
As an example, a simulation was conducted for a loading of 25 (12.2
kbit/s) voice users per cell at an E b N 0 value of 6 dB. The traffic channel
power required for a particular cell required was found to be 33.91 dBm.
It is possible to calculate the loading factor based on assumptions that the
3840
= 772
Eb N 0 (1 − α + i )
pole capacity is given by
kbit/s if α = 0.6, i = 0.85.
Thus 300 kbit/s throughput would result in a loading factor of 39% that
would produce a noise rise of 2.14 dB. The power available for traffic is
42.03 dBm. In order to work out the extra capacity possible, it is
necessary to answer the question: “if 33.91 dBm can produce a noise rise
of 2.14 dB, what noise rise would be produced by a traffic power of 42.03
dBm?”. It must be borne in mind that the traffic channel power of 33.91
dBm will be received as an equivalent of 33.91 + 10 log(1 − α + i) = 34.88 dBm.
This new noise rise can be converted to loading factor and, hence, to
throughput. A simple method of calculating the answer to this question
involves calculating the equivalent transmitted power of the noise, which
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(
)
− 1 = 36.84 dBm. Thus a traffic
in this case is equal to 34.88 − 10 log 10
power of 42.03 dBm (received as an equivalent power of 43.00 dBm once
out of cell interference and orthogonality have been considered) would
(
2.14 10
(43−36.84 ) 10
)
= 7.10 dB. This would
result in a noise rise of 10 log 1 + 10
correspond to a loading factor of 80.5%, suggesting a possible throughput
of 622 kbit/s equivalent to 52 users. This is the throughput possible if the
additional users possess a similar distribution of user density to those in
the original simulation. This method has been found to correspond
closely to that determined by simulation methods excepting those
situations where the loading is dominated by users that experience out of
cell interference values significantly different from 0.85. This can be predetermined by examination of the static analysis output.
12.5 Optimisation Issues
It is clear that the capacity on the downlink is heavily influenced by out
of cell interference on the downlink. Network capacity can be
enhanced by ensuring that any areas of high demand are in locations
where the out of cell interference is a minimum. One output that can
be obtained by conducting a simulation is the “pilot SIR”, that is the
quality of the pilot signal once interference from other channels on the
same cell has been reduced through orthogonality. Figure 5 gives an
example of a plot of Pilot SIR for a network for which the total cell
downlink power was 42 dBm and the pilot power was 33 dBm.
Pilot SIR for a heavily loaded network.
Values of pilot SIR of the order of –5 dB were reported for areas directly
in front of one of the antennas, up to a distance of about half the cell
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coverage range. The value then reduced to approximately –12 dB at the
edge of the cell. It is of note that this is the same SIR that would be
obtained by any traffic channel with a transmit power equal to the pilot (2
W). The data rate that this channel could sustain depends on the required
3840× SIR
Eb N 0 kbit/s. Thus the pilot SIR array can
be interpreted as the throughput possible at a particular value of Eb N 0 for
Eb N 0
and is equal to
unit power. This can be expressed as “bits per second per watt” (or
bits/joule). The bits per joule possible at any one location is given by
3840000 × SIR
PTpilot × (E b N 0 )
This expression has the advantage of being valid for any
level of downlink loading although most interest would probably be paid
to levels of throughput possible under high loading conditions. In
practice, an orthogonality value of 0.6 would reduce the effect of own cell
interference on the pilot SIR by 4 dB. Thus the best value of SIR that can
be obtained (when out of cell interference and thermal noise are at
negligible levels) is –4.4 dB. This suggests that values of approximately
220 kbit/J at an Eb N 0 value of 5 dB are achievable in the most favourable
locations. What is of considerable interest from a capacity enhancement
viewpoint is that the value of SIR varies by approximately 5 dB with
azimuth for a constant range. Thus, the throughput possible per unit
power can be expected to vary by a factor of 3 or more. The location of
areas of high user density should be served by a Node B that is not only in
close proximity but, further, care should be taken with regard to the
azimuth of the antennas of each cell to minimise the out of cell
interference experienced in these areas.
12.6 Conclusions
Equations whereby the capacity of the downlink of a UMTS network can
be estimated for dimensioning purposes have been put forward. These
equations have been validated by comparing estimates with values
obtained using a Monte Carlo simulator. Estimates can be obtained for
cells where either all users are identical or, alternatively, the user
distribution is uniform throughout the network. In cases where the user
distribution is non-uniform, the estimates are likely to become less
accurate. An additional method that is more suitable for these situations
has been explained. This involves using information from a Monte Carlo
simulator in order to estimate the possible throughput when the traffic
channel power on the downlink is a maximum.
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Coverage versus Capacity
Further Analysis of the Downlink
• The concept of the “identical user”.
Identical:
•Bit Rate
•Eb/No
•Path loss
•Orthogonality
•Interference
Coverage versus Capacity
Further Analysis of the Downlink
• Power Received by each user:
PTcom
PN +
Puser
N-1
“other
users”
NPuser (1 − α ) PTcom (1 − α )
+
+ PR int
LL
LL
Bit Rate
Eb/No
Path loss
Orthogonality
PRint
P
+ NPuser
i
= Tcom
LL
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Coverage versus Capacity
Further Analysis of the Downlink
• Eb/No delivered to each user:
Eb
Puser
W
=
N 0 L ⎛ P + PTcom (1 − α ) + (N − 1)Puser (1 − α ) + P
⎞ R
R int ⎟
L⎜ N
LL
LL
⎝
⎠
Total Transmitted Power
=
NPuser + PTcom
Downlink Analysis
Capacity vs. Link Loss
α = 0.6; i = 0.6; Eb N 0 = 6 dB;
PTcom = 36 dBm; R = 12200 bit/s; PN = −102 dBm
Link Loss
(dB)
Tx Power for
25 users
(dBm)
Maximum
users for 43
dBm Tx
Power
110
37.62
64
125
37.69
64
140
39.33
49
145
41.63
33
150
45.26
16
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Downlink Analysis
Rapid, Approximate Method
• As Puser is allowed to approach infinity:
W
RN ≈
Eb
N0
(1 − α + i )
• The “Pole Capacity”.
Downlink Analysis
Rapid, Approximate Method
• Identical Users will experience identical noise rise.
25
20
15
10
5
0
0
0.2
0.4
0.6
0.8
1
1.2
• Noise rise can be converted to throughput.
• We can predict the noise rise for given circumstances.
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Downlink Analysis
Rapid, Approximate Method
We can predict the noise rise for given circumstances.
The maximum noise rise that can be produced is
PT max (1 − α + i ) + PN LL
PN LL + PTcom (1 − α + i )
Then, capacity is given by
(
PC 1 − 1
Noise Rise
) = E WN
b
PT max − PTcom
0 PT max (1 − α + i ) + PN LL
.
Downlink Analysis
Effect of Link Loss on Capacity
There is a maximum capacity at low levels of link loss.
High transmit power allows this capacity to be
approached at significant levels of link loss.
Capacity (kbit/s)
1200
1000
800
600
400
200
0
120
130
140
150
160
+43 dBm
+46 dBm
Link Loss (dB)
+37 dBm
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166
Downlink Analysis
Maximum Capacity
At negligible levels of link loss, the expression for noise
rise becomes
PT max
PTcom
And capacity can be estimated from
⎛
⎞
P
.⎜⎜1 − Tcom ⎟⎟ kbit/s
(1 − α + i ) ⎝ PT max ⎠
3840
Eb
N0
Downlink Analysis
Maximum Capacity
If
PT max
PTcom
is taken to be fixed at, for example, 5,
then capacity is given by
And maximum capacity can be estimated from
3072
Eb
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N0
(1 − α + i )
kbit/s
167
Downlink Analysis
Effect of Orthogonality
Graph shows the effect of orthogonality on the
downlink capacity for a link loss of 145 dB and i set at
0.6.
Capacity (kbit/s)
1200
1000
800
600
400
200
0
0
0.2
0.4
0.6
0.8
1
Orthogonality
BTS Power: 37 dBm
40 dBm
43 dBm
46 dBm
Downlink Analysis
Effect of OutOut-ofof-Cell Interference
Graph shows the effect of variations in the value of i on
the downlink capacity for a link loss of 145 dB and
Capacity (kbit/s)
orthogonality of 0.6.
1400
1200
1000
800
600
400
200
0
0
0.4
0.8
1.2
1.6
2
Out of Cell Interference
BTS Power: 37 dBm
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40 dBm
43 dBm
46 dBm
168
Downlink Analysis
Extending the Validity – The EvenlyEvenly-loaded Network
So far, “identical users” have been considered.
Consideration is now given to an evenly loaded
network.
Crucially, is there a
representative value
of link loss and out-ofcell interference that
can be used to
estimate downlink
capacity?
Downlink Analysis
Extending the Validity
Experimentation with Monte
Carlo simulation suggests
that:
The effective value of link loss
is 4 dB less than that to the
edge of the cell.
The effective out-of-cell
interference ratio is 0.85.
Max throughput =
2458
kbit/s
Eb N 0
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Downlink Analysis
Extending the ValidityValidity- An Example
Network of cells with link
loss to edge of 133 dB.
Maximum throughput on
downlink at Eb/No of 7 dB
is 460 kbit/s for 43 dBm
transmit power.
Note:
Pole Capacity = 613 kbit/s
If 20% of power is for
common channels then
Max throughput = 490 kbit/s
Downlink Analysis
UplinkUplink-Downlink Balance
Approximate Downlink Pole Capacity =
Approximate Uplink Pole Capacity =
2458
kbit/s
Eb N 0
2400
kbit/s
Eb N 0
Initial expectation is that loading factors will be higher
on the downlink.
Uplink Diversity and MHA will favour the uplink.
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Downlink Analysis
The UnevenlyUnevenly-loaded Network
The situation is complicated by the fact that different
users experience different levels of noise rise.
For example, consider the case where there are 24
voice users, split into two, equal groups.
• Link loss = 120 dB
• i = 0.3
• NR = 2.1 dB
• Link loss = 140 dB
• i = 1.0
• NR = 1.4 dB
Downlink Analysis
The UnevenlyUnevenly-loaded Network
For a more general
situation, the
maximum capacity is
often determined
using a Monte Carlo
simulator on a trial
and error basis.
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Downlink Analysis
The UnevenlyUnevenly-loaded Network
However, if the pole capacity is estimated from
3840
Eb
N0
(1 − α + i )
Then a single simulation result can be used to estimate
the maximum downlink capacity.
Reports from the simulation include downlink traffic
channel power and throughput.
Downlink Analysis
The UnevenlyUnevenly-loaded Network
As an example, it was found that a cell supported 300
kbit/s at an Eb/No value of 6 dB using 33.9 dBm of
traffic channel power.
Pole Capacity estimated at 772 kbit/s.
Hence representative noise rise estimated as 2.14 dB.
42 dBm of traffic channel power is available.
What noise rise (and hence throughput) would this
cause?
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Downlink Analysis
The UnevenlyUnevenly-loaded Network
If 33.9 dBm causes 2.14 dB of noise rise then 42 dBm
would cause 7.1 dB of noise rise.
Loading factor of 80%.
Resulting throughput of 622 kbit/s at an Eb/No value of 6
dB.
Tested with Monte Carlo simulation and found to be
valid for general situations where the distribution of the
new load was similar to the existing load.
Downlink Analysis
The UnevenlyUnevenly-loaded Network
For heavily concentrated “hot spot” situations. A static
analysis can result in an estimate for downlink values
of i.
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Downlink Analysis
Optimising Throughput – using Pilot SIR
The value of i influences
throughput. Any hotspots
should be located where i is
low. Examining the Pilot
SIR as part of a static
analysis when the network
is heavily loaded will
indicate the throughput
possible.
Downlink Analysis
Optimising Throughput – using Pilot SIR
If the pilot is at +33 dBm, the SIR
reported will be that for any traffic
channel with the same power.
This influences throughput.
E.g. SIR = -6 dB; target Eb/No = 4 dB
Maximum throughput for 33 dBm =
384 kbit/s.
192 kbit/s/watt (192 kbit/J).
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Downlink Analysis
Optimising Throughput – using Pilot SIR
Pilot SIR varies between -5
dB and -12 dB.
kbit/J parameter varies by a
factor of 5.
Re-directing antennas can
cause variation by a factor
of 3 or more.
Downlink Analysis
Conclusions
• Downlink capacity can be estimated for dimensioning
purposes.
• Estimates compared with Monte Carlo simulator
predictions.
• Estimates less accurate where network is not evenly
loaded. Simulations can lead to a more accurate
estimate.
• Site location and antenna azimuth have key role in
optimising downlink throughput.
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13 Masthead Amplifiers
13.1 Introduction
Antennas placed at Node Bs in a UMTS network will gather thermal noise
at a level of approximately -108 dBm over the bandwidth of a single
carrier. The actual level is affected by temperature, but only slightly. If
there is a lossy feeder between the antenna and the receiver, the signal
will be attenuated but the noise level will not reduce. This is because the
resistive elements of the feeder will generate noise that exactly
compensates for any attenuation. The result is that the SNR at the
receiver is worse than that at the antenna.
