116997323 umts planning

Applied UMTS Planning for Experienced Radio Engineers 13.1 AIRCOM International Ltd 2002

13. Network Dimensioning and Planning

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.


Planning a UMTS NetworkPlanning 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 PhilosophyThe 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



Link BudgetLink Budget

• Crucial to the planning process.

• Derived assuming a particular Noise Rise.

• Combined with Path Loss model to determine cell range.

Voice ServiceEb/No 5 dBPower Control 2 dBShadow Fade 4 dB Noise Rise 3 dBAntenna Gain 18 dBiProc Gain 25 dBMobile Tx Pwr 21 dBmCell Noise Floor -100 dBmMax Path Loss 150 dBRange 2.35 km


Iterative Spreadsheet DimensioningIterative Spreadsheet Dimensioning

• Carry out link budget to determine range (remember link budget assumes a NR)

• Assess loading of cell and predict Noise Rise. This will differ from assumed Noise Rise.

• Re-calculate range using predicted Noise Rise.

• Re-assess the loading of the cell and re-predict the Noise Rise.

• Keep Calculating Range and re-assessing Noise Rise.

• Finally, the iterations should converge so that the assumedand predicted values of Noise Rise agree.



Graphical ExplanationGraphical Explanation• Increasing Range causes more traffic to be gathered.• Gathering More traffic increases Noise Rise and reduces Range.

Range/PathLoss

Number of active users

Intersection gives the operating point


A complicationA complication

Range/PathLoss

Number of active users

Intersection gives the operating point

• Range calculated from average number of users.

• Noise Rise predicted from estimated peak use of cell.

• Additionally, soft capacity must be considered.



Spreadsheet MethodSpreadsheet 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”


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 2 dB

Antenna Gains 18 dBi

“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.


Example OutputExample 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.

The need for a toolThe need for a tool

• If this can be done using a simple calculator, why do we need a planning tool?

• Planning tool can validate the strategy.

• 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.



Using the 3G Planning ToolUsing 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.


Summary of Initial ResultsSummary 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



Action takenAction 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.


Summary of ResultsSummary of Results• Parameters:


• Results:• Coverage Probability 99.7% (c.f. 98.0%)• Even split of failures between NR and UL Eb/No



Next StepNext 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.


Simulating the Effect of Imperfect Site Location and High Sites

Simulating the Effect of ProblemsSimulating 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.



Summary of ResultsSummary of Results• Parameters:


• Results:• Coverage Probability 97.5% (c.f. 98.7%)• 78% NR and 22% UL Eb/No• Uneven distribution of failures

• Results:• “Problem area” gives 95%

coverage probability (c.f. 97.5% for whole area).


Action takenAction taken• Antennas were re-pointed in an attempt to restore coverage.• Improvement was marginal (96.0% c.f. 95.8%)

• 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.



Problems caused by High SitesProblems 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.



• Uneven loading causes disastrous results.

• Coverage probability reduced from 98.7% to 78.6%.




• 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)


Action takenAction 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).



Alternative ActionAlternative 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 Txpower hence aggravating the problem.

Pilot Power Equal

Mobile Connects to High Site

Pilot Power scaled to equalise service areas.

Mobile Connects to Low Site - Tx Power increased


Alternative ActionAlternative Action• Increased NR Limit of High Site by 10 dB• Decreased Max Tx power, Common Chan power and Pilot power by

10 dB.

• Result:• A dramatic improvement. Performance of network

indistinguishable from ideal case.• High NR experienced by High Site but continued to perform

satisfactorily.• Detecting the existence of High Sites is crucial.



Spotting a High SiteSpotting a High Site

• Examining the Best Server by Pilot array on the 2D view is informative.

• Using a “dummy” GSM terminal and examining traffic captured is possibly more informative as it considers traffic distribution.

• Site35C: GSM-Default 18.0946• Site36A: GSM-Default 18.2301• Site36B: GSM-Default 19.5065• Site36C: GSM-Default 18.4447• Site37A: GSM-Default 13.9719• Site37B: GSM-Default 14.4915• Site37C: GSM-Default 18.2414• Site38A: GSM-Default 37.0476• Site38B: GSM-Default 38.7644• Site38C: GSM-Default 36.72• Site39A: GSM-Default 10.6173• Site39B: GSM-Default 18.9417• Site39C: GSM-Default 10.1203

– High Site


High Sites High Sites -- a final worda 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 otherusers.

• 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.



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 ( )( )10/10 101log10 AC −+= where

A

−=

11010log10 10

1010 X

B where X is the noise rise in dB with transmit 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 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.


Further Work: Adding traffic onto the Further Work: Adding traffic onto the downlinkdownlink

• 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.



• 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




• 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.


Further Work: Mixed ServicesFurther 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.



Campbell’s Theorem Example(1)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:

• The variance is:

∑ ∑ =×+×=×== 3063121Erlangs iiii aabγα

∑ ∑ =×+×=×== 6636112Erlangs 2222iiii aabγν



• Capacity Factor c is:

• Offered Traffic for filtered distribution:

• Required Capacity for filtered distribution at 2% GoS is 21

2.23066 ===

ανc

63.132.2

30 Traffic Offered ===cα




• 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.


Calculating the Relative AmplitudeCalculating 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

1 amplitudefor 1 amplitudefor ratebit

servicefor servicefor ratebit amplitude Relative

0

0

NE

NE

b

b

×

×=


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.

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.

Incorporating more sophisticated Path Loss Incorporating more sophisticated Path Loss ModelsModels

( ) ( ) )log()log()log()log(

)log()log()log()log(log Loss

625431

654321

dhkkhkhkhkk

dhkhkhkhk(d)kk

effeffmsms

effeffmsms

+++++=

+++++=

• “Cost 231 - Hata”

• If hms is fixed then variations are only dependent on heff. Using typical default parameters:

Antenna Ht Model15 140.0 + 32.3 log(d)20 138.2 + 31.5 log(d)25 136.9 + 30.8 log(d)30 135.8 + 30.3 log(d)



A More Challenging TerrainA More Challenging Terrain

154 km2. Heights vary from zero to 135 m a.s.l.


The ChallengeThe 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.



Placing the SitesPlacing the Sites

• Due to irregular outline, 31 sites were required to provide continuous coverage at a range of 1800 metres.


Coverage AnalysisCoverage 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.



Increasing Percentage CoverageIncreasing 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.


Analysing Reason for Analysing Reason for EbEb/No Failures/No Failures

• Eb/No failures follow high path loss areas. If the path loss is too great the required Eb/No cannot be achieved.

Coverage Eb/No Failures



Analysing Reason for NR FailuresAnalysing Reason for NR Failures

• Noise Rise failures concentrated on High Sites. An example is shown.

Coverage Strongest Pilot


Action taken to decrease NR failures.Action taken to decrease NR failures.

• 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.

Coverage

For the cell being investigated:



Covering an Urban Area.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.



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 re-starting 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.

Spreadsheet Dimensioning.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.



UMTS Simulation.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 capacity. Coverage Probability


Optimisation Procedures.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



Optimisation Procedures.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


Conclusions.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.


116997323 umts planning

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