Radio Network Planning Process and Methods for WCDMA

Jaana Laiho, Achim WackerNokia Networks

email: jaana.laiho[achim.wacker]@nokia.comphone +358718023773 fax +358718023876

Abstract - This paper describes the systemdimensioning and the radio network planningmethodology for a third generation WCDMA system.The applicability of each method is demonstrated usingexamples of likely system scenarios. The challenges ofmodeling the multiservice environment are describedand the implications to the system performancesimulations are introduced.Keywords: WCDMA, dimensioning, radio networkplanning, static system simulation, dynamic systemsimulation

I. INTRODUCTIONAs the launch of third generation technologyapproaches, operators are forming strategies for thedeployment of their networks. These strategies must besupported by realistic business plans both in terms offuture service demand estimates and the requirementfor investment in network infrastructure. Evaluatingthe requirement for network infrastructure can beachieved using system dimensioning tools capable ofassessing both the radio access and the core networkcomponents. Having found an attractive businessopportunity, system deployment must be preceded bycareful network planning. The network planning toolmust be capable of accurately modeling the systembehaviour when loaded with the expected trafficprofile. The third generation cellular systems will offerservices well beyond the capabilities of today'snetworks. The traffic profile, as well as the radioaccess technology itself form the two most significantchallenges when dimensioning and planning aWCDMA based third generation system. The trafficprofile describes the mixture of services being used bythe population of users. There are also specific systemfunctionalities which must be modelled including fastpower control and soft handover. In order to accuratelypredict the radio coverage the system featuresassociated with WCDMA must be taken into accountin the network modeling process. Especially thechannel characterization, and interference controlmechanisms in the case of any CDMA system must beconsidered. In WCDMA network multiple services co-exist. Different services (voice, data) have differentprocessing gains, Eb/N0 performance and thus differentreceiver SNR requirements. In addition to those theWCDMA coverage depends on the loadcharacterization, hand over parameterization, andpower control effects. In current second generationsystems' coverage planning processes the base stationsensitivity is constant and the coverage threshold is the

same for each base station. In the case of WCDMA thecoverage threshold is dependent on the number of usersand used bit rates in all cells, thus it is cell and servicespecific.The WCDMA planning process can be divided intothree phases: initial planning (dimensioning), detailedradio network planning and network operation andoptimization. Each of these phases requires additionalsupport functions like propagation measurements, KeyPerformance Indicator definitions etc. In a cellularsystem where all the air interface connections operateon the same carrier the number of simultaneous users isdirectly influencing on the receivers' noise floors.Therefore, in the case of UMTS the planning phasescannot be separated into coverage and capacityplanning. In the case of the post second-generationsystems data services start to play an important role.The variety of services requires the whole planningprocess to overcome a set of modifications. One of themodifications is related to the quality of service (QoS)requirements. So far it has been adequate to specify thespeech coverage and blocking probability only. Alsomore and more one has to consider the indoor and in-car coverage probabilities. In the case of UMTS theproblem is slightly more multidimensional. For eachservice the QoS targets have to be set and naturallyalso met. In practice this means that the tightestrequirement shall determine the site density. Inaddition to the coverage probability the packet dataQoS criteria are related to the acceptable delays andthroughput. Estimation of the delays in the planningphase requires good knowledge of the user behaviourand understanding in the functions of packet scheduler.Common features between second and third generationcoverage prediction also exist. In all the systems bothof the links have to be analyzed. In current systems thelinks tend to be in balance whereas in the case of thirdgeneration one of the links can be higher loaded thanthe other, and thus either one of the links could belimiting the cell capacity or coverage. The propagationcalculation is basically the same for all standards, withthe exception that different propagation models couldbe used. Another common feature is the interferenceanalysis. In the case of WCDMA this is needed for theloading and sensitivity analysis, in the case ofTDMA/FDMA it is essential for frequency allocation.In order to fully utilize the WCDMA capabilities, athorough understanding of the WCDMA air interface isneeded from the physical layer to the networkmodeling, planning and performance optimization.In this paper the pre-operational phase of the WCDMAplanning process, as depicted in Figure 1 in detail, is

discussed. Section II is concentrating on the initialplanning issues. The WCDMA link budget isintroduced and it is demonstrated how differentservices and their QoS requirements impact on the sitedensity estimate. In Section III a static radio networksimulator is introduced. The methodology required inthe coverage and capacity estimation for WCDMA isdescribed for both uplink and downlink. Topic ofSection IV is to demonstrate the accuracy ofdimensioning: an example area is dimensioned and theaverage site distance is determined. The dimensioningresult is compared with the outcome of a static networksimulation. In Section V the analysis methods of thestatic simulator are verified. The verification wasperformed with a dynamic system simulator. The paperis concluded in Section VI.

CoveragePlanning andSite Selection

ParameterPlanning

PropagationmeasurementsCoverageprediction

SiteacquisitionCoverageoptimisation

External InterferenceAnalysis

NetworkConfigurationandDimensioning

DEFINITION PLANNING AND IMPLEMENTATION

Traffic distributionService distributionAllowed blocking/queuingSystem features

IdentificationAdaptation

Area / Cellspecific

Handoverstrategies

Maximumnetworkloading

Other RRM

NetworkOptimisation

O & M

Surveymeasurements

Statistical performance analysis

Quality Efficiency Availability

Capacity Requirements

Requirementsand strategyfor coverage,quality andcapacity,per service

Figure 1. WCDMA Radio Network Planning process.

II. INITIAL PLANNING, SYSTEMDIMENSIONING

Initial planning (i.e. system dimensioning) provides thefirst and most rapid evaluation of the network elementcount as well as the associated capacity of thoseelements. This includes both the radio access networkas well as the core network. This paper focuses uponthe radio access part solely. The target of the initialplanning phase is to estimate the required site densityand site configurations for the area of interest. Initialplanning activities include radio link budget (RLB) andcoverage analysis, capacity estimation, and finally,estimation for the amount of base station hardware andsites, radio network controllers (RNC), equipment atdifferent interfaces, and core network elements. Theservice distribution, traffic density, traffic growthestimates and QoS requirements are essential alreadyin the initial planning phase. In the initial planningphase the quality is taken into account in terms ofblocking and coverage probability. RLB calculation isdone for each service, and the tightest requirementshall determine the maximum allowed isotropic pathloss.A. WCDMA specific items in the radio link

budgetIn this section the WCDMA uplink and downlinkbudgets are discussed. To estimate the maximum rangeof a cell a RLB calculation is needed. In the RLB theantenna gains, cable losses, diversity gains, fadingmargins, diversity gains etc. are taken into account.