The MHA helps to overcome this by amplifying the signal before it is
attenuated. Naturally, the noise is also amplified (and the amplifier adds
its own contribution to the noise level) but, once this has happened the
effect of the noise added by the lossy feeder is less significant. The overall
result is an improvement in the signal to noise ratio delivered to the
receiver and, in turn, a better received Eb/N0. This section describes a
typical MHA and analyses the improvement that can be expected in its
performance.
Of crucial importance is the fact that a MHA will assist the uplink only
whilst placing additional loss in the downlink direction.
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13.2 MHA example
Diversity
Mast Head Amplifiers
•
Compensates for cable loss between antenna
and base station (typically 3dB)
•
MHA used to increase coverage range
•
Tx Characteristics
•
Specification Frequency Range 2110-2170 MHz
•
Insertion Loss <0.6 dB
•
Max Power Handling 52 dBm CW 62 dBm Peak
•
Rx Characteristics
•
Specification Frequency Range 1920-1980 MHz
•
Noise Figure (Typical) <1.4 dB
•
Gain Variation Over Frequency 12.0 ± 0.9 dB
•Amplificadores MHAs
•UMTS Masthead Amplifier
•UMTSMHA002a/100800
Mast Head Amplifiers
Mast Head Amplifiers MHA’s
• Used to reduce the Noise Figure of the Node B subsystem
• Improves the uplink link budget
• Allows for greater coverage
• Use of MHA assumes the cell is uplink limited
• Downlink limited cells will have their capacity reduced.
• Insertion loss of typically 0.5 dB
• By extending the range of the cell, users will on average need more
power from the Node B
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Mast Head Amplifiers
MHA Composite Noise Figure - Uplink
•
Noise Figure of the first component is the most important
•
Noise Figure is in dB, Noise Factor, F is a ratio ( minimum 1 )
•
Passive components take their loss as a Noise Figure
F = F1 +
(F2 − 1) + (F3 − 1) + (F4 − 1) + .....
G1
G1G2
G1G2 G3
Element
Uplink Gain
Noise Figure dB
MHA
2.0 to 12.0 dB
Feeder
Length dependent eg -2.0 dB ( F
= 0.63 )
Bias-T
-0.3 dB (F = 0.933)
Downlink
Loss
1.4
0.5 dB
2
2.0 dB
0.3 ( F = 1.037 )
0.3 dB
Node B
4 ( F = 2.511 )
Mast Head Amplifiers
MHA Composite Noise Figure - Uplink
•
Note that at small values of MHA gain and low feeder loss, the overall NF is slightly worse
Noise Figure v Feeder Loss
14.000
12.000
No MHA
MHA 1dB
MHA 2 dB
10.000
Noise Figure dB
MHA 3 dB
MHA 4 dB
8.000
MHA 5 dB
MHA 6 dB
MHA 7 dB
6.000
MHA 8 dB
MHA 9 dB
4.000
MHA 10 dB
MHA 11 dB
MHA 12 dB
2.000
0.000
1
1.6
2.2
2.8
3.4
4
4.6
5.2
5.8
6.4
7
7.6
Feeder Loss dB
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Mast Head Amplifiers
MHA Downlink Limited
•
Assuming the system is
downlink limited
60
58
56
•
The improved coverage
puts additional strain on
the power supply of the
Node B
Increase in the allowed
propagation loss will
reduce the capacity
54
52
50
Tx Power ( dBm )
•
48
46
145 dB
150 dB
44
155 dB
160 dB
42
40
38
36
34
32
74
72
70
68
66
64
62
60
58
56
54
52
50
48
46
44
42
40
38
36
34
30
32
Effect is less for higher bit
rate services due to the
smaller number of users
30
•
Number of Speech Users
Mast Head Amplifiers
MHA Matrix
•
Usefulness Matrix range -5 to 5
• Cost
•
Relatively cheap solution
• Eb/No no effect
• Inter-cell interference
•
Uplink increases i due to more uplink users at edge of cell
which requires maximum power
•
Downlink increases i due to more users, forces Node B
closer power saturation.
• Coverage Improvement
•
Uplink range improvement
•
Downlink may limited coverage due to overall lack of
power
• Capacity Improvement
•
Uplink improved brings in more users
•
Downlink may reduce due to power limitation
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14 Diversity Antennas
14.1 Introduction
Diversity is a well-established method of improving the quality of a
communication channel. It traditionally means employing more than one
receive antenna and then combining the signal (sometimes merely
selecting the one with the larger amplitude) so that the outcome is
superior to that which would be obtained without diversity. Combining
has usually taken place at RF. In UMTS networks receive diversity
actually employs multiple receivers allowing the signals to be combined
at base band. This gives an improvement in the value of Eb/N0 which, in
turn gives an improvement in both coverage and capacity.
Another innovative feature of UMTS networks is the ability to utilise
transmit diversity. This is not so effective as receive diversity but,
nevertheless, can provide Eb/N0 improvements of greater than 1 dB
(compared to 4 dB improvements possible for uplink diversity).
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14.2 Definition of Fading
Diversity
Fading
•
Electromagnetic signals will interact, causing addition and
subtraction of their field strengths
•
Fast fading signal strength changes are due to relative
motion and local scattering objects such as buildings,
foliage, etc. and change rapidly over short distances.
• Typically Multipath interference results from fast fading
• Fading of the signal follows a Rayleigh distribution
•
Slow fading is the change in the local mean signal strength
as larger distances are covered.
• Fading of the signal is a log-normal distribution
•
The resultant signal at the Node B and UE antenna will be
subject to rapid and deep fading
Diversity
Diversity
• Signals from multiple antennas (spatial diversity), can be used to
reduce the effects of fast fading and improve received signal
strength.
• Three common combining schemes used for Rayleigh fading
channels (Fast fading) are
• Selection diversity
•
chooses the strongest signal power,
• Equal gain
•
combines the co-phased signal voltages with equal weights,
• Maximal ratio combining
•
weights the co-phased signal voltages relative to their signal to
noise ratio.
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14.3 Receive Diversity
Diversity
Receive Diversity
•
Basic idea is that, if two or more independent samples of a signal
are taken, these samples fade in an uncorrelated manner.
• Each path can then be thought of as separate and worked on in isolation
•
Increases the signal to interference ratio, SIR
• Allows a system to reduce the target uplink Eb/No of a channel
• Saves UE & Node B Power
•
Standard configuration for WCDMA may be two-branch Rx diversity
• Using a single cross polar antenna or two vertically polarised ones.
• Separation of the vertically polarised antenna is typically a few
wavelengths
c 3 × 108
=
= 15cm
f 2 × 10 9
separation ⇒ 30 to 40cm
c = f ×λ ⇒ λ =
Diversity
Uplink Receive Space Diversity
•
Even if signal is highly correlated, coherent combination should yield
about 3 dB improvement.
•
In practice a gain of 4 dB or more is expected from antennas
•
Typical dimension 1.5m
Receive
antenna 2
Receive
antenna 1
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Diversity
Uplink Receive Space Diversity
•
This is not “conventional” space diversity.
•
Each antenna is connected to a separate finger of the Rake
receiver.
•
This is possible due to the synchronisation and channel estimation
derived from the Pilot bits on the DPCCH channel.
•
Eb/No is improved, rather than simply an effective power gain.
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14.4 Transmit Diversity
Diversity
Downlink Transmit Diversity
•
UMTS explicitly allows the use of transmit diversity from the base station
•
However it is not possible to simply transmit simultaneously from two close antennas as
this would cause an interference pattern
•
Mobile terminals must have the capability of implementing downlink transmit diversity .
Transmit
antenna 2
Transmit
antenna 1
Diversity
Downlink Transmit Diversity
•
UMTS FDD mode does not allow for an accurate measure of the
downlink channel using uplink estimations
•
The UE can measure the downlink channel and return estimates to
the Node B – closed loop
•
The alternative is coding the downlink to allow for the UE to correlate
the two signals – open loop
•
The P-CPICH is transmitted from each antenna differently
• Orthogonal signals
• Antenna 1 { 0,0,0,0,0,0,0,0,0, …… } normal operation
• Antenna 2 { 0,0,1,1,1,1,0,0,0,0,1,1,1,1,0,0,0,0,1,1,
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Diversity
Downlink Transmit Diversity
• The following methods are suggested in the UMTS
standards to avoid the problem of the interference
Transmit Diversity
Method
Open Loop TSTD
Description
Time Switched Transmit antenna
Diversity for SCH only
Space Time block coding Transmit
antenna Diversity
Different Orthogonal Pilots
CPICH + S-CPICH
Same Pilot
Open Loop STTD
Closed Loop Mode 1
Closed Loop Mode 2
Diversity
Time Switched Transmit Diversity (TSTD) for SCH
• Even numbered slots transmitted on Antenna 1, odd
numbered slots on Antenna 2
Slot #0
Slot #1
Slot #14
P-SCH
P-SCH
P-SCH
S-SCH
S-SCH
S-SCH
Antenna 1
Antenna 2
Slot #2
P-SCH
S-SCH
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Diversity
Space Time Transmit Diversity (STTD)
•
STTD encoding is optional in UTRAN. STTD
support is mandatory at the UE
r(t) = r1 = S1 ⋅ h1 + S2 ⋅ h2 + n1
•
Channel coding, rate matching and
interleaving is done as in the non-diversity
r(t +T) = r2 = −S2* ⋅ h1 + S1* ⋅ h2 + n2
mode.
Sˆ1 = hˆ1* ⋅ r1 + hˆ2 ⋅ r2*
•
STTD encoding is applied on blocks of 4
consecutive channel bits
•
Sˆ2 = hˆ2* ⋅ r1 − hˆ1 ⋅ r2*
h is the impulse channel response of each
antenna
Diversity
Analysis of STTD
Antenna 1
b0
b1
b2
b3
Antenna 2
-b2
b3
b0
-b1
b0-b2
b1+b3
b0+b2
b3-b1
Combination
Processing alternate bits will extract the data
•
STTD encoding effectively spreads a data bit across more than one bit period.
•
This leads to a general improvement in noise performance.
•
Further, it allows a stronger signal from one antenna to dominate.
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Diversity
Analysis of STTD
•
The Space-time combining generates symbols that are proportional to the
sum of the powers from both antennas
Diversity
Closed Loop Mode
• Channel coding, interleaving and spreading are done as
in non-diversity mode
• The spread complex valued signal is fed to both TX
antenna branches, and weighted with antenna specific
weight factors w1 and w2.
• The weight factors are determined by the UE, and
signalled using the FBI field of uplink DPCCH
(Dedicated Physical Control Channel).
Pilot
Npilot bits
DPCCH
TFCI
NTFCI bits
FBI
NFBI bits
TPC
NTPC bits
Tslot = 2560 chips, 10 bits
Slot #0
Slot #1
Slot #i
Slot #14
1 radio frame: Tf = 10 ms
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Diversity
Closed Loop Mode
w1
Spread/scramble
DPCCH
Ant1
CPICH1
Tx
∑
DPCH
Ant2
DPDCH
Tx
∑
w2
CPICH2
Rx
w1
w2
Weight Generation
Rx
Determine FBI message
from Uplink DPCCH
Diversity
Closed Loop Mode
• Closed Loop mode 1
• The phase of one antenna is adjusted relative to the other
• Using 1 bit accuracy per slot
• Feedback rate is 1500 Hz
• Closed Loop mode 2
• Relative phase adjusted using 3 bit accuracy
• Amplitude adjusted using 1 bit
• Feedback rate is 1500 Hz
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Diversity
Downlink Eb/No reduction
Diversity
Mode
Modified Vehicular A
3km/h……. …..50km/h
………………
…..120 km/h
Pedestrian A
…… 3km/h
Open Loop
1.0 dB
0.5 dB
0.5 dB
3.0 dB
Closed Loop 1
1.5 dB
1.0 dB
0.0 dB
3.5 dB
Source Radio Network Planning and Optimisation for UMTS, Jaana Laiho et al
•
Slower speeds and lower multipath interference produce the best results
Diversity
Transmit Diversity - Conclusions
• Depends on UE performance
• Estimate of channel impulse and SIR
• Main benefit is reduction in downlink Eb/No
• No advantage in problematic time and multipath environments
• 50km/h -- Eb/No only 0.5dB better in open-loop mode
• 120km/h -- Eb/No no real improvement
• Microcell’s will benefit from TxDiversity
• Beam forming problems associated with location
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Diversity
Downlink Transmit Diversity Matrix – Open Loop
Cost (-2)
Uplink
Downlink
Eb/No
0dB
3dB
Inter-cell Interference
0
0
Capacity
0
2
Coverage
0
2
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14.5 Multi-User Detection MUD
One major advantage that the downlink has in a UMTS network is the use
of orthogonal codes to reduce the interference effect of other traffic and
control channels. This relies on the fact that the downlink channels can be
easily synchronised as they originate from the same point. The same sort
of cancellation is not possible on the uplink as the transmission delay is
different for each user. MUD helps to provide some interference
cancellation by performing an inverse transform on the message
contained in interfering channels and then removing that from the input
of the wanted signal. It is a highly sophisticated method and its potential
is yet to be fully realised. However, a 1 dB improvement in uplink
performance can be recorded (which can lead to useful coverage and
capacity increases). Note that MUD is only effective at a serving cell, the
interference effect on neighbouring cells is not reduced.
