Admission Control and Downlink Scheduling forAdvanced Antennas in WCDMA

Master of Science Thesis written at Ericsson Radio Systems ABand Linköping Institute of Technology

by

Jonas Brorsson

Reg nr: LITH-ISY-EX-3239

Admission Control and Downlink Scheduling forAdvanced Antennas in WCDMA

Master of Science Thesis written at Ericsson Radio Systems ABand Linköping Institute of Technology

by

Jonas Brorsson

Reg nr: LITH-ISY-EX-3239

Supervisors: Johan Lundsjö, Ericsson Radio Systems ABErik Geijer Lundin, Linköping Institute of Technology

Examiner: Fredrik Gunnarsson, Linköping Institute of Technology

Linköping, February 27, 2002

Avdelning, InstitutionDivision, Department

Institutionen för Systemteknik581 83 LINKÖPING

DatumDate2002-02-27

SpråkLanguage

RapporttypReport category

ISBN

Svenska/SwedishX Engelska/English

LicentiatavhandlingX Examensarbete ISRN LITH-ISY-EX-3239-2002

C-uppsatsD-uppsats Serietitel och serienummer

Title of series, numberingISSN

Övrig rapport____

URL för elektronisk versionhttp://www.ep.liu.se/exjobb/isy/2002/3239/

TitelTitle

Admission Control and Downlink Scheduling for Advanced Antennas in WCDMA

Författare Author

Jonas Brorsson

SammanfattningAbstractTransmissions to a mobile can be limited to the direction where the mobile is located usingAdvanced Antennas. Beside other advantages, this allows for efficient radio resourcemanagement algorithms. One of them is the admission control, which determines whether a usershould be allowed to set up a call or data connection. If the locations of the mobiles areconsidered in this decision, only mobiles in overloaded areas have to be blocked. Anotheralgorithm, which can be improved, is the scheduling. This is the process of determining theamount of data to transmit to each user, and the order in which to transmit the data. Bytransmitting to mobiles at different locations simultaneously the capacity of the system willincrease. The aim of this thesis has been to evaluate how much capacity and delays could beimproved if the locations of the mobiles were considered in the admission control and scheduling.Simulations show that in a scenario where the mobiles are uniformly distributed the capacity willincrease by at least 10%, and that delay improvements of up to 45% can be achieved. The capacityincrease and delay improvements are due to efficiency improvements in both admission controland scheduling. Simulations where the users are concentrated to hotspots point out thatparameters have to be carefully chosen. If the parameters are not carefully chosen, consideringlocation information may in some cases hamper the performance rather than improving it.

NyckelordKeywordAdmission Control, Scheduling, Advanced Antennas, WCDMA

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AbstractTransmissions to a mobile can be limited to the direction where themobile is located using Advanced Antennas. Beside other advantages, thisallows for efficient radio resource management algorithms. One of them isthe admission control, which determines whether a user should be allowedto set up a call or data connection. If the locations of the mobiles areconsidered in this decision, only mobiles in overloaded areas have to beblocked. Another algorithm, which can be improved, is the scheduling.This is the process of determining the amount of data to transmit to eachuser, and the order in which to transmit the data. By transmitting tomobiles at different locations simultaneously the capacity of the systemwill increase.The aim of this thesis has been to evaluate how much capacity and delayscould be improved if the locations of the mobiles were considered in theadmission control and scheduling. Simulations show that in a scenariowhere the mobiles are uniformly distributed the capacity will increase byat least 10%, and that delay improvements of up to 45% can be achieved.The capacity increase and delay improvements are due to efficiencyimprovements in both admission control and scheduling.Simulations where the users are concentrated to hotspots point out thatparameters have to be carefully chosen. If the parameters are not carefullychosen, considering location information may in some cases hamper theperformance rather than improving it.

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Table of Contents

1 INTRODUCTION ......................................................................... 1

1.1 BACKGROUND .............................................................................. 11.2 PROBLEM STATEMENT .................................................................. 11.3 SCOPE .......................................................................................... 11.4 ASSUMPTIONS............................................................................... 21.5 METHOD....................................................................................... 21.6 PREVIOUS WORK .......................................................................... 21.7 ORGANIZATION OF THE REPORT..................................................... 3

2 WCDMA ........................................................................................ 4

2.1 BACKGROUND .............................................................................. 42.2 SERVICES PROVIDED ..................................................................... 42.3 SYSTEM OVERVIEW ...................................................................... 42.4 RADIO INTERFACE ........................................................................ 52.5 ADMISSION CONTROL ................................................................... 62.6 CONGESTION CONTROL................................................................. 72.7 SCHEDULING ................................................................................ 72.8 POWER CONTROL.......................................................................... 7

3 MODELS ....................................................................................... 9

3.1 SYSTEM MODEL............................................................................ 93.2 TRAFFIC MODEL........................................................................... 93.3 MOBILITY MODEL ........................................................................ 93.4 CHANNEL MODEL....................................................................... 10