The output of the RLB calculation is the maximumallowed propagation path loss which in returndetermines the cell range and thus the amount of sitesneeded. There are a few WCDMA specific items in thelink budget if one compares to the current TDMAbased radio access system like GSM. These includeinterference degradation margin, fast fading margin,transmit power increase and soft handover gain.The interference degradation margin is a function ofthe cell loading. The more loading is allowed in thesystem, the larger interference margin is needed inuplink, and the smaller is the coverage area. The uplinkloading can be derived as follows, for simplicity thederivation is performed with service activity v = 1.To find out the required uplink transmitted andreceived signal power for a mobile station MSkconnected to a particular base station BSn, the basicCDMA Eb/N0 equation is used. The usual, slightlytheoretical, assumption is that Ioth, the interferencereceived from the MSs connected to the other cells isdirectly proportional (proportionality constant i) to Iown,the interference received from the MSs connected tothe same BSn as the desired MS. Assume that the MSkuses bit rate Rk, its Eb/N0 requirement is ρk and theCDMA modulation bandwidth is W. Then the receivedpower of the k-th mobile, pk, at the base station it isconnected to, must be at least such that

n

kownkown

k

kothkown

k

k

Kk

NiIpIp

RW

NIpIp

RW

,...,1

,

=

≥���

�

��

�

�

++−=��

�

�

��

�

�

++−ρ

(1)

where Kn is the number of MSs connected to BSn,N = N0W = NfκT0W is the noise power in the case of anempty cell, Nf is the receiver noise figure, κ is theBoltzmann constant and T0 is the absolute temperature.

The inequalities in (1) are slightly optimistic because itis assumed that there is no interference from the ownsignal. In reality this is not exactly true in multipathpropagation conditions. Equation (1) is however stillchosen to avoid taking multipath interference intoaccount twice. I.e., the Eb/N0 requirements determinedfrom link level simulations are presented so that N0means only noise and multipath interference is visiblein higher Eb/N0 requirement to a certain BERperformance. Solving the inequalities as equalitiesmeans solving for the minimum required receivedpower (sensitivity), pk:

( )

KkN

RW

Ii

RW

p

NW

RIi

WR

WR

p

kk

own

kk

k

kkown

kkkkk

,...,1,1

1)1(1

1

11

=+

+++

=

�++=���

����

�+

ρρ

ρρρ

(2)

If the Equations in (2) are summed over the mobilestations connected to BSn then

���

�

�

��

�

�+

��

�

�

��

�

�+= ����

++Npip

k RW

kk

k RW

kk

kkkk ρρ1

1

1

1 )1(

��

�

�

��

�

�+−

��

�

�

��

�

�+

=+

�

�

�

+

+

)1(1

)1(

)1(

1

1

1

1

i

Ni

ip

k RW

k RW

kk

kk

kk

ρ

ρ (3)

since �=k

kown pI . If loading is defined as

)1(1

1 ik R

W

kk

+=�+

ρ

η (4)

this loading definition can be enhanced to includesectorisation gain, ζ, and service activity, ν:

)1(1

1 ζηνρ

⋅+=�+

ik R

Wkkk

(5)

In [12] the uplink loading is estimated using equation

)1(1

1 ijρjνm

j jRW

η +⋅⋅�

=⋅= (6)

where m is the number of services used. The differencebetween Equations (5) and (6) are due to the fact that(6) does not include sectorisation gain and that in thederivation starting from Equation (1) the denominatoris Iown - pk + iIown +N rather than Iown + iIown +N, whichis only the case when pk <<Iown.The downlink dimensioning is following the samelogic as the uplink. For a selected cell range the totalbase station transmit power ought to be estimated. Inthis estimation the soft handover connections must beincluded. If the power is exceeded either the cell rangeought to be limited, or number of users in a cell has tobe reduced. For downlink the loading (ηDL) isestimated based on

� �= ≠= �

�

�

�

��

�

�

��

�

�

�+−=

I

i

N

mnn ni

mii

iiiDL Lp

LpW

vR1 ,1

)1( αρ

η(7)

where Lpmi is the link loss from the serving BS m toMS i, Lpni is the link loss from another BS n, to MS i,ρi is the transmit Eb/N0 requirement for the MS i,including the SHO combining gain and the averagepower raise caused by fast power control, N is thenumber of base stations, I is the number of connectionsin a sector and αi is the orthogonality factor dependingon multipath conditions (α = 1: fully orthogonal).The term

�≠=

N

mnn ni

mi

LpLp

,1

defines the iDL.

Direct output of the downlink RLB is the single linkpower required by a user at the cell edge. The totalbase station power estimation must take into account

multiple communication links with average ( miLp )distance from the serving base station. Furthermore,the multicell environment with orthogonalities αishould be included in the modeling. More on thedownlink loading and transmit power estimations canbe found in [13]. In the RLB calculation in uplinkdirection the limiting factor is the mobile stationtransmit power, in downlink direction the limit is thetotal base station transmit power. When balancing theuplink and downlink service areas both links must beconsidered.The interference degradation margin to be taken intoaccount in the link budget due to a certain loading η(either in uplink or downlink) is

( )η−⋅= 1log10 10L (8)Fast fading margin or power control headroom isanother CDMA specific item in the RLB. Some margin

is needed in the mobile station transmission power formaintaining adequate closed loop fast power control inunfortunate propagation conditions like the cell edge.This is applicable especially for pedestrian users wherethe Eb/N0 to be maintained is more sensitive to theclosed loop power control. The power controlheadroom has been studied more in [6] and [7].Another impact of the fast power control is the transmitpower increase. In the case of a slowly moving mobilestation the power control is able to follow the fadingchannel and the average transmitted power increases.In own cell this is needed to provide adequate qualityfor the connection and does not cause any harm, sinceincreased transmit power is compensated by the fadingchannel. For neighbouring cells however this meansadditional interference. The transmit power increase(TxPowerInc) is used to reduce the reuse efficiencyaccording to Equation (9). In Equation (4) i should bereplaced with term TxPowerInc⋅ i in case the mobilestation transmit power increase is significant.

iTxPowerIncFr ⋅+

=1

1 (9)

Soft handover gain is discussed already in [3].Handovers – soft or hard − provide gain againstshadow fading by reducing the required fading margin.Due to the fact that the slow fading is partlyuncorrelated between cells, and by making handoversthe mobile can select a better communication link.Furthermore, soft handover (macro diversity) gives anadditional gain against fast fading by reducing therequired Eb/N0 relative to a single radio link. Theamount of gain is a function of mobile speed, diversitycombining algorithm used in the receiver and channeldelay profile. More about the SHO gain can be foundin Section II C.B. Receiver sensitivity estimationIn the link budget the BS receiver noise density isestimating the noise level over one WCDMA - carrier.The required receiver SNR contains the processinggain and the loss due to the loading. The loading usedis the total loading due to different services on thecarrier in question. The required signal power (S)depends on the SNR requirement, receiver noise figureand bandwidth.S SNR N W= ⋅ ⋅0 (10)where