Diversity
Multi-User Detection
• Multi-User detection (MUD) is a method used to improve the
performance of the receiver by reducing the noise
contributions from other CDMA users.
• The concept is based on the fact that noise from CDMA users,
although usually approximated with AWGN characteristics,
inherently consists of coherent signals.
• MUD reception decodes a number of users simultaneously
and subtracts their noise contributions from the others
• Essentially this results in a more sensitive receiver
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Diversity
Multi-User Detection
•
Mid 1980s research showed that joint, optimal, maximum-likelihood decoding of
all users out performed matched filter alternatives.
•
The problem was the exponential increase in processing as the number of
simultaneous users went up. ( Viterbi trellis techniques )
•
Current research interests
• Suboptimal linear receivers
• Data-aided minimum mean squared (MMSE) linear receivers
• Blind ( nondata-aided ) MMSE receiver
• Non-linear multiuser detection
• Multistage interference cancellation, parallel and serial, PIC & SIC
Diversity
Multi-User Detection
•
Viterbi decoding uses past symbol knowledge to weight present
and future choices
•
Multiuser decoding has the added complexity of having present
‘other user’ interfering symbols
•
Therefore some decision as to the interfering symbols must be
made
•
Due to the complexity, multiuser detection is more likely to exist
in the Node B
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Diversity
Multi-User Detection
•
Multiuser detection reduces the need for tight power control
•
Power control is still important to the performance of the MUD
system
•
Best performance used with short spreading codes, repeating
every symbol. ( Downlink )
•
Can be used with long spreading codes, pseudorandom
sequences which are much longer than the symbol duration.
(Uplink)
Diversity
Visualising the Processing Gain w/o MUD
W/Hz
W/Hz
W/Hz
Ec
Before
Spreading
After
Spreading
f
Io
With Noise
f
W/Hz
f
Eb
W/Hz
After
Despreading
/Correlation
f
Signal
Intra-cell Noise
Inter-cell Noise
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Post
Filtering
(No MUD)
No
f
dBW/Hz
Eb
Eb/No
No
f
194
Diversity
Visualising the Processing Gain with MUD
Post
Filtering
W/Hz
After
Despreading
/Correlation
W/Hz
No
f
Other Users
Eb
No
f
W/Hz
Signal
W/Hz
Eb
f
W/Hz
Eb
No
Eb
No
f
f
Inter-cell Noise
Because of MUD the contribution of the other users to the
Noise is Reduced.
It is not completely eliminated because of the inaccuracies of
the Multiple access interference estimation.
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14.6 Predicting the Effect of Different Coverage
and Capacity Enhancement Devices
It is clear that adding certain devices, such as mast head amplifiers or
diversity receivers will improve network performance. However, we
need to be able to quantify any likely improvement in order to undertake
a cost-benefit analysis. As a starting point we shall consider an isolated
cell that is serving voice users delivering a bit rate of 12200 bps at an
Eb/N0 of 4 dB on the uplink and the downlink. With an uplink Noise Rise
of 3 dB the cell can accommodate a link loss of 133 dB.
This information alone is sufficient to suggest that the pole capacity is
1530 kbps on the uplink and 3822 kbps on the downlink (assuming an
orthogonality value of 0.6). An uplink Noise Rise of 3 dB would suggest
that 63 voice users are seen as a full load for the cell. The loading factor
on the downlink would be estimated to be only 20% suggesting a Noise
Rise figure of 1 dB. If 36 dBm of common channel and pilot power is
transmitted, the effect at the mobile receiver would be that of a -94 dBm
interference power if the mobiles are at a path loss of 126 dB. If the noise
floor of the receiver is -101 dBm then the overall “noise plus interference”
level would be -93.2 dBm. If a Noise Rise of 1 dB must be produced, then
an effective traffic channel power of -99.2 dBm (actual receive power -95.2
dBm) must be received. This would necessitate a transmit power of 30.8
dBm if all users were at a path loss 7 dB less than the cell edge (which is
defined by a link loss of 133 dB).
Quick check downlink analysis. 30.8 dBm corresponds to 12.8 dBm per
user (if there are 63 users). Received power per user is -113.2 dBm.
Effective Noise Power is -92.2 dBm (given a NR of 1 dB). Thus wideband
SNR is -21.0 dB. Processing gain of 25 dB will restore the required Eb/N0
value of 4 dB.
Having carried out and understood the mechanism of this calculation it is
possible to predict the effect of capacity enhancement devices such as
uplink diversity. When considering whether or not to use such devices it
is important that their purpose is made clear. For example, is maximising
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capacity or maximising coverage range our goal (or is it a combination of
the two aims)? Additionally, the affect on the downlink must be assessed.
Consider, as an example, the effect of implementing uplink diversity on
this cell. The effect is to reduce the target Eb/N0 value by 3 dB. If
maximising capacity (whilst keeping the coverage range fixed) is taken to
be our goal then it is possible to increase the NR limit by 3 dB to 6 dB and
then note that the pole capacity on the uplink has doubled to 3060 kbps.
The loading factor of 75% means that a throughput of 2290 kbps is
possible, equivalent to 188 voice users. This represents a dramatic
increase on the previous value of 62 users. However, there has been no
help offered on the downlink. The pole capacity in this direction remains
unchanged at 3822 kbps. Thus a loading factor of 60% will be imposed
causing a Noise Rise of 4 dB. The effective Traffic Channel Power
required to cause this Noise Rise will be -91.5 dBm, an actual received
power of -87.5 dBm. The total traffic channel transmit power would have
to be 38.5 dBm (15.8 dBm per user). This is a significant increase over the
previous value of 30.8 dBm. Notice that the amount of power required by
each user has increased significantly.
Alternatively, if may be that uplink diversity has been introduced with
the goal of increasing the range of the cell keeping its capacity constant. If
that is the case the new pole capacity of 3060 kbps can be used to calculate
a reduced loading factor of 25%, which represents a noise rise of 1.2 dB.
Thus the cell coverage range can be increased by 4.8 dB. Thus a typical
user can be thought of as having a path loss of 131.8 dB to the cell. The
result of this is that the interference effect of the pilot and common
channels is reduced. However, the fact that users are at a greater distance
means that the power requirements will be greater, although not 4 dB
greater. Calculations show that the Traffic Channel power requirement
will rise from the initial value of 30.8 dBm to 32.0 dBm.
It is possible to use similar techniques to predict the effect of using mast
head amplifiers and of implementing downlink diversity.
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Diversity
Predicting the Effects
• It is important to be able to
predict the coverage and
capacity effects of
introducing a feature such as
uplink diversity into a cell.
• Common Channel and Pilot
Power taken to be 33 dBm
each (total 36 dBm).
• As a starting point we will
consider an isolated cell that
is serving voice users
delivering a bitrate of 12200
bps in both directions at an
Eb/No of 4 dB.
• We shall assume that the
orthogonality factor is 0.6.
• Maximum link loss is taken to
be 133 dB with the “average
user” on the downlink having
a link loss of 126 dB.
• Mobile noise floor is -101
dBm.
Diversity
Pole Capacity Calculations
• In the uplink the pole
capacity is
3840
= 1530
100.4
kbps
• In the downlink the pole
capacity is
3840
= 3822 kbps
10 (1 − 0.6)
0 .4
• Initial loading condition is
taken as 63 voice users
producing a NR of 3 dB.
Throughput approx 785
kbps.
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Diversity
Downlink Calculations
• Noise Floor of Mobile is -101 dBm
• Common and Pilot Channels
received at a level of 36 – 126 = -90
dBm.
• Orthogonality reduces this by 4 dB
(10log[1-0.6]=-4). Thus equivalent
is -94 dBm.
Noise plus interference
= -93.2 dBm
• -94 dBm + (-101 dBm) = -93.2 dBm
• The pole capacity of the DL has
been calculated as 3822 kbps.
Throughput of 785 kbps would be a
loading factor of 20% and a NR of 1
dB.
• Traffic channel power has to
produce this Noise Rise.
Diversity
Downlink Calculations
• Noise plus interference plus traffic
channel power must be -92.2 dBm.
• Effective traffic channel power must
be -92.2 dBm – (-93.2 dBm)=-99.1
dBm.
• But traffic channel power will benefit
from orthogonality. Actual received
traffic channel power must be -95.1
dBm.
Required transmit
traffic channel power =
30.9 dBm.
Noise plus interference
plus traffic channel
power = -92.2 dBm
• Transmitted traffic channel power
must total -95.1+126=30.9 dBm
• Confidence check: 63 users: 12.8
dBm per user: Rx power per user is
-113.2 dBm. Noise plus
interference = -92.2 dBm. SNR = 21 dB. Processing Gain = 25 dB.
Eb/No = 4 dB as required.
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Actual received traffic
channel power = -95.1
dBm
199
Diversity
Introducing UL Diversity
• Now we will introduce UL diversity
and prioritise capacity, keeping the
range the same.
• UL Eb/No improvement assumed to
be 3 dB.
Required TCH power =
38.5 dBm.
Capacity on UL is
trebled.
• Pole capacity on UL is now 3060
kbps; on DL it remains at 3822 kbps.
• NR limit can be increased on UL
from 3 dB to 6 dB. Throughput on
UL increased to 2290 kbps (188
voice users).
• Loading factor on DL is now 60%: a
NR of 4 dB.
• Effective Traffic Channel power is
now required to be -89.2 dBm –
(-93.2 dBm)=-91.5 dBm.
• Actual Traffic Channel Power
Received = -87.5 dBm.
Actual received traffic
channel power = -87.5
dBm
• Required Traffic Channel transmit
power = 38.5 dBm (15.8 dBm per
user)
Diversity
Introducing UL Diversity
• Now we will introduce UL diversity
and prioritise range increase,
keeping the capacity the same.
• UL Eb/No improvement assumed to
be 3 dB.
UL path loss increased
by 4.8 dB.
• Pole capacity on UL is now 3060
kbps; on DL it remains at 3822 kbps.
• UL loading factor is now 25%
• NR limit can be reduced on UL from
3 dB to 1.2 dB.
• Path loss can be increased by 4.8
dB so typical user now has link loss
of 130.8 dB.
• DL interference from pilot and
common channel = -98.7 dBm
• Adding thermal noise gives -98.7
dBm + (-101 dBm) =-96.7 dBm
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Diversity
Introducing UL Diversity
• To give 1 dB NR on downlink, the
Effective TCH power must be -95.7
dBm –(-96.7 dBm) = -102.7 dBm.
Required TCH power =
32.0 dBm.
UL path loss increased
by 4.8 dB.
• Actual Received TCH power must be
-98.7 dBm.
• Required Transmit TCH power must
be 32 dBm.
• Note: this has risen from 30.9 dBm.
The 1.1 dB rise in power is less than
the 4.8 dB rise in path loss due to
the fact that the majority of “noise
plus interference” at the mobile is
pilot and common channel power
from the cell.
Actual received traffic
channel power = -98.7
dBm
• One conclusion is that it is the
loading that most influences
requirements on the downlink power
level.
Diversity
Introducing MHA
•
Now we will now consider the effect
of introducing a MHA and prioritising
capacity, keeping the range the
same.
•
The Noise Performance improvement
is assumed to be 2 dB.
•
Pole capacity on UL remains
unchanged at 1530 kbps.
•
NR limit can be increased on UL from
3 dB to 5 dB. Throughput on UL
increased to 1045 kbps (86 voice
users).
•
Loading factor on DL is now 27%: a
NR of 1.4 dB.
•
Effective Traffic Channel power is
now required to be -91.8 dBm –
(-93.2 dBm)=-97.4 dBm.
•
Actual Traffic Channel Power
Received = -93.4 dBm.
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Required TCH power =
32.6 dBm.
UL NR increased by 2
dB.
Capacity increased by
37%
•
Required Traffic Channel transmit
power = 32.6 dBm (13.3 dBm per
user)
201
Diversity
Introducing MHA – prioritise coverage
•
Now we will now consider the effect
of introducing a MHA and prioritising
coverage, keeping the capacity the
same.
•
The Noise Performance improvement
is assumed to be 2 dB.
•
Pole capacity on UL remains
unchanged at 1530 kbps.
•
NR limit is unchanged: maximum link
loss now increased by 2 dB to 135
dB.
•
Loading factor on DL is unchanged.
•
Effective Traffic Channel power is
now required to be -93.8 dBm –
(-94.8 dBm)=-100.7 dBm.
•
Actual Traffic Channel Power
Received = -96.7 dBm.
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Required TCH power =
31.3 dBm.