4 RADIO RESOURCE MANAGEMENT ALGORITHMS ......... 11

4.1 LOAD MEASURES........................................................................ 114.2 ADMISSION CONTROL ................................................................. 114.3 SCHEDULING .............................................................................. 13

5 SIMULATIONS........................................................................... 14

5.1 SIMULATION ENVIRONMENT ....................................................... 145.2 SIMULATION SETUP .................................................................... 145.3 MAXIMUM TOTAL BIT RATE ....................................................... 145.4 THROUGHPUT ............................................................................. 175.5 DELAY ....................................................................................... 195.6 THROUGHPUT DISTRIBUTION AMONG SERVICES .......................... 225.7 HOTSPOT USER DISTRIBUTION .................................................... 23

5.7.1 Throughput ........................................................................ 245.7.2 Delay ................................................................................. 25

6 CONCLUSIONS.......................................................................... 26

6.1 SUMMARY .................................................................................. 26

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6.2 FURTHER STUDIES ...................................................................... 266.2.1 Taking Spreading Codes into Account................................ 266.2.2 The Choice of Maximum Total Bit Rate.............................. 266.2.3 Impact of System Delays and Measurement Errors............. 266.2.4 Scheduling Taking Pathgain into Account .......................... 276.2.5 Scheduling Taking Adjacent Beams into Account ............... 276.2.6 Interference Aware Beam Selection.................................... 27

REFERENCES.................................................................................... 28

APPENDIX A: ABBREVIATIONS .................................................. 30

APPENDIX B: SIMULATION PARAMETERS ............................. 31

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1 Introduction

1.1 BackgroundAn inherent characteristic of Code Division Multiple Access (CDMA)systems is that the capacity is mainly limited by the interference differenttransmissions present to each other. In order to decrease the interference,the use of Advanced Antennas (AA) in the base stations has beenproposed. The idea common to most AA approaches is to use antennas,which can limit the radio transmissions to the direction where the mobileis located. By doing this, a transmission to a mobile will cause lessinterference to other mobiles.AA also allows for more efficient radio resource management algorithms.One of them is the admission control, which determines whether a usershould be allowed to set up a call or data connection. If the locations ofthe mobiles are considered in this decision, only mobiles in overloadedareas have to be blocked. Another algorithm, which can be improved, isthe scheduling. This is the process of determining the amount of data totransmit to each user, and the order in which to transmit them. Bytransmitting to mobiles at different locations simultaneously the capacityof the system will increase.

1.2 Problem StatementIn Wideband CDMA (WCDMA) the admission control and schedulingare not performed in the base station but in the Radio Network Controller(RNC), which is a network node typically not co-located with the antennaand the base station. When using AA, the position (or at least the directionas seen from the base station) of the mobile within the cell is estimated.As pointed out in previous section, this information could potentiallyincrease the efficiency of the scheduling and admission control if it wereavailable in the RNC. This is not the case in the present standard.In order to make this information available in the RNC the currentstandard has to be changed. Furthermore, the signaling on the interfacebetween the base station and the RNC would increase. The aim of thisstudy is therefore to evaluate how much would be gained if thisinformation were available to the scheduling and admission control. Thegain has to be substantial in order to make it worth the effort of changingthe standard.

1.3 ScopeThis study focuses on a concept where an antenna array is used to form anumber of beams pointing in equally spaced directions. The concept isreferred to as fixed beams, and is the simplest and thus most likelyconcept to be deployed initially. Figure 1.1 shows the antenna patterns forconventional antennas and for a system using fixed beams. The

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conventional antennas use one lobe to cover each cell, while in this studyeach cell is divided into four slices, each covered by one lobe.

Figure 1.1 Antenna pattern for conventional sector antenna and for fourfixed beams.

In the uplink, i.e. transmissions from mobiles to base stations, all beamsare used to receive the signal, while in the downlink only the beamcovering the area where the mobile is located is used. This results in lessdownlink interference for mobiles in other parts of the cell.This study focuses on the downlink, since this is expected to be thelimiting link. The reason for this is that most data applications mainlydownload data to the mobiles, which will lead to a strongly asymmetrictraffic. It is also more realistic to introduce this kind of scheduling in thedownlink, since it does not require a lot of signaling to the mobiles.

1.4 AssumptionsIt is assumed that the locations of the mobiles are correctly estimated, i.e.the best beam is chosen. It is further assumed that there are no delayswithin the system, i.e. the location of the mobiles can be transferred to theRNC instantaneously.

1.5 MethodSystem level simulations are used to obtain the results. A scenario wherethe users are uniformly spread and a scenario where the users areconcentrated to hotspots are simulated.Two concepts are compared in terms of throughput, delays and error rates.Mean values as well as the distribution among users are considered.