)1( ηρ

−⋅⋅=W

RSNR (11)

and WTNWN f 00 κ⋅=⋅ (12)

where Nf is the receiver noise figure, κ is Boltzmannconstant, T0 is the absolute temperature and η is theloading. In some cases the basic noise/interferencelevel is further corrected with the man made noiseterm.C. Shadowing margin and soft hand over gain

estimationThe next step is to estimate the maximum cell rangeand cell coverage area in different environments/regions. The RLB is estimating the maximum allowed

isotropic path loss, from that value a slow fadingmargin, related to the coverage probability, has to besubtracted. When estimating the coverage probabilitythe propagation model exponent and the standarddeviation for the log-normal fading must be set. If theindoor case is considered the indoor loss is from 15 dBto 18 dB and the standard deviation for log-normalfading margin calculation is set to 10 - 12 dB. In thecase of outdoor coverage typical standard deviationvalue is 7 to 8 dB. Typical propagation constants rangefrom 2.5 to 4. Traditionally the area coverageprobability used in the RLB is for single cell case [1].The required probability is 90% to 95% and typicallythis leads to 7 - 8 dB fading margin, depending on thepropagation constant and standard deviation of the log-normal fading. The Equation (13) estimates the areacoverage probability for single cell case:

��

���

���

�

� ⋅−−⋅��

�

� ⋅⋅−+−=b

baerfb

baaerfFu1121exp)(1

21

2

(13)

Where 2

0

⋅−

=σ

rPxa and

2log10 10

⋅⋅⋅=

σ

enb , Pr is

the received level at cell edge, n is the propagationconstant, x0 is the average signal strength threshold andσ is the standard deviation of the field strength..In real WCDMA cellular networks the coverage areasof cells overlap and the mobile station is able toconnect to more than just one serving cell. If more thanone cell can be detected the location probabilityincreases and is higher than determined for a singleisolated cell. Analysis performed in [2] indicates that ifthe area location probability is reduced from 96% to90% the number of base stations is reduced by 38%.This number indicates that the concept of multiserverlocation probability should be carefully considered. Inreality the signals from two base stations are notcompletely uncorrelated, and thus the soft handovergain is slightly less than estimated in [2]. In [3] thetheory of the multiserver case with correlated signals isintroduced:

dxb

xaQeP SHOx

out

2

22

21

���

�

���

����

�

�

⋅⋅⋅−

= �∞

∞−

−

σσγ

π

(14)

where Pout is the outage at the cell edge, γSHO is thefading margin in the case of soft handover, σ is thestandard deviation of the field strength and for 50%correlation a = b = 2/1 . With the theory presentedfor example in [1] this probability at the cell edge canbe converted to the area probability. In the WCDMAlink budget the SHO gain is needed. The gain consistsof two parts: combining gain against fast fading andgain against slow fading. The gain against slow fadingis dominating and it is specified as:

SHOsingleG γγ −= (15)

If we assume 95% area probability, n = 3.5 and thestandard deviation is 7 dB the gain will be 7.3 dB -4 dB = 3.3 dB. If the standard deviation is larger andthe probability requirement higher the gain will bemore.

Table 1. Example of a WCDMA RLB.

UL DL

Transmitter power 125.00 a 1372.97 mW

20.97 b=10log10(a) 31.38 dBm

Tx antenna gain 0.00 c 18.00 dBi

Cable/body loss 2.00 d 2.00 dB

Transmitter EIRP (incl. losses) 18.97 e=b+c-d 47.38 dBm

Thermal noise density -174.00 f -174.00 dBm/Hz

Receiver noise figure 5.00 g 8.00 dB

Receiver noise density -169.00 h=f+g -166.00 dBm/Hz

Receiver noise power -103.13 i=10log10(W)+h

-100.13 dBm

Interference margin -3.01 j -10.09 dB

Required Ec/Io -17.12 k=10log10(Eb

/No/(W/R))-j-7.71 dB

Required signal power [S] -120.26 l=i+k -107.85 dBm

Rx antenna gain 18.00 m 0.00 dBi

Cable/body loss 2.00 n 2.00 dB

Coverage probability outdoor(requirement)

95.00 95.00 %

Coverage probability indoor(requirement)

0.00 0.00 %

Outdoor location probability(calculated)

85.62 85.62 %

Indoor location probability(calculated)

32.33 32.33 %

Limiting environment: outdoor outdoor

Log normal fade constantoutdoor

7.00 7.00 dB

Log normal fade constantindoor

12.00 12.00 dB

Propagation model exponent 3.50 3.50

Log normal fade margin -7.27 o -7.27 dB

Handover gain (inc. any macrodiversity combining gain at celledge)

0.00 p 2.00 dB

Slow fade margin -7.27 q=o+p -5.27 dB

Indoor loss 0.00 r 0.00 dB

TPC headroom (fast fademargin)

0.00 s 0.00 dB

Allowed propagation loss 147.96 t=e-l+m-n+q+r-s

147.96 dB

D. Cell range and cell coverage area estimationOnce the maximum allowed propagation loss in a cellis known, it is easy to apply any known propagationmodel for the cell range estimation. The propagationmodel should be chosen so that it optimum describesthe propagation conditions in the area. The restrictionsof the model are related to the distance from the basestation, the base station effective antenna height, themobile antenna height and the frequency. One typicalexample for macro cellular environment is Okumura-Hata. Equation (16) presents an example Okumura-Hata path loss model for an urban macro cell with basestation antenna height of 25 m, mobile antenna heightof 1.5 m and carrier frequency of 1950 MHz [4].

( )rLp 10log7.355.138 ⋅+= (16)

After choosing the cell range the coverage area can becalculated. The coverage area for one cell in hexagonalconfiguration can be estimated with:S = K⋅r2 (17)Where S is the coverage area, r is the maximum cellrange and K is a constant, depending on the networktopology. The number of sectors is typically from 1 to3. In the case of WCDMA reasonable values are up to6 sectors. In the case of 6 sectors the estimation of thecell coverage area becomes problematic, since a six-sectored site does not necessary resemble a hexagon. Aproposal for the cell area calculation at this stage is thatthe equation for the omni case is used also in the caseof 6 sectors and the larger area is due to a higherantenna gain. The more sectors are used the morecareful soft handover overhead has to be analysed toprovide an accurate estimate. In Table 2 some of the K-values are listed.

Table 2. K-values for the site area calculation.

SITECONFIG.

1 omni 2-sectored 3-sectored 6-sectored

K 2.6 1.3 1.95 2.6

E. Capacity and coverage analysis in the initialplanning phase

Once the site coverage area is known the siteconfigurations in terms of channel elements, sectorsand carriers, and site density (cell range) has to beselected so that the supported traffic density can fulfilthe requirements. An example dimensioning case canbe seen in Section IV. The WCDMA RLB is slightlymore complex than the TDMA one. The cell rangedepends on the number of simultaneous users (numberof channels/users in terms of interference margin, seeEquation (6)). Thus the coverage and capacity areconnected and already in the very beginning theoperator should have knowledge and vision of thesubscriber distribution and growth since it has a directimpact on the coverage. Finding the correctconfiguration for the network so that the trafficrequirements are met and the network cost minimisedis not a simple task. The number of carriers, number ofsectors, loading, number of users and the cell range allhave an impact on the result.