Max PL increased by 2
dB
Capacity stays the
same
•
Required Traffic Channel transmit
power = 31.3 dBm (13.3 dBm per
user)
202
15 Smart Antennas
15.1 Introduction
The ability to provide many separate but connected antennas, leads to the
technique of smart antennas. Cost and Physical size are problematic and
due to canyon effects cannot be used at street level.
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Diversity
High-order Receive Diversity
•
WCDMA signals have a high delay spread
• Potentially large gains from multipath diversity
•
Uplink performance benefits from higher-order receive diversity
•
Downlink performance improvement is limited due to the UE
• Limited processing power
• Limited number of fingers on the RAKE receiver
•
Using Maximal Ratio Combining, MRC
• Here all the incoming signals from all the M branches are weighted according to
their individual signal to noise ratios and then summed.
• All the individual signals must be co-phased before being summed.
• This requires individual receiver circuitry and phasing circuit for each antenna
element.
Diversity
Smart Antennas
•
Objectives
• To maximise signal to interference ratio, SIR
• Providing beam steerage allowing for a choice of desired
direction
• Reduction in side lobes due to beam forming techniques
•
Assumptions
• Time delays can be approximated by phase shifts
• The signal arrives at the antenna equally. Independent
of dimension of antenna
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Diversity
Smart Antennas
•
Intelligence of the Smart Antenna is in its signal processing
•
The level of intelligence can be defined
• Switched Beam
•Based on best signal power
•Easy to implement
•Limited gain
• Dynamically Phased Array
•Includes Direction of Arrival DoA
•Received power is maximised
• Adaptive Array
•The DoA of interferes is determined
•Allowing for nulls to be introduced
Diversity
Smart Antennas - Uplink
Interfering
Connection
Desired
Connection
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•
By using a narrower
beam the signal to
interference ratio of
the beam forming
antenna is reduced in
comparison with a
normal sectorised
antenna
•
Active nulls can be
generated, reducing
the interference from
other users
205
Diversity
Smart Antennas - Uplink
•
By combining the uplink
received signal in all beams
with appropriate weighting,
the uplink performance can
be improved.
Beam 2
w1 Signal from
Beam 1
x
MRC
Combiner
a
1
x
Beam 1
a
2
w2 Signal from
Beam 2
Diversity
Smart Antenna Gain – 16 beam
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Diversity
Uplink Eb/No reduction
Antenna
Configuration
Modified Vehicular A
3km/h……. …..50km/h
………………
…..120 km/h
Pedestrian A
…… 3km/h
4 MRC
3.0 dB
2.5 dB
2.3 dB
5.9 dB
8 beams
4.9 dB
5.2 dB
5.1 dB
5.9 dB
4 + 4 array
5.5 dB
5.7 dB
5.9 dB
7.0 dB
Source Radio Network Planning and Optimisation for UMTS, Jaana Laiho et al
•
Gain is relatively insensitive to direction of arrival, DoA
•
Slower speeds and lower multipath interference produce the best results
Diversity
Smart Antennas - Downlink
•
Beam forming techniques provides spatial filtering
• Transmit power can be reduced by the gain of the antenna
• Reduces interference between users
•
Multiple users are each assigned a secondary pilot S-CPICH to
provide a reliable phase reference
•
Requires the UE to estimate channel impulse response and SIR
accurately.
• Similar to transmit diversity STTD
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Diversity
Downlink Eb/No reduction
Antenna Configuration
Angular spread 10o
2 beam
2.1 dB
4 beam
4.5 dB
8 beam
7.0 dB
Source Radio Network Planning and Optimisation for UMTS, Jaana Laiho et al
•
Gain is sensitive to spread of UEs
Diversity
Why Smart Antennas
• Advantages
• Higher capacity per site – increase in revenue
• Higher QoS due to reduced interference
•
Disadvantages
• Cost
• Physical size
• Site Sharing
• Maintenance Overheads
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Diversity
Planning Smart Antennas
• Positioning of Adaptive Antennas
• Road side
•Need to be further away from road to allow beam forming
• Below rooftop
•Reduced performance due to canyon effect
• New radio models for angular/directional antennas
• Macro cells rather than Micro cells
Diversity
Smart Antenna – Capacity & Coverage
• Simplified Conclusions
• Improves uplink capacity proportional to the number of
antennas in the array, N
• Improves uplink coverage proportional to N2/gamma, gamma is
the path loss exponent
• Either improves downlink capacity proportional to N, if Node B
power is kept the same
• Or improves downlink coverage proportional to N1/gamma, if
Node B power is kept the same
• Improves downlink capacity proportional to N, and
simultaneously increases coverage proportional to N1/gamma, if
Node B power is also increased by a factor N.
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Diversity
Smart Antenna v 2 branch Receive Diversity
•
Capacity Gain
• Assuming a load factor in the uplink is 30% then higher order receive
diversity performs better than 2 branch receive diversity.
•
Higher Uplink loading
• Loading factor increase 30% to 50%
• Cell rapidly reaches downlink limited
• Capacity gain is reduced
•
Equal Gains in coverage
• Higher order receive diversity is better than MHAs
• No downlink insertion loss
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16 Practical Simulation
16.1 Exercise using MHA’s
Case Study - Advanced
Case Study - MHA
• Network Cluster of 7 sites, large region
putting pressure on coverage
• 3 sector sites
• Standard voice users
• Site A
• Uplink limited
• Noise Rise not pressured
• Node B power plenty
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16.1.1
Network with no MHA’s
Uplink Eb/No failures denote high pathloss for UE’s.
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16.1.2
Insert MHA at centre of network
Defined central area.
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16.1.3
All sites with MHA’s
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16.2 Downlink Limited case – MHA’s
16.2.1
Downlink limited case for network without MHA’s
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16.2.2
MHA applied to all sites
No solution for this type of problem
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16.3 Transmit Diversity
16.3.1
Voice Traffic – NO Tx diversity
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16.3.2
64kbps Service – NO Tx diversity
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16.3.3
Tx Diversity Voice Service
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16.3.4
Tx Diversity 64kbps Service
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16.3.5
Tx and Rx Diversity Applied – Voice Service
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16.3.6
Tx and Rx Diversity Applied to 64kbps Service
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17 Measuring Success
17.1 Customer Focus
KPI
Customer Focus
• Residential Customer
• Important to get the message delivered
• Always on Internet
• Simplicity of use of application
• Business Customer
• Detailed service level agreements, SLA’s
• Availability or coverage defined
• Customisation of interface
• Customer mix/clutter will become highly diversified
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KPI
Customer Experience Gap
• The customer experience gap is the difference between
what the customer wanted and what they got.
• There is a semantic disparity between what is good for the
service provider and what is good for the customer.
• The problem is:
• Parameters that are easy for networks to measure do not
translate well into parameters that are understood by the
customer
• Parameters that are readily understood by the customer are
not easy for the network specialist to measure.
17.2 Key Quality Indicators KQI’s
KPI
Key Quality Indicators – KQI’s
• KQI’s provide a measurement of a specific aspect of performance
• The KQI measurement draws on
• Key Performance Indicators KPI’s
• KQI’s provide for an end-to-end service measurement
• Reasons for end-to-end
• Retain high value customers
• Regulation requires a measure on quality ( end-to-end )
• Service levels are being set by regulators
• Introduction of value added services, require these 3rd party vendors to
be monitored.
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KPI
Key Quality Indicators – KQI’s
• KQI’s can be divided into 2 types
• Service KQI’s
• Product KQI’s
• Network Elements provide network performance data
• This data is collected to form KPI’s
• The KPI’s are used to produce Service KQIs
• Service KQIs are used as primary input for internal/partner SLAs
• Service KQIs provide the main source of data for Product KQIs
• Product KQIs support the contractual SLAs with the customer
17.3 Key Performance Indicators KPI’s
KPI
Key Performance Indicators – KPI’s
•
KPI’s are calculated from active measurements
•
3GPP standards define the UE and UTRAN measurements taken
•
KPI’s will gather these measurements and calculate an average value
• Average Uplink Load
Average Uplink Load =
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∑ Ptx
∑ RSSI
225
17.3.1
Exercise 17.3
Prove the formula for Average Uplink Load using loading factor and Noise Rise.
17.4 Measurements
KPI
Measurements
•
The UTRAN may control a measurement in the UE either
•
•
•
By broadcast of SYSTEM INFORMATION
And/or by transmitting a MEASUREMENT CONTROL message.
The following information is used to control the UE measurements
•
Measurement identity: A reference number that should be used by
the UTRAN when setting up, modifying or releasing the measurement
and by the UE in the measurement report.
•
Measurement command: 1 of 3 different measurement commands.
•
Setup: Setup a new measurement.
•
Modify: Modify a previously defined measurement, e.g. to
change the reporting criteria.
•
Release: Stop a measurement and clear all information in the
UE that are related to that measurement.
•
Measurement type
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KPI
Measurement Type
•
Intra-frequency measurements
•
•
Inter-frequency measurements
•
•
downlink quality parameters, e.g. downlink transport block error rate.
A measurement object corresponds to one transport channel in the case of BLER.
UE-internal measurements
•
•
•
uplink traffic volume.
Quality measurements
•
•
•
downlink physical channels belonging to another radio access technology e.g. GSM.
Traffic volume measurements
•
•
downlink physical channels at frequencies that differ from the frequency of the active
set and on downlink physical channels in the active set.
Inter-RAT measurements
•
•
downlink physical channels at the same frequency as the active set.
UE transmission power and UE received signal level.
UE positioning measurements
A measurement object corresponds to one cell.
KPI
Measurement Control Messages
•
Within the measurement reporting criteria field in the
Measurement Control message the UTRAN notifies the UE which
events should trigger a measurement report.
•
The listed events are the toolbox from which the UTRAN
•
•
•
the reporting events are needed for handover evaluation function,
or other radio network functions.
The measurement quantities are measured on the monitored
primary common pilot channels (CPICH) of the cell defined in the
measurement object.
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KPI
Reporting event 1A: A Primary CPICH enters the reporting range
• When an intra-frequency measurement configuring event
1a is set up, the UE shall:
•
create a variable TRIGGERED_1A_EVENT related to that
measurement, which shall initially be empty;
•
delete this variable when the measurement is released.
KPI
Reporting event 1A: A Primary CPICH enters the reporting range
•
When event 1A is configured in the UE, the UE shall:
• if "Measurement quantity" is "pathloss" and Equation 1 is fulfilled for
one or more primary CPICHs, or if "Measurement quantity" is "CPICH
Ec/No" or "CPICH RSCP", and Equation 2 is fulfilled for one or more
primary CPICHs, for each of these primary CPICHs:
•
if all required reporting quantities are available for that cell; and
•
if the equations have been fulfilled for a time period indicated by "Time
to trigger", and if that primary CPICH is part of cells allowed to trigger
the event according to "Triggering condition 2", and if that primary
CPICH is not included in the "cells triggered" in the variable
TRIGGERED_1A_EVENT:
– include that primary CPICH in the "cells recently triggered" in the variable
TRIGGERED_1A_EVENT.
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KPI
Reporting event 1A: Equation 1
• MNew is the measurement result of the cell entering the reporting range.
• CIONew is the individual cell offset for the cell entering the reporting range if an individual cell
offset is stored for that cell. Otherwise it is equal to 0.
• Mi is a measurement result of a cell not forbidden to affect reporting range in the active set.
• NA is the number of cells not forbidden to affect reporting range in the current active set.
3GPP TS 25.331 version 4.10.0 Release 4 page 838
KPI
Reporting event 1A: Equation 1
• For pathloss
• MBest is the measurement result of the cell
• For other measurements quantities.
• W is a parameter sent from UTRAN to UE.
• R1a is the reporting range constant.
• H1a is the hysteresis parameter for the event 1a.
• If the measurement results are pathloss or CPICH Ec/No then MNew, Mi and
MBest are expressed as ratios.
• If the measurement result is CPICH-RSCP then MNew, Mi and MBest are
expressed in mW.
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KPI
UE Measurements
•
The reference point for these measurements is at the antenna connector of
the UE
•
Antenna Gain
•
Body Loss
•
CPICH RSCP ( Received Signal Code Power ) = -114 dBm
•
PCCPCH RSCP ( handover to TDD only )
•
UTRA carrier RSSI ( Received Signal Strength Indicator )
•
•
GSM carrier RSSI
•
•
Reporting range -100 to -25 dBm
Range as specified in TS 45.008, RXLEV at -70dBm
CPICH Ec/Io
•
Reporting range -24 to 0 dB
3GPP TS 25.133 version 4.9.0 Release 4 page 56-81
KPI
Calculated DL Pathloss
•
Pathloss in dB = Primary CPICH Tx power - CPICH RSCP.
•
•
•
Primary CPICH Tx power the unit is dBm.
CPICH RSCP the unit is dBm.
If necessary Pathloss shall be rounded up to the next higher integer.
•
•
Results higher than 158 shall be reported as 158.
Results lower than 46 shall be reported as 46.