III. DETAILED PLANNING PROCESS

A. Introduction to a static radio networkplanning simulator

In this study the simulator first introduced in [9] wasused. It is of static nature and needs as inputs a digitalmap, the network layout and the traffic distribution inform of a discrete user map. Each of the users can havedifferent terminal speed and uses a different service(bit rate, activity factor, which both can be different foruplink and downlink). Therefore each mobile stationgets assigned an individual Eb/N0 requirement importedfrom link level simulations. The simulator itself

consists of basically three parts – initialisation,combined uplink and downlink analysis and postprocessing phase. Following the initialisation part,round after round in the main part of the tool, both theuplink and downlink for all mobile stations areanalysed and after the iterations have fulfilled certainconvergence criteria, in the final step, the results of theuplink and downlink analyses are post processed forvarious graphical and numerical outputs. On top ofthese results, for selected areas (which also can consistof the whole network) area coverage analyses for ULand DL dedicated channel as well as for commonchannels (common pilot CPICH, broadcast controlchannel BCCH, forward access and paging channelFACH and PCH on the P-CCPCH and S-CCPCH) canbe performed. In case a second carrier is present in thenetwork area, either used by the same operator or byanother operator adjacent channel interference (ACI)can be taken into account. Only in case the secondcarrier is assigned to the same operator, load can beshared according different strategies between thecarriers (IF-HO).

global Initialisation

uplink iteration step

downlink iteration step

coverage analyses

combined UL/DLiteration

Initialise Iterations

Initislisation phase

graphical outputs

post processing

post processingphase

E N D

Figure 2. Static simulator overview.

B. Initialisation PhaseIn the global initialisation phase the networkconfiguration is read in from parameter files for basestations, mobile stations and the network area. Somesystem parameters are set and propagation calculationsare performed. In the following step, requirementscoming from the link level simulations are assigned tobase stations and mobile stations. After someinitialisation tasks for the iterative analysis – settingdefault transmit powers and network performance - theactual simulation can start.C. Combined uplink and downlink analysis

C1. Uplink iteration stepThe target in the uplink iteration is to allocate themobile stations’ transmit powers so that the(interference+noise)-levels and thus the base station

sensitivity values converge. The average transmitpowers of the mobile stations to each base station areestimated so that they fulfil the base stations Eb/N0requirements. The average mobile stations’ transmitpowers are based on the sensitivity level of the basestation, service (data rate) and speed of the mobilestation and the link losses to the base stations. They arecorrected by taking into account the activity factor, thesoft handover gains and average power raise due to fasttransmit power control. The impact of the uplinkloading on the base station sensitivity (noise rise) istaken into account by adjusting it with (1-η). η can bedefined by Equation (5).After the average transmit powers of the mobiles havebeen estimated they are compared to the maximumvalue allowed and mobiles exceeding this limit aretrying IF-HO if allowed or are put to outage. Now theinterference analysis can be performed again and thenew loading and base station sensitivities arecalculated until their changes are smaller than specifiedthresholds. Also in case the uplink loading of a cellexceeds specified limits, mobile stations are moved toanother carrier if allowed (IF-HO). Otherwise they areput to outage.C2. Downlink iteration stepSimilarly to the uplink the goal of the downlinkiteration is to assign the base station transmit powersfor each link (including SHO connections) a mobilestation is having until all mobile stations receive theirsignal with the required carrier-to-interference-ratio,C/I, defined by Equation (18).

RWEbNotargetCI MS

/= (18)

where EbNoMS is the received Eb/N0 requirement of theMS depending on terminal speed and service. Theactual received (C/I)m of MS m is calculated usingMRC according Equation (19) by summing the C/Ivalues of all links k, k=1...K mobile station m is having.

�= ++−−

=���

����

� K

k mkothkmkmmkk

kmkm

m NILppvPLpp

IC

1 ,))(1( α(19)

where Pk is the total transmit power of the base stationto which link k is established, Lpkm is the link loss fromthe cell k to the mobile station m, αk is the cell specificorthogonality factor, pkm is the power allocated to thelink from base station k to mobile station m, Ioth,m is theother cell interference and Nm is the background andreceiver noise of MS m.The initial transmit powers are adjusted iterativelyaccording the difference between the achieved and thetargeted C/I value until convergence is achieved. Theprocess requires iteration, since the C/I at each mobilestation is dependent on all the powers allocated to theother mobile stations and it is not known a prioriwhether a link can be established or not. In case eithercertain link power limits or the total transmit power ofa base station is exceeded mobile stations areperforming IF-HO if allowed or taken out randomlyfrom the network.

In a further step for each mobile station it is checkedwhether the received Ec/I0 value is above a user definedthreshold so that the mobile station can reliablymeasure the base station and synchronise to it. Alsohere if the threshold given is exceeded, the mobilestation tries IF-HO or is put to outage. A flow chart forthe detailed iteration steps can be seen from Figure 3.

set oldThresholds to thedefault/new coverage thresholds

RlbUL.mcalculate new coverage thresholds

ReduceLoad.m - DoIFHO.mDoSaattohoito.m

check UL loading and possibly moveMSs to new/other carrier or outage

CalcSiteLinks.m - ReduceLinks.mcheck hard blocking and possibly take

links out if to few HW resources

Evaluate UL break criterion

CalcMsTx.mcalculate adjusted MS TX powers,

check MSs for outage

CalcIntUL.mcalculate new i=Ioth/Iown

Flow chartUplink iteration step

BestServerUL.mConnect MSs to best server, calculateneeded MS TxPower and SHO gains

DL iteration step

no convergence

post processing

E N D

Initialisation

convergence

check UL andDLbreak criteria

adjust TX powers of each remaininglinks according to deltaCI

update deltaCIold

fullfilled

Flow chartDownlink iteration step

CalcIntDL.mcalculate the C/I for each connection

calculate C/I for each MS

CalcMsSHOgainsDL.mcalculate the SHO diversity combining

gains; adjust the required change to C/I

UL iteration step

initialise deltaCIold

PerchPowAlloc.mallocate the Perch channel powers

BestServerDL.mcalculate the received Perch levels and

determine the best server in DL

RlbDL.mcalculate the MS sensitivities

BStxPowAlloc.mcalculate initial TX powers for all links

CalcSHO2.mdetermine the SHO connections

calculate target C/I's

CalcEcIoM.mcalculate CPICH Ec/Io for all MSs

CheckEcIoCoverage.mcheck Ec/Io, perform IFHO or put

MSs to outage

not fullfilled

Global Initialisation

Initislise Iterations

post processing

E N D

Figure 3. Flowcharts for the UL and DL iteration steps.

C3. Adjacent channel interference calculationsThe adjacent channel interference influence due to thetwo possible carriers – either from own network orfrom a competitive operator's network in the same area- is taken into account by filtering this interferencewith a channel separation dependent filter. In bothdirections UL and DL the adjacent carrier filtering isimplemented as a two-fold process. In UL, one filterfor the mobile stations has been implementedindicating its out of band radiation (acpFilterUL). Thisfilter is used to indicate how much power the mobile

station is leaking into the other carriers receiving band(Adjacent Channel Leakage Ratio, ACLR). For the basestation in the uplink another filter (aciFilterUL) hasbeen implemented. This filter is indicating theselectivity of the base station’s receiver in multicarriersituation, i.e. how big portion of the adjacent channelpower is received by the base station as adjacentchannel interference power (Adjacent ChannelProtection, ACP). Also this filter setting depends onthe carrier separation. The adjacent channelinterference situation in UL is depicted in Figure 4. Inthe simulations these two filters are combined to asingle filter by Equation (20):

��

�

�

��

�

�+⋅= 1010

10 1010log10LacpFilterU

-LaciFilterU

- - acFilterUL (20)

f1 f2 f1 f2

f1 f2

Rx Rx

Ptx

Frequency 1 Frequency 2

BS selectivity

wanted signal

MS ACLR

BS ACP

0 dB

0 dB

f1 f2

Ptx

MS leakage

MS ACLR

0 dB

Figure 4. UL adjacent channel interference situation.

Adjacent channel interference (IACI) is taken intoaccount when calculating the UL load according toEquation (21).

NIIIIII

ACIothown

ACIothown

+++++

=η (21)

Also in the downlink similar type of filtering isintroduced as in the uplink. One filter for the basestations has been implemented indicating the out ofband radiation of the base station (acpFilterDL). Thisfilter is used to indicate how much power the basestation is leaking into the other carriers receiving band(ACLR). The filter setting depends on the separationbetween the carriers. For the mobile station anotherfilter has been implemented (aciFilterDL). This filter isindicating the selectivity of the mobile station'sreceiver in multicarrier situation, i.e. how much of theadjacent channel interference power is received by themobile station (ACP). Also this filter setting dependson the carrier separation. The adjacent channelinterference situation in DL is depicted in Figure 5. Inthe simulations these two filters are combined to asingle filter by Equation (22):

��

�

�

��

�

�+⋅= 1010

10 1010log10LacpFilterD-LaciFilterD-

- acFilterDL (22)

Adjacent channel interference (IACI) in DL is taken intoaccount when calculating the C/I of a single link a MSis having according to Equation (23).

�= +++−−

=���

����

� K

k mACIkothkmkmmkk

kmkm

m NIILppvPLpp

IC

1 ,))(1( α(23)

where variables are as defined after Equation (19), Iothis interference from other cells on same carrier and IACIis adjacent channel interference.

f1 f2 f1 f2

f1 f2

Ptx Ptx

Rx

Frequency 1 Frequency 2

BS leakage

MS selectivity

wanted signal

BS ACLR

MS ACP

0 dB

0 dB

f1 f2

Rx

MS ACP

0 dB

Figure 5. DL adjacent channel interference situation.

D. Predicting the network coverageIn all estimations of area coverage probability (UL, DLDCH, CPICH, BCH, FACH, PCH) it is assumed thatthe interference situation is stable. This means that acertain traffic distribution has been assumed and thedetailed UL and DL iteration has been run. A testmobile is then run through all pixel of the interestingarea and all other MSs which could be served arecontributing to the interference. The test mobile is notinfluencing on the interference situation, therefore theother to own cell interference ratio will not change andalso the total transmit power of the serving BSs areconstant.

UL DCH coverageIn UL direction now it can be estimated whether or notthis additional mobile station using a certain bit rateand having a certain Eb/N0 requirement could get theservice in the chosen geographical location. Thismeans, if the maximum allowed transmit power of thetest MS is enough to fulfil the Eb/N0 requirement at theBS receiver. The needed transmit power for the MS iscalculated with Equation (24) and compared to themaximum allowed.

( ) ���

����

�

⋅⋅+⋅−⋅

⋅=

νρη

RWv

LpNP MSTX

11

0, (24)

Area coverage probability finally is defined as theproportion of the chosen area where the additional MSreally gets the wanted service under that stableinterference situation. The weakness in this approach isthat in reality an additional mobile station wouldchange the interference situation, for example someother mobiles could go to outage but in the case of lowbit rate services this effect can be neglected.

DL DCH coverageIn downlink direction the coverage probabilitycalculation is based on the transmit power limits perradio link. The main focus is to check pixel-by-pixel,whether or not there is enough transmit power per linkfrom base stations in the active set, if there would be a

MS in the pixel, using a given service (bit rate) andhaving a given speed. Also here it is assumed that thetotal transmit powers of BSs do not change from whatwas left after UL/DL iteration, i.e. it could be assumedthat the influence of the test MS is replaced by theclosest original MS. In iteration however there may ormay not have been a MS in the pixel. The coverageprobability then again is defined as the amount ofpixels from the whole area where the service waspossible.

CPICH coverageIn radio network planning the CPICH transmit powershould be set as small as possible but ensuring that thebest cell and neighbour cells can be measured andsynchronised and the CPICH can be sufficiently usedas the phase reference for all other DL physicalchannels. Typically this means that 5% - 10% of thetotal BS power is used for CPICH. For each pixel inthe chosen area the Ec/I0 in that pixel is calculatedaccording Equation (25).

01

, NILpP

LpPCPICHecioACI

numBSs

iiiTX

CPICH

++=�

=

(25)

where PCPICH is the CPICH power of the best server, Lpis the link loss to the best server, PTX,i is the totaltransmit power of BS i, Lpi is the link loss to BS i, IACIis adjacent channel interference, N0 is the thermal noiseof the default MS and numBSs is the number of basestations in the network. The achieved Ec/I0 is thencompared to a user given threshold and the CPICHcoverage defined as the ratio of pixels where thethreshold is exceeded compared to all pixels. Theweakness of this modeling for the CPICH Ec/I0coverage is that it is done only for the best server. In anoperating network however, all neighbour cells mustalso be measured and therefore all neighbour cells'CPICH Ec/I0 should be analysed, too. This could beovercome however by e.g. adding a threshold to therequired CPICH Ec/I0. Descriptions of other staticsimulators can be found for example in [18], [19].