Source TS 25.331 section 14.1
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KPI
UE Measurements
•
Transport Channel BLER
•
•
Estimate of the transport channel block error rate.
•
CRC checking
•
Estimated over time – range 0 to 1
Synchronisation
•
•
SFN-CFN observed time difference, range 0 to 9830400 chip
•
SFN-SFN observed time difference, range 0 to 9830400 chip
•
UE Rx-Tx time difference, range 768 to 1280 chip
UE Transmitted Power ( Total on one carrier )
•
Range -50 to +33 dBm
KPI
UE Transmitted Power Test
•
Example of test procedure specified in
•
TS 25.133 version 4.9.0 Release 4 page 138
Parameter
Value
DCH parameters
DL Reference Measurement - Channel 12.2 kbps
Power Control
On
Target quality value on DTCH BLER
0.01
Parameter
Cell 1
CPICH_Ec/Ior
-10 dB
PCCPCH_Ec/Ior
-12 dB
SCH_Ec/Ior
-12 dB
PICH_Ec/Ior
-15 dB
DPCH_Ec/Ior Note1
OCNS other cell noise source Note 2
Ior/Ioc
0 dB
Ioc
-70 dBm/3.84MHz
CPICH_Ec/Io
-13 dB
Propagation Condition
AWGN
Note 1: The DPCH level is controlled by the power control loop
Note 2: The power of the OCNS channel that is added shall make the total
power from the cell to be equal to Ior
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KPI
UE Transmitted Power Test
•
Set the UE power and Maximum allowed UL TX power to
the maximum power for that UE power class.
•
Send continuously during the entire test Up power control
commands to the UE.
•
Measure the output power of the UE. The output power
shall be averaged over the transmit one timeslot.
•
Check that the reported UE transmitted power is within the
specified range.
•
Decrease the Maximum allowed UL TX power with 1 dB
and signal the new value to the UE.
•
Repeat from step 3) until the entire specified range for the
UE transmitted power measurement has been tested,
•
the accuracy requirement for the UE transmitted power
measurement is specified 10dB below the maximum power
for the UE power class.
KPI
UTRAN Measurements
•
Received total wide band power
•
•
•
•
If receive diversity is being used then take the average of the power
Measurement period 100ms
Range is -112dBm to -50dBm
Signal to Interference Ratio SIR
•
•
•
•
•
•
•
Measured on a DPCCH – Dedicated Physical Control Channel
(RSCP / ISCP) x SF
RSCP - Received Signal Code Power (of one code)
ISCP - Interference Signal Code Power
SF – Spreading Factor 256
Measurement period 80ms
Range -11 to 20 dB
Source TS 25.133
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KPI
UTRAN Measurements
•
Signal to Interference Ratio SIR
•
•
•
•
•
•
•
Measured on a DPCCH – Dedicated Physical Control Channel
(RSCP / ISCP) x SF
RSCP - Received Signal Code Power (of one code)
ISCP - Interference Signal Code Power
SF – Spreading Factor 256
Measurement period 80ms
Range -11 to 20 dB
Reported value
Measured
quantity value
UTRAN_SIR_00
SIR < -11.0 dB
UTRAN_SIR_01
-11.0 = SIR < -10.5 dB
UTRAN_SIR_02
-10.5=SIR < -10.0 dB
…….
UTRAN_SIR_61
19.0 =SIR < 19.5 dB
UTRAN_SIR_62
19.5 = SIR < 20.0 dB
UTRAN_SIR_63
20.0 = SIR dB
KPI
UTRAN Measurements
•
SIRerror = SIR – SIRtarget
•
•
•
Measurement period 80ms
Accuracy ±3dB
Range -31 to 31 dB
Reported value
Measured quantity value
UTRAN_SIR_ERROR_000
SIRerror < -31.0 dB
UTRAN_SIR_ERROR_001
-31.0 = SIRerror < -30.5 dB
UTRAN_SIR_ERROR_002
-30.5 = SIRerror < -30.0 dB
………
UTRAN_SIR_ERROR_062
-0.5 = SIRerror < 0.0 dB
UTRAN_SIR_ERROR_063
0.0 = SIRerror < 0.5 dB
………
UTRAN_SIR_ERROR_123
30.0 = SIRerror < 30.5 dB
UTRAN_SIR_ERROR_124
30.5 = SIRerror < 31.0 dB
UTRAN_SIR_ERROR_125
31.0 = SIRerror dB
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KPI
UTRAN Measurements
•
Transmitted carrier power
•
Ratio of total transmitted power on one DL carrier to the maximum possible
power of this DL carrier, range 0 to 100%
•
•
Measurement period 100ms
Transmitted code power
•
Measurement of the DPCCH field of any dedicated radio link
•
Measurement period 100ms
•
Range -10 to 46 dBm
•
Reflects the power on the pilot bits of the DPCCH field
•
Transmitted channel BER – range 0 to 1
•
Physical channel BER – range 0 to 1
KPI
UTRAN Measurements
•
•
SFN-SFN observed time difference – Synchronisation
•
Measurement period 100 ms
•
Range -19200 to 19200 chip
Round trip time
•
RTT = Trx – Ttx
•
Trx – time of reception of DPCCH/DPDCH from UE
•
Ttx – time of transmission of DL DPCH to a UE
•
Measurement period 100ms
•
Range 876.0000 to 2923.8750 chip
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KPI
UTRAN Measurements
•
PRACH/PCPCH Propagation delay
•
One-way propagation delay of either PRACH or PCPCH
•
Prop Delay = (Trx- Ttx – 2560)/2
•
Trx – time when PRACH message from UE arrives, after
AICH arrives
•
Ttx – time when AICH is transmitted
•
2560 length of AICH
•
Divide by 2 gives one-way propagation
•
Only RACH messages with correct CRC will be considered
•
Range 0 to 765 chip
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18 Drive Test Measurements
18.1 The concept of Drive Testing
Drive Test Measurement
Drive Test
• Pre-construction phase
• Primary use of drive testing is to validate a propagation model
• Post-construction
• Test for coverage
• Measure Pilot strength
• Inter-cell Interference – i
• Number of soft handover channels ( active set size )
• Effective loading of cells
•
Big problem
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Drive Test Measurement
Drive Test Equipment
•
Some equipment suppliers
• Anritsu
•
http://www.eu.anritsu.com
•Portability and ease of setup prove to be the
strongest points of the Anritsu scanner.
•The Anritsu scanner was very simple to set up
•The information collected, although limited to
RSCP, Ec/Io and SIR measurements for up to 32
received scrambling codes.
•The receiver sensitivity was found to be better
than that of the Agilent scanner- measuring RSCP
signal levels as low as -122dBm.
Drive Test Measurement
Drive Test Equipmen
Equipment
•
Some equipment suppliers
• Agilent
•
http://we.home.agilent.com/
•The extensive amount of output information
•Although more complicated in terms of setup
•Agilent scanner provides the user with more
measured information and additional graphical
functionality.
•A strong solution but has limited sensitivity and
is not hand portable.
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Drive Test Measurement
Drive Test Planning
•
Pre-planning of drive test routes
• Knowledge of network
•Site location
•Site configuration
• Knowledge of location
•Towns
•Terrain
• Operator known issues
•GSM problem areas
18.2 Test mobile Measurements
Pre-planning of drive test routes is essential prior to any active testing.
Local knowledge of the environment, with problem areas highlighted will
produce better results. Take notice of terrain, and population density ie
towns. Consult previous work maybe for GSM drive tests, and pick out
relevant areas.
Drive tests will have to be repeated at different times of day and days of
the week if accurate impressions of the traffic and radio characteristics are
to be gained. You may also need to repeat drive tests if building work is
on-going and seasonal variations in traffic is expected. For example
tourists and special events will change how the network is loaded.
3g – UMTS/CDMA is a multi-application platform and as such varying
demands are placed on the network when different applications are used.
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Drive Test Measurement
Test-mobile Measurements
•
A known CPICH transmit power in
conjunction with the CPICH RSCP and
UTRA carrier RSSI would allow the
calculation of pathloss to the cell and
allow an estimation of cell dominance in
idle mode.
•
Estimate of the orthogonality of the
downlink is still problematic
•
Drive test data is essential to validate
propagation models.
Drive Test Measurement
Drive Test Measurements
• Prediction Assessment
• Test Site Comparison
•
Comparison of model against drive test measurements of site not used in
the calibration process
• Drives vs. Predicted Best Server
•
Comparison between predicted and measured best servers
• Drives vs. Predicted Pilot Pollution
•
Comparison between predicted and measured pilot pollution
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Drive Test Measurement
Drive Test Measurements Analysis
• Test Site Comparison
• Drive Test data compared with 3g calibration tool
• Analysis should provide both mean and standard deviation agreement
•
For example
– Mean error of 1.8dB
– S.D of 7.9
– Is a good practical fit
• Drives vs. Predicted Best Server
• Exposes discrepancies with map data and local features
•
Mud banks, rocks,
• Exposes limitations in antenna models and propagation model
• Drives vs. Predicted Pilot Pollution
• Will highlight regions of multipath interference, difficult to calculate
Drive Test Measurement
Drive Test Measurements Analysis
• Suggested Improvements
• Use of multiple propagation models for terrain.
•
Flat areas
•
Hilly areas
•
Urban areas
• Accurate clutter definition
• Drive test to be repeated in some areas where major discrepancies occur
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Drive Test Measurement
Test-mobile Measurements
Measurements
• The commonly identified KPIs are not in themselves appropriate for
pre-launch optimisation and acceptance
• Test-mobile measurements, depending on the availability of
engineering mobiles, should allow measurement of:
• CPICH and P-CCPCH availability
• DCH - Dedicated channel DL performance
• Cell dominance
• Active set size
• Required UL Tx Power
• These measurements would be possible under both loaded and
unloaded conditions
18.3 Interpretation of Measurements
It is not sufficient to know what measurements can be made. The
optimisation engineer needs to be able to interpret measurements to
identify problems, choose the most appropriate measure to rectify the
problem, and identify the best method for enhancing network
performance. This will often entail taking a number of KPI’s in
conjunction. For example, it is often necessary to know the condition of
the uplink and of the downlink when choosing between alternative
proposed methods of network optimisation.
For example, a drive test in undertaken during the busy hour in a live
network. The test route is 100 metres in length along a route such that the
distance to the nearest cell remains approximately constant. The
following KPIs are extracted from the measured data.
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Ec/No Serving Cell
-11 dB
Ec/No Neighbour 1
-20 dB
Ec/No Neighbour 2
-22 dB
Average Uplink Channel Power
+21.4 dBm
Average Downlink Total Traffic Channel Power
+39.6 dBm
Note the maximum uplink channel power is 23 dBm and the maximum
total downlink channel power is 42 dBm.
What can an intelligent look at such results reveal? Firstly, the cell is
under stress (which is probably why the drive test was performed). We
can see from the pilot measurements that there is only one dominant
serving cell. We are near the edge of the cell from the uplink coverage
viewpoint (dangerously near judging by the uplink power levels
recorded). Let us assume that the reason for carrying out the drive test
was because coverage levels were reported as poor in this particular road.
What methods would you recommend for improving this coverage?
We should consider the cost-benefit implications of any possible
solutions:
Additional Site
Very expensive – last resort
Mast Head Amplifier
Cheapest Solution – probably
Uplink Diversity
More expensive than MHA but
capacity benefits
If we narrow down the possibility to either installing an MHA or
implementing uplink diversity we need to establish the benefits that each
would bring. When considering UL diversity, the possibility of increasing
capacity must be assessed. In this circumstance a load will be transferred
to the downlink. However, the data received shows that the downlink
traffic power is near its limit and that the downlink would become the
limiting factor if UL diversity was implemented. The MHA appears to be
an attractive, rapid, relatively cheap solution – but – would it work? It is
possible for the MHA to offer no improvement at all. Remember that a
MHA only offers improvement if there is a noise problem to start with,
probably caused by high feeder loss. If such circumstances exist, then an
improvement of about 2 dB can be expected (an exact calculation is
possible). This level of improvement should reveal itself through a
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subsequent drive test with the UE transmit power being lower than
before the MHA was installed.
Alternative solutions: a still-cheaper solution would be to simply reduce
the Noise Rise limit of the cell by 2 dB or so. It is significant that the test
was done at the busy time of day when the cell Noise Rise level would be
at or near its limit. Reducing the limit will have a coverage benefit but
will reduce the capacity. It is important to realise that the amount by
which it reduces the capacity depends on the original setting. If the
original setting was 3 dB then reducing it by 2 dB would reduce the
maximum loading factor from 50% to 21%. If however the original setting
was 10 dB then the loading factor reduction would be from 90% to 84%, a
much less severe reduction. If coverage is crucial to the area under test
and is being judged as unsatisfactory, this might well be the short term
solution to adopt whilst an MHA is ordered and installed.
Drive Test Measurement
Interpretation of Measurements
•
It is not sufficient to know what measurements can be made.
•
The optimisation engineer needs to be able to interpret measurements
•
This will often entail taking a number of KPI’s in conjunction.
•
For example, lets imagine a drive test
•
•
The test route is 100 metres in length along a route such that the distance to the
nearest cell remains approximately constant.
The following KPIs are extracted from the measured data.
Ec/No Serving Cell
-11 dB
Ec/No Neighbour 1
-20 dB
Ec/No Neighbour 2
-22 dB
Average Uplink Channel Power
+21.4 dBm
Average Downlink Total Traffic
Channel Power
+39.6 dBm
• maximum uplink channel power is 23 dBm
• maximum total downlink channel power is 42 dBm.
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Drive Test Measurement
Interpretation of Measurements
•
The cell is under stress
•
•
There is only one dominant serving cell.
•
•
Pilot levels of other cells are much lower than main cell
We are near the edge of the cell from the uplink coverage viewpoint
•
•
Uplink power is close to maximum
Uplink power is close to maximum
Let us assume that the reason for carrying out the drive test was because
coverage levels were reported as poor on this particular road.
•
What methods would you recommend for improving this coverage?
Drive Test Measurement
Interpretation of Measurements
•
Mast head Amplifier
•
•
Transmit Diversity
•
•
Will increase load on DL and with fast moving traffic has little effect.
Additional Site
•
•
Only reduces feeder loss and can introduce DL problems due to insertion loss
Very expensive option and should be last on list
Reduce Noise Rise Limit
•
Reduction of noise rise limit will increase coverage but will reduce total
capacity.
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18.3.1
Using Measurements to Validate Improvements
Let us now consider a different situation. Suppose we are building a
network to cover a city-centre area. Site density is going to be high and so
coverage will not be a problem. We are in an interference-limited
situation. Before the network is switched on, it is suggested that the
improvement that can be expected from implementing uplink diversity
should be investigated. Accordingly, a drive test is carried out without
diversity and then repeated with diversity activated on the uplink. We
are to confirm that the diversity receiver is working correctly and, further,
we are to comment on the improvement that will be offered by such a
network.
The problem is one of checking that a reduction in uplink Tx power
results from enabling diversity, then using such results to predict an
increase in capacity. If we are in a situation where coverage is not an
issue, then the improvement in uplink capacity will be in proportion to
the reduction in required transmit power. For example, if the reduction is
an average of 3.5 dB, then we can assume that the target Eb/No reduction
is also 3.5 dB. This is a ratio of 2.2 and a capacity improvement by a factor
of 2.2 could be expected. Remember, MHA’s would do no good whatever
in this situation as they do not increase the pole capacity. However, the
question must be asked regarding the downlink capacity. Our previous
analysis (section 12) suggests that the downlink may well prove to be the
limiting factor in such a situation. Again, downlink measurements can be
put to good use.
18.3.2
Comparing Uplink and Downlink Capacity
If the network is quiet, then the uplink loading factor measured by the
UTRAN should be a reliable indicator of uplink capacity in terms of
similar users to the single user conducting the drive test. On the
downlink, it can be assumed that the downlink Tx power was required to
overcome the interference effect of the common and pilot powers.
Suppose the data available, when there is a single user present on the
network, showed the following average levels (without diversity being
implemented).
Downlink:
o Pilot 33 dBm
o Traffic Channel 20 dBm
o Total Transmit power 37 dBm
¾ Uplink:
o Loading factor 4%
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The uplink record simply suggests that, at pole capacity, 25 connections
could be made. On the downlink, at low levels of path loss it is
reasonable to ignore thermal noise. The traffic channel power to total
transmit power ratio is -17 dB. 17 dB is 50 as a ratio. This puts a pole
capacity of 50 channels on the downlink. However, if we have a constant
transmission at +37 dBm, and the maximum total transmit power is 43
dBm, then the maximum noise rise on the downlink will be 6 dB and the
maximum loading factor 75%. This puts a limit of 38 simultaneous
connections.
If this was the case, we can say that we are in an uplink-limited situation
(if simultaneous traffic is to be used) but implementing UL diversity
might well lead to a doubling of uplink capacity that would reverse the
situation and make it downlink limited.
18.4 Using Measured Data
One of the biggest 3GPP documents is TS25.331 v4.10 Release 4, Radio
Resource Control RRC protocol specification. At 942 pages this isn’t a
document that you print out and have sitting on your desk. We are going
to use this document as an online reference and investigate drive test
message flow data.
Drive Test Measurement
System Information Structure
•
Measurement data which can be recorded are in the form of message flows.
•
These message flows indicate which blocks of information have been
transmitted and from which channel.
•
Broadcasy Information is organised into a structure
•
Master Information Block MIB
•
Scheduling Block SB
• System Information Block SIB
RRCD
10:44:24.384
BCCH_BCH
SYSTEM_INFORMATION_BCH
RRCD
10:44:24.414
BCCH
MASTER_INFORMATION_BLOCK
RRCD
10:44:24.454
BCCH
SYSTEM_INFORMATION_BLOCK_TYPE_1
RRCD
10:44:24.504
BCCH_BCH
SYSTEM_INFORMATION_BCH
RRCD
10:44:24.554
BCCH
SCHEDULING_BLOCK_1
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Drive Test Measurement
System Information Blocks SIB’s
•
18 SIB’s defined by ETSI TS 25.331 Release 4
•
Type 1
•
•
NAS system information as well as UE Timers and counters
Type 2
•
•
URA identity
Type 3
•
Parameters for cell selection and re-selection
•
Type 4
•
Type 5
•
Same as Type 3 but in connected mode
•
•
Parameters for configuration of common physical channels
Type 6
•
Same as Type 5 but in connected mode
Drive Test Measurement
System Information Blocks SIB’s
•
18 SIB’s defined by ETSI TS 25.331 Release 4
•
Type 7
•
•
Type 8
•
•
•
Only for FDD -- CPCH information to be used in the cell
Type 10
•
Only FDD – Used by UE’s having their DCH controlled by a DRAC.
•
DRAC
Type 11
•
•
Only for FDD – static CPCH information to be used in the cell
Type 9
•
•
Fast changing parameters for UL interference
Contains measurement control information to be used in the cell
Type 12
•
Same as Type 11 but in connected mode
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Drive Test Measurement
System Information Blocks SIB’s
•
18 SIB’s defined by ETSI TS 25.331 Release 4
•
Type 13
•
•
Type 14
•
•
Radio bearer, transport channel and physical channel parameters to be
stored by UE for use during Handover HO
Type 17
•
•
UE positioning method for example GPS
Type 16
•
•
Only TDD
Type 15
•
•
Used for ANSI-41
Only TDD
Type 18
•
Contains PLMN identities of neighbouring cells
Drive Test Measurement
Example 3g Message Flow
RRCD
10:44:24.675
BCCH
MASTER_INFORMATION_BLOCK
RRCD
10:44:24.725
BCCH
SYSTEM_INFORMATION_BLOCK_TYPE_1
RRCD
10:44:24.775
BCCH_BCH
SYSTEM_INFORMATION_BCH
RRCD
10:44:24.795
BCCH
SYSTEM_INFORMATION_BLOCK_TYPE_2
RRCD
10:44:24.825
BCCH
SYSTEM_INFORMATION_BLOCK_TYPE_3
RRCD
10:44:24.855
BCCH
SYSTEM_INFORMATION_BLOCK_TYPE_7
RRCD
10:44:24.885
BCCH
SYSTEM_INFORMATION_BLOCK_TYPE_18
RRCD
10:44:24.935
BCCH_BCH
SYSTEM_INFORMATION_BCH
RRCD
10:44:24.985
BCCH_BCH
SYSTEM_INFORMATION_BCH
RRCD
10:44:25.035
BCCH_BCH
SYSTEM_INFORMATION_BCH
•
Exercise
•
Check the SIB’s with the descriptions in the ETSI TS 25.331 document
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Drive Test Measurement
Example 3g Message Flow
RRCU
10:36:28.320
CCCH
RRC_CONNECTION_REQUEST
RRCD
10:36:28.660
CCCH
RRC_CONNECTION_SETUP
RRCU
10:36:29.461
DCCH
DCCH_RRC_CONNECTION_SETUP_COMPLETE
L3U
10:36:29.531
DCCH
CM_SERVICE_REQUEST
RRCU
10:36:29.531
DCCH
INITIAL_DIRECT_TRANSFER
L3D
10:36:29.842
DCCH
CM_SERVICE_ACCEPT
RRCD
10:36:29.842
DCCH
DOWNLINK_DIRECT_TRANSFER
L3U
10:36:29.862
DCCH
SETUP
RRCU
10:36:29.862
DCCH
UPLINK_DIRECT_TRANSFER
L3D
10:36:30.162
DCCH
CALL_PROCEEDING
RRCD
10:36:30.162
DCCH
DOWNLINK_DIRECT_TRANSFER
RRCD
10:36:30.733
DCCH
RADIO_BEARER_SETUP
RRCU
10:36:31.444
DCCH
RADIO_BEARER_SETUP_COMPLETE
•
In this segment a call is established
•
Check the SIB’s with the descriptions in the ETSI TS 25.331 document
Drive Test Measurement
Example 3g Message Flow
•
RRCU
10:38:48.651
DCCH
MEASUREMENT_REPORT
RRCD
10:38:48.922
DCCH
ACTIVE_SET_UPDATE
RRCU
10:38:48.932
DCCH
ACTIVE_SET_UPDATE_COMPLETE
RRCD
10:38:49.403
DCCH
MEASUREMENT_CONTROL
During Call is message flow is repeated over and over
L3U
10:44:23.433
DCCH
IMSI_DETACH_INDICATION
RRCU
10:44:23.433
DCCH
UPLINK_DIRECT_TRANSFER
RRCD
10:44:23.713
DCCH
RRC_CONNECTION_RELEASE
RRCU
10:44:23.753
DCCH
RRC_CONNECTION_RELEASE_COMPLETE
RRCU
10:44:23.884
DCCH
RRC_CONNECTION_RELEASE_COMPLETE
RRCU
10:44:24.034
DCCH
RRC_CONNECTION_RELEASE_COMPLETE
•
Call detach sequence
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19 Cluster Identification
19.1 Procedure and Measurements
Clusters
Optimisation of Site Clusters
• Procedure
• Identify size and location of clusters
• Define primary, secondary clusters.
• Define Cluster characteristics
– Coverage, Interference, Handover region size and location
– Neighbour list assessment
– Access, handover and call failures
• Take Measurements
– Drive tests
– EC/Io, pilot power, UE TX Power, Neighbours, call
success drops and Handover stats.
– Service allocation, FER/BLER, Throughput, Max and Av.
BER, Delay
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Clusters
Cluster Defining
• Identify Clusters of sites
• Based on
•
Terrain
•
Traffic distribution
• Characterise clusters in terms of primary/secondary clusters
• Network is to be optimised in clusters based on external interferers
• This method provides for
• Work delegation
• Progress tracking
• Minimises tool processing time
Clusters
Cluster Defining
Datafill
Eg
Scrambling Codes
Node B Parameters
Network
Acceptance
Cluster Approval
Site Approval
Network of clusters
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Site
251
Clusters
Cluster Defining
• Once Clusters have been defined then external
interferers are found
• Using 3g simulation tools based on pilot coverage
• Report on each cell within a cluster
• The Interferer Signal Level
•
Assume interference occurs when interfering
signal is within 10dB of the reporting cell
• The Interference Area Threshold
•
Other cells which interfere with the reporting cell
area can be graded according to how much of the
area is affected.
•
Less than 5% can be regarded as insignificant
within the overall simulation tolerances
Clusters
Cluster Defining
• Simulation can then be filtered to cluster regions
including other cell interferers
• Your network can then be analysed
• Let’s develop a method ….
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Pilot Coverage
Pilot Coverage
• Simulate existing network to determine pilot coverage
• At this stage no traffic loading is required
• Support results with cross reference to drive test data
• Pilot coverage identifies
• Indication of high levels of interference between sites
• Non-dominance issues
• Uneven service area distribution between sites
• New site requirement for areas which lack coverage.
• Expected pilot coverage levels, may indicate that initial
pilot power is too high.
•
Pilot power reduction
– more power to users
– Less interference
Network Acceptance
• Live traffic network loading
• Regionally based
• Measurements
–
–
–
–
OMC stats – KPI’s
Drive tests – Sample drives
Iu analysis – Specific problems
Call trace – Specific problems
• Highlight Poor Areas
– Resolve or negotiate
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Tool Requirement
• Planning Tool
• Network Simulator
• OMC data download and analysis
• Network Configuration Management
• ‘Drive Test’ mobiles.