IV. EXAMPLE DIMENSIONING CASEAND VERIFICATION OFDIMENSIONING WITH STATICSIMULATIONS

This section is containing an example use case for theinitial planning phase in case of a green fieldmacrocellular operator. In this example case only onenetwork evolution phase is considered, in the real radionetwork planning case the traffic growth should bemore carefully considered. In this work three caseshave been analysed. First case is 8 kbps speech only,mobile station speeds 3 (50% of MSs) and 120 km/h(50% of MSs). Second case is dimensioning speechand circuit switched data (64 kbps), speech mobilesmoving 50 km/h, data terminals 3 km/h. The last caseis 144 kbps data only, terminals moving with 20 km/h.More details related to the case can be found in [14].The study consisted of two parts. In the first part the

operator's macrocellular network is dimensioned, i.e.the cell range is estimated with given input parameters.This study is based on the assumption that the trafficand the QoS information are available from theoperator. In the second phase the network is plannedfor the estimated site distance (1.5*R) and theWCDMA analysis is performed for the radio network.As depicted in Figure 1 this use case is concentratingon the first half of the radio network planning process:the network dimensioning, network configurationdefinition and coverage/capacity planning.In the first phase the dimensioning task is to generatecertain traffic and QoS requirements for the abovementioned three cases and to dimension the casesaccordingly. The radio network was dimensioned foran urban area of 13 x 13 km2. The propagation modelused was Okumura-Hata with an area correction factorof 0 dB. The traffic and QoS requirements for all thethree cases are in Table 3.

Table 3. The traffic and QoS requirements and otherdimensioning parameters.

SPEECH SPEECHAND 64KBPS CSDATA

144 KBPSPACKETDATA

Subscribers 60000 60000,12000

24000

Averagetraffic/subscriber

0.060 Erl 0.040 Erl ,0.025 Erl

3 kbps

Blocking 2% 1% -Coverage probability 95% 95%/70% 80%Data activity 50% 50% 100%Assumed soft capacity 20% 10% 10%SHO overhead 40% 40% 40%Maximum uplinkloading

60% 65% 65%

MS/BS transmitpower

24/43 dBm 24/43 dBm 24/43 dBm

Common channeloverhead

10% 10% 10%

Antenna gain MS/BS 0/17 dBi 0/17 dBi 0/17 dBiCable/body loss 3/0 dB 3/0 dB 3/0 dBMS speed 3 km/h

120 km/h50 km/h, 3 km/h

20 km/h

Std for the log normalfading

7 dB 7 dB 7 dB

Peak to average ratiofor total BS powercalculation

4 dB 4 dB 4 dB

Average orthogonality 50% 50% 50%i and iDL 55% 55% 55%BS antenna height 30 m 35 m 35 m

In the dimensioning process both the capacity and thecoverage have to be considered. The cell range isdetermined not only by the RLB, but also on thecapacity requirements. From the selected cell range thecoverage area for the site can be estimated by Equation(17). Once the site coverage area is known thesupported traffic density can be estimated. The selectedsite density must be such that the traffic densityrequirement and the coverage requirement in terms of

coverage probability are met. In the following table thedimensioning results are collected. In the example casethe cell range has been solely based on the uplinkresults. In uplink direction the target loading asspecified by Equation (6) is limiting the number ofchannel elements per cell. As it can be seen already inthe dimensioning results, the base station transmitpower is actually limiting in all of the cases. In order tomeet the capacity requirements either cell range,number of sectors or number of carriers should bechanged. In this case only one carrier was used.

Table 4. Dimensioning results.

SPEECH SPEECHAND 64KBPS CSDATA

144 KBPSPACKETDATA

Selected cell range 2.08 km 1.98 km 1.52 kmUplink loading 0.32 3 km/h

0.29 120 km/h0.40 speech0.18 data

0.65 data

Service limitingthe cell range

Speech 3 km/h 64 kbps data 144 kbps data

Number of channelelements per cellrequired to meetthe capacity basedon UL

30 3 km/h30 120 km/h

42 speech 6 data

855.6 kbpsthroughput ~6 datachannels

Number of channelelements per cellsupported by DL

21 3 km/h19 120 km/h

27 speech 6 data

5 data

Required numberof 3-sectored sites(based on UL)

20 (60 cells) 22 (67 cells) 37 (112 cells)

In the second phase of the work the dimensioningresults in terms of number of cells and the cell rangewere used in the corresponding static simulator runs.The items with bold font in Table 3 and Table 4 wereused as inputs for the simulation. The site distance usedin the static simulator has been estimated withD = 1.5*R where R is the cell range obtained from theRLB in dimensioning. In this study the networkscenario was based on a regular grid, and the networkarea consisted only of urban area type. The staticsimulator described in Section III was used in thisstudy. The Eb/N0 requirements and the trafficdistribution used in the simulation were the same aswere used during dimensioning. In the dimensioningphase only the antenna gain is used. In the simulationsthe antenna radiation pattern is also required and anantenna with 65° horizontal beamwidth was selected.The 65° antenna was selected because it is widely usedalready in 2G networks with three sectoredconfigurations. Furthermore, according to [11] the 65°provides the optimum performance for the usednetwork configuration. In all the simulations theantenna gain was always 17 dBi. The soft handoveraddition window was set to –6 dB. In Figure 6 there isan example of the network scenario. The systemfeatures used in the simulations are from [10] and theITU vehicular A channel [5] has been assumed for thechannel delay profile.

According to the simulations in the speech case thedimensioning is too pessimistic for the uplink capacity.Based on the simulations the network could support 72speech users versus the 60 proposed by dimensioning.The main difference is because of the interferencestatistics. The other to own cell interference ratio hasrelative large standard deviation (0.27, minimum valueonly 0.11) and thus there are cells which can carrymore traffic than Equation (6) is proposing. With thehelp of the results in Table 5 it can be concluded thatcurrent dimensioning is correctly limiting the downlinkcapacity. According to the simulations with 65°antenna the downlink should serve 46 users, thedimensioning is proposing 40. The simulated coverageprobability is slightly higher than the requirement, andthus the site distance in reality could be slightlyincreased.

Figure 6. Example of a network scenario. Mixed trafficcase.