• ‘Drive Test’ data analysis software
• Band monitors
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20 Scrambling Code Example
20.1 Case Study
Scrambling Codes
Scrambling Code/Pilot Pollution
• Rake Receiver
• Typically 3 fingers
• Can only receive the best 3 RF signals
• Additional signals will cause interference
• Design consideration
• Provide a single strong signal
• Make sure cells have at most an additional 2 signals which meet
selection criteria, eg -3dB down from main signal
• Footprint of cell
• Should have a defined area
• Useable signal at cell boundary
• No sputtering of signal outside of main area
• Determine number of pilot signals above threshold
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Scrambling Codes
Scrambling Code/Pilot Pollution
•
Best Server by Pilot
Scrambling Codes
Scrambling Code/Pilot Pollution
•
Signal to Interference Ratio SIR, and Active set size
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Scrambling Codes
Scrambling Code/Pilot Pollution
•
Downlink Interference
• High Inter-cell Interference i
•
Solutions
• Increase downlink power to maintain Eb/No on user channel
• Introduce Transmit Diversity into offending cell
• Consider soft handover with cell2
• Change carrier frequency ( GSM type solution )
•
Implications
• Raises the value of i in cell1 and in cell2
• Increases the Node B cell power in cell1 and cell2
Scrambling Codes
Limitations
• 12.2 kbps speech uses a spreading factor of 128
• Making allowances for control and handover channels, this reduces to
a maximum of 98.
• Reducing speech rate to 7.95 kbps or below will increase this maximum
to 196 channels.
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Scrambling Codes
Use of Multiple Spreading Codes
• Adopting sophisticated signal processing techniques reduces target Eb/No.
• Target Eb/No can become negative resulting in very high pole capacities.
• E.g. Uplink Eb/No -2 dB. i = 0.5 pole capacity 4065 kbps
• Downlink Eb/No -0.5 dB. i = 0.5; α = 0.6 pole capacity 4801 kbps
• Throughputs in excess of 2 Mbit/s achievable.
Scrambling Codes
Use of Multiple Spreading Codes
• Suppose we want to service 160, 12.2 kbps voice users on such a cell.
• We need more than one scrambling code. A secondary code would be
allocated.
• No orthogonality between scrambling codes making downlink analysis
more complicated.
• Suppose 98 users are on the primary channel and 62 users on the
secondary channel.
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Scrambling Codes
Use of Multiple Spreading Codes
• From viewpoint of mobile on primary channel.
• Loading factor from other primary channel users
• Pole capacity with no orthogonality = 12.2 +
98×12.2
= 24.9%
4801
3840
10−0.05 = 2881kbps
1.5
• 62 users represent a loading factor of 26.3%.
• Total loading factor 51%. Noise Rise 3 dB.
Scrambling Codes
Use of Multiple Spreading Codes
• From viewpoint of mobile on secondary channel.
• Loading factor from secondary channel users
62×12.2
= 15.8%
4801
• 98 users on primary channel represents a loading factor of
98×12.2
= 41.5%
2881
• Total loading factor is 57%. Noise Rise is 3.7 dB.
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Scrambling Codes
Use of Multiple Spreading Codes
• Mobiles receive the same wideband power but experience
different noise rise.
• To equalise Noise Rise, the users must be equally split
between codes.
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21 Neighbour Planning
21.1 Neighbour Lists
Neighbour Planning
Neighbour Planning
• For 3G cells, neighbour lists can consist of upto
• 32 co frequency neighbours
• 32 adjacent frequency neighbours
• 32 gsm neighbours
• The RAN broadcasts the initial neighbour cell lists of a cell
in the system information messages on the BCH.
• In SHO state, neighbour lists from the active sets are
combined in the RNC and sent to the UE on the DCCH.
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Neighbour Planning
Neighbour Planning
• To identify a UMTS neighbour cell, this list includes the
following information:
• Global RNC identifier (PLMN identifiers, RNC identifier)
• Cell identifier
• LAC
• RAC
• Channel Number
• Scrambling code of the Primary Common Pilot Channel
(P-CPICH)
• For a GSM neighbouring cell, the following information
is sent:
• Cell Global Identification, CGI=MCC+MNC+LAC+CI
• BCCH Frequency
• BSIC
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21.1.1
Initial Neighbour List Generation
Neighbour Planning
Initial Neighbour List Generation
• The initial neighbour lists for a new system or portion of a system can
be generated as follows:
• generate a best server array plot
• run the neighbour creation.
• While carrying out post analysis, the neighbour lists for each cell can
be prioritised according to the boundary lengths (longest boundary
first).
• Do not be tempted to add more distant sites to the neighbour list “just
in case”.
• The objective is to keep the neighbour lists to the minimum length and
hence reduce search times.
• For intra-frequency neighbours, where SHO and softer handover are
also possible, keeping neighbour list to a minimum can also help in
reducing the overall network load by avoiding unnecessary SHO.
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21.1.2
Optimisation of Neighbour lists:
Neighbour Planning
Optimisation of Neighbour Lists
• Neighbour lists should be made as accurate as possible.
• Because if there is a situation when the mobile detects a
candidate cell, which is not, defined in the neighbouring cell.
• Then the mobile has to decode the cell, to identify the cell and
report it back to RNC.
• Secondly, handovers can only be performed from one cell to
another if the target cell is a neighbour to the serving cell.
• So, even if a mobile receives pilot signal from a neighbouring
cell which is fulfilling the handover criteria but that cell is not
defined in the neighbour list of the serving cell, handover will
never occur.
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Neighbour Planning
O
ptimisation of Neighbour Lists
Optimisation
• Different approaches can be used for different areas
depending on the importance of the area and the
complexity of the network.
• For most critical areas, pilot strength measurement
messages sent by UE to the network can be accessed
through OMC.
• These measurements can be taken over a specified
period of time and can be analysed on cell by cell basis.
• Overall trend (more frequently occurring) of the cells
reported by the mobile can be compared with the original
neighbour lists.
• By removing the discrepancies in the two lists, an
accurate neighbour plan can be obtained.
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21.1.3
Inter-freq & Inter-system Neighbour Planning:
Neighbour Planning
Inter-frequency & Inter-system Neighbour Planning
• Inter-frequency and inter-system neighbour measurements are
triggered by RNC.
• Depending on the network configuration (frequency/carrier
allocation, neighbour cell definitions, cell layers etc), the RNC
recognises the possibility of an inter-frequency or inter-system
handover.
• Handovers to inter-frequency and inter-system neighbours can be
based on the imperative situations, which can arise when
• Average DL transmission power of radio link = maximum DL power.
• Quality deterioration report from uplink outer-loop control is generated.
• Quality deterioration report from MS is generated.
• Unsuccessful SHO procedure.
• Unsuccessful radio access bearer setup
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Neighbour Planning
Inter-frequency & Inter-system Neighbour Planning
•
To avoid frequent SHO, disabling SHO capability in certain cells can be
performed.
•
Load sharing and best use of the resources can be obtained through the
handover criteria between neighbours.
•
For instance, when the coverage areas of UMTS and the GSM system
overlap each other, speech connections can be handed over to the 2G
system.
•
In a similar fashion, for different frequencies in 3G, load sharing can be
controlled through neighbour planning. Different weight values can be used
to direct traffic to specific cells.
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22 Automation Topics
22.1 Modelling
Automation
Automation of Network Modelling
• Dynamic nature of 3g networks
• Many new services
• Different data rates
• Different terminals
• Rapid operational optimisation
• Increase in complexity – increases the time for
analysis
• Should the process be automated ?
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Automation
Automation of Network Modelling
• How can we automate ?
• What can we tune ?
• How do we validate the results ?
Automation
How can we automate ?
•
Default parameters provided by manufacturers ( starting point )
•
You then optimise cell by cell, within clusters
•
Take the KQI – KPI history, and QoS targets
•
Alter parameters in the RNC and Node B
•
Feedback of new KPI’s will enable the quality manager to
evaluate new QoS
•
This cycle can be automated.
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Automation
What can we tune?
• Total Power
• P-CPICH power
• Dedicated NRT/RT capacity
Automation
Total Power Target
•
Powertx_target
• Transmitter target power
•
Powerrx_target
• Receiver target power
•
Powertotal_tx
• Total transmitter power
•
Powertotal_rx
• Total receiver target power
•
Sets the capacity/coverage of the cell
•
Determines the admission of users
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22.2 Total Power Targets
Automation
Total Power Target
• Call accepted if
• Load control and admission control say “ok”
• Powertotal_rx < Powerrx_target
• So higher the Powerrx_target the greater the capacity of
the cell
• Setting a lower Powerrx_target will provide greater
coverage, due to lower interference.
Automation
Total Power Target
•
Optimisation can occur between Powerrx_target and Interference Margin
Power Receive Target
Interference
Margin
Power Distribution
Powerrx_total
Blocking
Prob 95%
Powerrx_target
Node B Power
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Automation
Total Power Target
• Setting the interference margin defines the
coverage/capacity
• If we set Powerrx_target below the interference margin
• Coverage is reduced
• Capacity is reduced
Automation
Total Power Target
•
Including NRT traffic pushes the Powerrx_total to the right
Power Receive Target
Interference
Margin
Powerrx_total (RT+NRT)
Power Distribution
Packet Load
Blocking
Prob 95%
Powerrx_target
Node B Power
Packet Capacity
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23 Future Impact of
Standards
23.1 Observations of Release 5 and beyond
Release Impact on Optimisation
DCH rate control
• DRNC release 99
• No way of requesting rate reduction from SRNC
• DRNC release 4
• Signals SRNC with current allowed maximum rate of a DCH
• TR 125.935 V4.1.0 (2002-03)
• SRNC uses R99, DRNC uses R4
• DRNC will never receive a guaranteed rate of a DCH and will assume
the maximum rate is the guaranteed rate.
• DRNC will not apply restrictions
• SRNC will reject the request if made by the new “DCH rate control”
• SRNC uses R4, DRNC uses R99
• DRNC will discard any rate restrictions
• SRNC will never receive any rate restrictions
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Release Impact on Optimisation
Cell Loading
• SRNC admission control requires knowledge of cell loading to be
useful
• SRNC controlling mobility within its own RNS no problem
• SRNC controlling mobility between own cell and DRNC controlled cell
•
SRNC has no parameter in R99 to establish load in other cell
• SRNC controlling mobility between two cells controlled by DRNC
•
SRNC has no idea as to the loading of either cell
• Radio Resource Management Optimisation for Iur and Iub
• TR 125.935 V4.1.0 ( 2002-03) release 4
• Vendor specific calculations of load passed over Iur to SRNC
Release Impact on Optimisation
AAL2 QoS Optimisation
•
No way under Q2630.1 to establish priority in the AAL2 type
•
Use of Q2630.2 provides for a method of prioritising
•
UMTS QoS optimisation for AAL2 type 2 connections over Iub and Iur
interfaces
•
TR 125.934 V4.0.0 (2001-03) release 4
• Assumes the SRNC can reschedule data frames with CFN numbers in the future to
optimise the bandwidth requirements for the ATM link
• Example given
•
•
Old method required 2.8Mbps
•
New method requires 0.37Mbps
Radio link is unaffected by this change
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24 From Initial Roll-Out to
Mature Network
24.1 Introduction
Optimisation procedures should be incorporated into every stage of
development of a UMTS network. Bearing in mind the different
priorities that are likely to affect the different stages, it is possible to be
alert to opportunities to implement the best possible network in all
circumstances from the initial roll-out to targeting specific services and
traffic loads in a mature network. This section follows the
development of a network highlighting the possible different strategies
that can be employed.
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24.2 Initial Roll-Out
Here the priority is probably to obtain the maximum coverage as
quickly as possible for a minimum investment. GSM operators will
want to make the best use of existing sites. The issues here will be:
Does operator have GSM
network?
Is GSM network 900 MHz?
1800
What is the “benchmark” service?
If yes, possible to provide good
coverage at 64 kbps.
Coverage problems need to be
addressed.
Data rate and Eb/No will affect
coverage.
Questions that have to be answered include:
How many antennas per site
What capacity can I expect per cell?
Should I deploy MHAs?
Should I use the “Optimised
Configuration for Roll-out”?
Should I use diversity or Smart
Antennas?
Should I plan to
asymmetric services?
24.2.1
provide
for
1, 3 or 6?
Initially 300-400 kbps but
heavily dependent on service
and configuration.
Will help with UL coverage
Can lead to coverage being DL
limited.
These will add substantially to
cost and will probably be left
until demand justifies them.
This will increase the cell power
requirement.
The Initial Plan
Initially, coverage will be dictated by the limitations of the uplink. Key
parameters are the transmit power of the mobile, Eb/N0, bitrate, antenna
gains, noise rise limit. However, when planning a UMTS network it must
be born in mind that the capacity of the network will be influenced by the
location of the users. If the traffic density is uniform, then there isn’t a
problem. But, if there are clearly identifiable hotspots within a network
then the position of sites with respect to these hotspots will affect the
capacity substantially.
A hotspot that is located very close to the Node B will:
a) be able to communicate with the Node B with low levels of UL power.
This will lead to a high value of Frequency Re-use Efficiency being
realised.
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b) require only low levels of DL power thus increasing the capacity in this
direction and also reducing DL interference.
Often, it is not possible to relocate a Node B to assist in this matter.
However, it should be noted that merely re-directing antennas can help in
this situation. The difference between the link loss to a location at the
border between two, co-located, cells and the loss to a location at the same
distance but in the principal direction of the antennas will be as much as 6
dB. This will allow the mobile power and cell power to be reduced.