In the mixed traffic case the uplink dimensioning resultwas proposing 42 channel elements for speech usersand 6 for data users to meet the traffic requirement.The UL simulation result is slightly different from thedimensioning result. The reason for this is partly that itis very difficult to control the simulation run so that theratio of the data users and the speech users would beexactly as required. The initial requirement was thatthe data users are 17% of the total users. After thestatic simulator run the percentage was 16%. In thecase of UL there are in average 37 speech users insteadof 42, but on the contrary there are 8 data users insteadof 6. Therefore one can claim that the uplinkdimensioning result is well in line with the simulationresults. The power amplifier dimensioning for the DL(based on [13]) shows a clear downlink limitation. Theuplink 48 users cannot be served in downlink directionwith the assigned 20 W maximum base station transmitpower. When the number of users in the dimensioningwas reduced to 27 speech and 6 data users thedimensioning estimates the total TX power of 17 Wincluding 10% common channel overhead. Values usedfor the power calculation were iDL (=

�≠=

N

mnn ni

mi

LpLp

,1

, see

[13]) 55% and peak to average ratio for Lpmi of 4 dB.The downlink is limiting also according to the networksimulations. According to the simulation downlinkanalysis the network can support 25 speech users and

roughly 5 64 kbps data users simultaneously, the basestation total transmit power being 19 W to 20 Wdepending on the selected scenario. In the mixed trafficcase the dimensioning of the base station total transmitpower follows extremely well the simulations. In termsof coverage probability the dimensioning is slightlypessimistic. According to the simulations the datacoverage probability is always better than the required70%. Since the data service is limiting the cell rangethe speech coverage probability is always better thanthe required 95%.In the data case the dimensioning was proposing855.6/144 = 5.94 simultaneous users (assuming 10%soft capacity, and iDL = 55%). This result is very closeto the simulated case, but also in this case the uplinkdimensioning is slightly pessimistic. In the downlinkdimensioning with iDL = 55%, orthogonality 50% and4 dB peak to average ratio the BS transmit power forthe 5 users is roughly 19 W, including commonchannels (10% overhead) and 40% soft handoverprobability. A similar number is also achieved with thestatic simulations. In the data case the coverageprobability is up to 8% higher than required. Thedifference in decibels of coverage probability of 80%and 88% is 2 to 3 dB, depending on the exactparameter values that have been used in theestimations, see [1]. In coverage limited case this hasan impact on the required number of sites. Allsimulation results are collected in Table 5.

Table 5. Simulation results. Only the average results(averaged over all the cells) are included.

SPEECH SPEECHAND 64KBPS CSDATA

144KBPSPACKETDATA

Antenna 65°, site distance D = 1.5*RNumber ofusers UL

35 3 km/h36 120 km/h

37 speech 8 data 7

Number ofusers DL

23 3 km/h23 120 km/h

25 speech 5 data 5

UL coverageprobability

96.3% 3 km/h98.8% 120 km/h

97.6%74.4% 87.5%

Other to owncell interference 0.65 0.62 0.75

Loading 0.58 0.67 0.62BS transmitpower/W 19.34 18.95 19.10

In Figure 7 there is an example of the dominance andcoverage analysis plot for speech services, test mobilespeed 50 km/h. In the dimensioning the usedrequirement for speech was 95%.For mixed traffic (speech and 64 kbps) case theprobabilities are 98% and 70% respectively. Since dataservices are limiting the range the actual coverageprobability for speech was higher, i.e. 98%. Similaranalysis for the RT data gave 68% coverageprobability. In the dimensioning the used requirementwas 70%.

The results presented here demonstrate that inmacrocellular environment the downlink dimensioningis essential, due to the fact that with the assumptions ofthe macrocellular environment and Vehicular Achannel conditions the network is downlink limited.

Figure 7. Example result of the mixed traffic case. Thecoverage probability for speech services.

Uplink dimensioning alone gives too optimisticcapacity predictions for the network. Furthermore, themodeling proposed for the dimensioning is verifiedwith static network simulations. The comparison of thesimulation results and the dimensioning results showgood agreement.

V. COMPARISON OF A STATIC TO ADYNAMIC NETWORK SIMULATOR

The scope of this section is to demonstrate that theaccuracy of the static simulator is adequate for radionetwork planning purposes.A. Introduction to the dynamic simulatorTypically the system level simulators operate with theresolution determined by the feature that changesinterference situation most often. In WCDMA the fastclosed loop power control operating with 1.5 kHzfrequency is the algorithm having the highestfrequency, and therefore, 1.5 kHz frequency is used inthe system simulator used in the comparison.Conventionally, the information obtained from the linklevel tool is linked to the system simulation by using aso-called average value interface describing the BLERperformance by average Eb/N0 requirements. Theaverage value interface is not accurate if there are fastchanges in the interference due to, e.g. high bit ratepacket users. This kind of approach suits well for staticsnap-shot simulations, but cannot be used whensimulating systems with fast power control and high bitrate packet data. With the presented dynamic simulatorhowever, a so-called actual value interface (AVI) isused that provides accurate modeling of fast power andhigh bit rate packet data [16].In the dynamic simulator the users are making callsand transmitting data according to the traffic models.The call generation process for real time services, suchas speech and video, is made according to a Poissonprocess [15], [17]. For speech, voice activity anddiscontinuous transmission have to be considered. For

circuit switched data services, the traffic model is aconstant bit rate model, with 100 % of activity.The calculation of interference is an essential processof the system simulator. The better the interferencemodeling is, the more accurate results can be obtained.The total interference power Ibs(k) received by a basestation k is calculated as follows:

��

�

≠=

=

=

����

�

�

����

�

�

⋅⋅=N

mnn

nmsJ

nkni

J

ikni

knkbs pg

gLpI

1)(

1,,

1,,

,)(

ˆ

(26)

where N is the total number of active mobile stations inthe system and m is index for the observed user. Lp

n,k is

path loss (attenuation due to distance and slow fading)between the base station k, and the mobile station n.

�� gg ˆ is the multipath fading normalized to havinglong term average equal to one and J is the number ofmultipath components. pms(n) is the transmission powerof the mobile n. After the interference calculations, theuplink signal-to-noise ratio SNRUL can be calculated forthe user m connected to the base station k as

�= +

⋅⋅=

J

i kbs

immskmUL NI

apGSNR

1 )(

2)(

),( (27)where G is the processing gain, ai is amplitudeattenuation of path i and J is the number of allocatedRAKE fingers. In (27) it is assumed that the receivedsignals are combined coherently with maximal ratiocombining. In downlink the effect due to orthogonalcodes has to be considered. Because of the multipathpropagation perfect orthogonality cannot be assumed.For optimal maximal ratio combining, the downlinksignal-to-noise-ratio SNRDL for a user m can becalculated as