Additionally, because the users will be experiencing much less
(downlink) interference, the pole capacity on the downlink will increase.
Uplink coverage problems can be overcome by:
•
•
•
•
•
•
•
•
Reducing the Noise Rise limit.
Installing MHAs.
Using lower loss feeder.
Implementing diversity reception at the cell.
Implementing Multi-User Detection at the cell.
Using higher gain cell antennas.
Reducing bitrate and/or Eb/N0 value offered.
Using a second carrier to allow further reduction in NR limit.
24.3 Evolution of the Network
The result of the initial plan should be to provide continuous coverage
over a specified area for a specified service. The next stages in network
development will be to:
Increase network capacity.
Increase coverage range for higher resource services.
Provide specifically for provision of asymmetric services.
Network capacity can be increased by:
•
•
•
•
•
•
•
•
•
Sectorising sites (1 to 3; 3 to 6).
Implementing MHAs to allow NR limit to be increased.
Implementing diversity reception and transmission.
Implementing Multi-User Detection.
Increasing cell transmit power.
Adding micro-cells.
Incorporating extra sites into a macro-cell layer.
Adding extra carriers.
Reducing mutual interference between cells.
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Coverage range for higher-resource services can be increased by
• Reducing the Noise Rise limit.
• Installing MHAs.
• Using lower loss feeder.
• Implementing diversity reception at the cell.
• Implementing Multi-User Detection at the cell.
• Using higher gain cell antennas.
Provision specifically for asymmetric services can be helped by:
• Ensuring external interference is a minimum at traffic hotspots.
• Planning to minimise link loss to traffic hotspots.
• Increasing cell power.
• Implementing transmit diversity at the cell.
Being able to quantify the improvements that will result from a specific
strategy is crucial to being able to evaluate alternative approaches. The
end result should be the best value for money and the best return on
investment.
Network Implementation and Evolution
Network Implementation and Evolution
•
Optimisation is about undertaking every task so as to
achieve the maximum benefit for a given investment of
resource.
•
This applies to the initial network implementation as
much as it does to deciding on micro-cell
implementation strategies.
•
We should be aware of the possible alternative
approaches to solving problems and be able to
evaluate these alternatives.
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Network Implementation and Evolution
Initial Roll-out
•
•
Issues:
•
Is there an existing GSM network?
•
Is it 1800 MHz or 900 MHz
•
What is the “benchmark” service
Questions
•
How many cells per site?
•
What will be the capacity per cell?
•
Should MHAs be deployed
•
What about Optimised Configuration
for Roll-out (OTSR)?
•
Should diversity or even “smart”
antennas be used?
•
Should we plan for asymmetric
services?
Network Implementation and Evolution
Initial Roll-out
•
Initial Priorities:
•
Coverage: determined by UL budget
•
Key parameters:
• Tx Power of Mobile
• NR limit
• Antenna gains
• Eb/No
• Bitrate
•
Capacity issues arise:
•
How can mutual interference be
minimised?
•
Is the subscriber density uniform?
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Network Implementation and Evolution
Optimising the Initial Roll-out
Low Link Loss: Low Tx power;
•
Minimising mutual inteference
•
High DL capacity; High FRE.
Pay careful attention to the radiation
from each cell.
•
•
Downtilting of antennas.
Minimise the link loss to traffic
hotspots.
•
If the loss is low, UL power will be low;
FRE will be high.
•
High Link Loss: High Tx power;
Low DL capacity; Low FRE.
Requirement on DL power will be low,
thus increasing DL capacity.
•
Network Implementation and Evolution
Optimising the Initial Roll-out
Low Link Loss: Low Tx power;
•
Optimising the situation is
High DL capacity; High FRE.
possible without moving
sites.
•
Re-directing the antennas
on a site can affect the link
loss by up to about 6 dB.
•
Also, if there is one
dominant serving cell,
mutual interference is
reduced.
High Link Loss: High Tx power;
Low DL capacity; Low FRE.
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Network Implementation and Evolution
Optimising the Initial Roll-out
•
Overcoming coverage problems.
•
Reduce NR limit
•
Install MHAs
•
Use lower loss feeder
•
Implement diversity reception
•
Implement MUD
•
Use higher gain cell antennas
•
Reduce bitrate
•
Reduce Eb/No
•
Use a second carrier to aid in NR limit
reduction
Network Implementation and Evolution
Network Evolution
•
As network evolves, we
need to:
• Increase network
capacity.
• Increase coverage range
for higher-resource
services.
• Provide specifically for
asymmetric services.
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Network Implementation and Evolution
Optimising Capacity
•
Capacity can be increased by:
•
Sectorising sites
•
Implementing MHAs to allow NR
limit to rise.
•
Implementing diversity in both
directions
•
Implementing MUD
•
Increasing cell Tx power
•
Adding Micro-cells
•
Incorporating extra sites into a
macro layer
•
Adding carriers
•
Reducing mutual interference
Network Implementation and Evolution
Optimising Coverage Range for New Users
•
Increasing coverage range for
higher resource users.
• Reducing NR limit.
• Installing MHAs.
• Using lower loss feeder.
• Implementing diversity reception.
• Implementing MUD.
• Using higher gain antennas.
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Network Implementation and Evolution
Asymmetric Services
•
Provision for Asymmetric
Services
• External interference at hotspots
is kept to a minimum.
• Minimise link loss to hotspots.
• Increase cell power.
• Implement transmit diversity.
Network Implementation and Evolution
Optimising the Network
• Demand for downlink-dominated
services are not likely to be uniformly
spread.
• The ease with which demand can be
met is very dependent on the
location of the mobile user.
• It is important, when network
planning, to be able to identify the
“good” and the “bad” areas quickly.
Variations in Traffic Density
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Network Implementation and Evolution
Optimising the Network
• We need an indicator that will predict
Pilot Power
downlink performance and is quick and
easy to predict.
Traffic Power
• The “pilot SIR” (Ec/I0) serves as a
suitable indicator.
• If the pilot power is +33 dBm, the pilot
SIR shows the SIR for any traffic
channel that is given 33 dBm of power.
• For a given Eb/N0 value, the necessary
processing gain and hence maximum
bitrate can be found.
Network Implementation and Evolution
Optimising the Network
• As an example, suppose the pilot SIR at a point is found to
be -12 dB.
• If the Eb/N0 required is +4 dB, then 16 dB of processing
gain will be necessary.
• The maximum bitrate possible for a power of +33 dBm is
then 96 kbps.
• If the pilot SIR is -6 dB then 384 kbps would be possible.
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Network Implementation and Evolution
Determining pilot SIR
• AIRCOM’s 3g tool allows you to
display pilot SIR for various
levels of network loading.
Pilot SIR -7 dB
• The display predicts the result
of a drive test through a
network, examining each pixel
in the coverage area.
Pilot SIR -1 dB
• Pilot SIR is seen to be very
dependent on location and the
loading level of the network.
Lightly Loaded network
(Traffic Power 35 dBm)
Network Implementation and Evolution
Determining pilot SIR
• We are probably more
interested in the situation with a
heavily loaded network.
• Variations in pilot SIR at a given
Pilot SIR -11 dB
distance can be as much as 6
dB.
• This represents a factor of 4 in
the “bits per second per
Pilot SIR -5 dB
milliwatt” possible on the
downlink.
Heavily Loaded network
(Traffic Power 41 dBm)
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Network Implementation and Evolution
Determining pilot SIR
• Over the coverage area of a cell
the pilot SIR varied by about 10
dB.
• Thus the “bits per second per
milliwatt” factor would vary by a
factor of 10 or more.
• The implications for cell siting
and antenna orientation are
clear.
• Note: simply re-orientating
antennas can improve
throughput by a factor of 4.
Pilot SIR -14
dB
Pilot SIR -4 dB
Heavily Loaded network
(Traffic Power 41 dBm)
Network Implementation and Evolution
Limiting Factors
• Even if there is zero pathloss,
pilot SIR will be limited by the
interference effect of the other
channels, mainly the traffic
channel power.
• Traffic channel power of 41
dBm reduced to effective
interference power of 37 dBm if
the orthogonality is 0.6.
• Comparing this with 33 dBm
pilot power suggests that the
maximum value of pilot SIR will
be -4 dB.
Pilot SIR -14
dB
Pilot SIR -4 dB
Heavily Loaded network
(Traffic Power 41 dBm)
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Network Implementation and Evolution
Limiting Factors
• If orthogonality is 0.9, the pilot SIR is
improved by approximately 4 dB
relative to a value of 0.6.
• If orthogonality is 0.2, the pilot SIR is
worsened by approximately 3 dB
relative to a value of 0.6.
• This 7 dB swing represents a capacity
variation by a factor of 5.
• Further work: site location so as to
optimise orthogonality?
Heavily Loaded network
(Orthogonality 0.9)
Network Implementation and Evolution
Summary
• Approximate methods of
predicting network downlink
capacity can be used in
preliminary planning stages.
• The accuracy can be enhanced
if simulations are available for a
known data throughput.
• Rapid analysis methods using
AIRCOM’s 3G planning tool will
allow a nominal plan to be
assessed and optimised.
• Improvements in capacity by a
factor of 10 are possible by
correctly locating sites and
pointing antennas.
Heavily Loaded network
(Traffic Power 41 dBm)
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24.4 Concluding Remarks
Network Implementation and Evolution
Concluding Remarks
• Why are we bothering?
•To make or save money.
• How do operators make money?
•By transferring data from one point to
another
Network Implementation and Evolution
Concluding Remarks
• Revenue Gains
•Suppose revenue of $ 0.1 is received for every megabit of
data transferred.
•A cell whose capacity is increased by 500 kbit/s (per
carrier) can be expected to earn approximately $ 200000
per carrier per year extra (depending on occupancy rates).
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Network Implementation and Evolution
Concluding Remarks
• Revenue Gains
•If an engineer takes responsibility for 60 cells, each with a
single carrier, the potential gains add up to $ 12 million per
engineer.
•Go and make an extra $ 12 million per year.
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25 Appendix
25.1 Amplificadores MHA
UMTS Masthead Amplifier
ALP Enabled
TM
ISSUE : UMTSMHA002a/100800
FEATURES
•
Market leading low noise
performance
•
Simple to install
•
Bypass in "power down" mode
•
Rugged and highly reliable
•
Excellent lightning protection
•
Full water immersion (IP68)
specification
BENEFITS
REMEC Masthead Amplifiers help reduce the cost of base
station deployment by extending cell coverage.
They also significantly improve call quality and reduce the number
of dropped calls, which is the number one reason for customer
churn.
UMTS Advanced Cell Planning and Optimisation
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Extends cell coverage
•
Reduces bit error rate – vital for data
applications
•
Significantly reduces roll out costs
•
Improves call quality
•
Reduces dropped calls
•
Enhances in-building coverage
291
REMEC MHAs improve in-building coverage and reduce overall
system bit error rate, which is vitally important for data applications.
•
Increases handset battery life
These units have the best noise and lightning performance
available and are IP68 rated for full water immersion.
Time and time again network trials have proven these units to
significantly improve network performance, providing the largest
improvements margins in competitive benchmarking. Over fifty
networks worldwide have improved their performance using
REMEC MHAs.
Tx Characteristics
Frecuency Range
Bandwidth
Insertion Loss
Ripple
Max Power Handling
Return Loss
(VSWR)
Specification
2110-2170 MHz
60 MHz
<0.6 dB
±0.2 dB
52 dBm CW
62 dBm Peak
>18 dB
(<1.29)
Rx Characteristics
Frecuency Range
Bandwidth
Noise Figure (Typical)
Gain Variation Over Frequency &
Temperature
Gain Variation with Frequency
Output 1dB Compression
Output IP3
Return Loss (VSWR)
Rx to Tx Rejection
(Over Operating Band)
System Characteristics
Intermodulation
(2 Tx Carriers at +43 dBm
Products in Rx Band)
DC Supply Voltage*
Current (Nominal)*
Specification
<-120 dBm
+12V±1VDC
125 mA normal
175 mA alarm
Environmental Characteristics
Operating Temp. Range
Storage Temperature
Relative Humidity
Enclosure Protection
Lightning Protection
BTS Port (Bias Tee)
*Other Options Available
ANT Port
EMC
MTBF
Mechanical Characteristics
Dimensions
Weight
Volume
RF Connectors
BTS
ANT
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Specification
1920-1980 MHz
60 MHz
<1.4 dB
12.0±0.9 dB
±0.5 dB
>= 10 dBm
>= +22 dBm
>18 dB active (<1.29)
>12 dB in bypass
(<1.67)
>80 dB
Specification
-40ºC to +65ºC
-40ºC to +85ºC
5 to 95%
IP68
8/20 µS 10Ka Pulse
IEC-801-5
DC Grounded
ETS 300 342-3 compliant
>800,000 hrs.
Specification
312 x 162 x 77 mm
<4kg
3.9 Ltr
7/16 female
7/16 female
292