� �= = ⋅−

⋅⋅=

M

k

J

i ikkbsmms

ikkmbsmDL

k

aPIapG

SNR1 1

2,)()(

2,),(

)( )( (28)

where Ims(m) is the total interference power received bythe mobile station m, M is number of base stations inthe active set, pbs(m,k) is the transmitting power for theobserved user from the base station k, Pbs(k) is the totalpower transmitted from the base station k, ak,i isamplitude attenuation of the channel tap i and Jk is thenumber of allocated RAKE fingers from base station k.In the dynamic simulator following items weremeasured: Bad quality calls, defined as calls having anaverage frame error rate FER exceeding a threshold(usually 5% for speech). The minimum call duration isset to 7 seconds in order to increase the confidence ofthe averaging. Statistical data of these calls arerecorded such as coordinates, start and end time andthe call duration. Dropped calls, i.e. calls that haveconsecutive frame errors that exceed a threshold(usually 50 frame errors). Usually dropped calls areconsidered as severely poor quality calls. So badquality and dropped calls can be taken as one measurewhose percentage is referred to the number of startedcalls after the warm-up period. Power outage – forspeech, this is taken from active terminals includingthose that are in DTX. Therefore it is slightly distorteddue to the other half of the users that are in DTX. So

the actual outage for terminals that are actively"talking" is higher. Rough value is twice than that ofthe output. There is no discrepancy for data. Eb/N0targets is taken from all active terminals includingthose in SHO. So all factors regarding the channel anddiversity are taken into account. Finally SHOprobability histogram of the number of branches peruser was collected.From the static simulator for all UL and DLconnections the histogram of the transmit powers andtheir cumulative distribution function are taken.Moreover the p-th percentiles Qp for 0, 50, 75, 90, 95and 100% are extracted. Statistics showing the numberand type of SHO connection were gathered. For thewhole simulated area the estimated active set size (ASsize) is collected (based on the CPICH levels.) In eachsimulated case also the UL loading level was stored.In the final comparison the total traffic per cell, ULpower distribution [dBm], DL total/link powerdistribution [dBm], SHO statistics, SHO areas, celldominance areas, and not served mobiles (static) versusdropped and bad quality calls (dynamic) were ofinterest.B. Comparison resultsIn this section some of the comparison results arecollected. Main conclusion is that the cells level results(for example loading) are in good agreement with boththe simulation methods. In Figure 8 the number oflinks is depicted cell by cell. It can be seen that thenumber of links per cell follows the same trend.

1 4 7

10 13 16 19 22 25 28 31

staticdynamic0

20406080

100120140160180

links

cell

Served linksspeech

1 4 7

10 13 16 19 22 25 28 31

staicdynamic0

10

20

30

40

50

60

links

cell

Served linksdata

Figure 8. Number of links per cell for static simulatorand dynamic simulator cell by cell.

In the following figure the difference of the celldominance areas as seen by the two differentsimulators is depicted. It can be stated that the

difference is minor. In 90-95 % of all the pixels bothsimulators propose same dominant cell.

Figure 9. Dominance difference in speech case.

The uplink power distribution statistics are collectedfor speech and data case in Table 6. The maximumvalues do not differ significantly, but some of thepercentile-values are well apart. This could indicatedifferent power distribution shapes for the twosimulators. This cannot be avoided due to the differentnature of the simulators.

Table 6. UL Power distribution difference.

MIN Q50 Q75 Q90 Q95 MAX

Speech case

Static s.[dBm] -44 -10.38 -1.37 5.81 10.95 20.39

Dyn. s. [dBm] -49 -14.5 -7 0 4.5 20

diff [dB] -5 -4.12 -5.63 -5.81 -6.45 -0.39

Data case

Static s.[dBm] -41.79 -0.08 7.1 13.59 15.77 20.03

Dyn. s. [dBm] -44 -3 6 15 19 20

diff [dB] -2.21 -2.92 -1.1 1.41 3.23 -0.03

In downlink direction the transmit power statisticswere collected. The comparison results are collected inTable 7. The difference in downlink direction hassimilar trend as in uplink.

Table 7. DL Power distribution difference.

MIN Q50 Q75 Q90 Q95 MAX

Speech case

Static s.[dBm] 8.25 13.58 16.12 18.37 18.98 24.14

Dyn. s. [dBm] -1 12.5 16.5 20 21.5 24

diff [dB] -9.25 -1.08 0.38 1.63 2.52 -0.14

Data case

Static s.[dBm] 18.91 24.01 24.8 25.57 25.83 26.29

Dyn. s. [dBm] 7 25 25.5 25.7 25.8 26

diff [dB] -11.91 0.99 0.7 0.13 -0.03 -0.29

The (downlink) link power distributions for the twosimulators in speech case are depicted in Figure 10.

The shapes of the distributions are close to each other.In case of data the variance is larger.

Figure 10. Link power distributions. Top figure for thestatic simulator (ave Ueta = average UL loading).

Another important result is the soft handover behaviourin the simulators. In Table 8 soft handover statisticsfrom the data simulations have been collected.

Table 8. Handover comparison – 64 kbps CS data case.

HANDOVER TYPE SHO1-way 2-way 3-way OVERHEAD

static sim.[%] 83.7 14.9 1.4 17.7

dyn. sim. [%] 72 23 5 33

In addition to the soft handover overhead the differencein active set sizes were investigated. These results aredepicted in Figure 11.

Figure 11. AS size difference in speech case.

In a radio network planning phase it is important toidentify the outage areas of the network. In this study

the outage prediction of the static radio networksimulator was compared to the result from the dynamicsimulator. Main conclusion of this case is that theproblems have the tendency to be distributed roughlyin the same locations for either static tool or dynamicone. The number of problematic calls cannot bedirectly compared to each other.

VI. CONCLUSION

In this work the radio network planning process andmethods for WCDMA networks were introduced andverified. Accuracy of the tools is essential to providean operator with reasonable information of the requirednetwork topology and hardware requirements. In thiswork initial planning phase (dimensioning) methodswere introduced. Furthermore the dimensioning resultswere compared with results proposed by staticsimulator. The comparison of the static simulationresults and the dimensioning results show goodagreement. In general it can be stated that the proposeddimensioning methods perform with reasonableaccuracy in cases where the traffic distribution is suchthat the network can serve several simultaneous usersin each cell. In case of high bit rate services thenetwork performance is strongly dependent on thelocation of the mobile users and the generalinterference situation, therefore it can be stated thatalso the proposed dimensioning modeling will performwith degraded accuracy. In case of high bit rateservices with low number of connections the proposedmethods would underestimate the required BS powertoo much giving only a long-term average. One way toovercome this problem would be to use the worst caseparameter values (cell edge) for the most demandingservices.Further, it has been demonstrated that static radionetwork planning simulator is giving a realisation ofthe network, which is close to the network analysed bythe fully dynamic simulator. Generally the tools areresulting in similar picture of the network. The uplinkand downlink power distributions as well as the cellloading levels and supported links per cell arefollowing the same trends. Problem zones in thenetwork (dropped/bad quality calls, outage etc.) occurin the same locations in both analyses. Handoverprobabilities, active set sizes and dominance areas arealmost the same in both tools. Nevertheless, a statictool is suitable for network planning. Dynamicsimulator however is superior for benchmarking ofradio resource management algorithms and foranalysing of the dynamic phenomena in the networks.The reason is not only in the computation complexityof the dynamic one but also in the fact that the dynamictool is "not calibrated", i.e. that the call drop rate isdependent on dropping criteria and thus the numbercannot be taken as exact absolute value. The numbercould be just compared with different simulation withthe same dropping criterion.

Acknowledgements

The authors would like to thank all their colleagues,especially Mr. Kari Sipilä, Dr. Ari Hämäläinen and Dr.Tomáš Novosad for support and valuablecontributions.

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