1.6 Previous WorkThere have been some previous studies on capacity in WCDMA systemsusing Advanced Antennas. In [2] the capacity of systems using four fixed

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beam antennas was compared to the capacity of systems usingconventional antennas. A capacity comparison between various advancedantenna concepts was presented in [3]. However, neither of these studieshas taken the possibility to use the locations of the mobiles for admissioncontrol and scheduling purposes into account. In fact, they have not usedadmission control and scheduling at all.[4] and [5] have both focused on how much capacity and delays can beimproved if the location of the mobiles are considered in the scheduling.However, the framework was WLAN so these results cannot be directlyapplied to WCDMA systems due to the different media access and trafficsituation. [11] compares some scheduling strategies for packet radiosystems. Results for a GPRS system are presentedIn [6] the performance of various admission control strategies andscheduling algorithms were compared. The context was a WCDMAsystem but advanced antennas were not considered. A call admissioncontrol algorithm based on estimated signal-to-interference-plus-noiseratio was proposed in [10]. The problem how to handle packet data wasnot adressed.

1.7 Organization of the reportThe rest of this report is organized as follows:

Chapter 2 gives an overview of WCDMA for readers not already familiarwith the standard.

Chapter 3 describes the models used in the simulations. Models for radiochannels as well as the system and the users are presented.

Chapter 4 describes the radio resource management algorithms developedfor and used in this study

Chapter 5 presents the simulations and the obtained results. The resultsare commented as they are presented.

Chapter 6 contains a summary of the obtained results including drawnconclusions. It also contains a number of ideas for future studies.

Throughout the text, references are made. The reference list is located atthe end of the report, before the Appendices.

In order to make this report shorter and faster to read, numerousabbreviations are used. They are explained when they first appear, and arealso assembled in Appendix A.

Finally, the most important parameters used in the simulations aretabulated in Appendix B.

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2 WCDMAThis chapter gives a system overview for readers not familiar withWCDMA. The focus is on topics relevant for the understanding of thisreport. A more thorough description of WCDMA can be found in [1] and[9]. These are the references, which have been used when writing thischapter.

2.1 BackgroundWCDMA (Wideband Code Division Multiple Access) is the agreed uponstandard for the third-generation mobile communications systems inEurope and Asia. It is standardized by the 3rd Generation PartnershipProject (3GPP), which is a joint project of standardization bodies inEurope, Asia and USA as well as manufacturers, operators and otherinterest groups.Third generation systems, such as WCDMA, are designed for multimediacommunication and are characterized by high bit rates and flexibleassignment of resources. This will allow for numerous new applicationssuch as video telephony and WWW browsing to co-exist with classicalapplications such as phone calls.

2.2 Services providedWCDMA offers circuit switched as well as packet switched connections.It also supports variable bit rates and a number of Quality-of-Service(QoS) classes. To utilize the spectrum as efficiently as possible, users areassigned bearer characteristics appropriate for the application. Thesecharacteristics can include throughput, delay and error rate.

2.3 System OverviewIn cellular communications systems the area to be covered is divided intocells, each served by one base station. A mobile located in a cellcommunicates with the base station serving that specific cell. InWCDMA, each base station can serve several cells, see figure 2.1.

Figure 2.1 An idealized segmentation of an area into cells. Each basestation serves three cells.

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Base stations and their cells are in turn groped into larger domains, eachcontrolled by a Radio Network Controller (RNC) as depicted in figure 2.2.

RNC1

BS1 BS2 BS3

RNC2

BS4 BS5 BS6

Figure 2.2 Several RNCs, each serving a number of basestations, can coexist.

The task of the base station is to forward data from the RNC to themobiles (downlink) and from the mobiles to the RNC (uplink) over therradio interface. The RNC is responsible for the radio resource control inits domain. This includes admission control, congestion control andscheduling. These three mechanisms are described later in this chapter.

2.4 Radio InterfaceBefore the data are modulated and transmitted over the radio interface,they are spread as illustrated in figure 2.3.

Figure 2.3 Spreading and de-spreading in WCDMA.

As a result of the increased amount of bits, more bandwidth is needed totransmit the data. However, by spreading the data with orthogonal codes,several channels can be transmitted over the same spectrum. Orthogonalcodes means that when de-spreading a signal using the correct code thesignal is restored, while when using an orthogonal code the signal isfiltered out totally. Of course, due to distortions and other non-ideal

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conditions, the signals will not be completely orthogonal at the receiver.The signals will consequently present some interference to each other,which will add to the background noise.There are of course a limited number of orthogonal codes. Non-orthogonalcodes must thus be used, but usually not within the same cell. However,the capacity increase obtained when using AA can require that non-orthogonal codes be used.Figure 2.4 shows that even though a non-orthogonal signal is not filteredout totally, it is suppressed by the correlation receiver.

Figure 2.4 De-spreading using a correlation receiver. The desired signalis restored, while other signals are suppressed.

Spreading the signal over a wide frequency band has a number ofadvantages. One is that the signal is less sensitive to bad transmissionconditions in narrow frequency bands. Another is that the use of thespectrum is more flexible since codes of different lengths can be used fordifferent bit rates.

2.5 Admission ControlEach phone call or data transmission increases the interference in the radiointerface, and interference causes transmitted data blocks to beerroneously received. Admission control is used to prevent the BlockError Rate (BLER) from exceeding an unacceptable level.The admission control determines whether a user should be allowed to setup a call or data connection. Before admitting a user into the system it isimportant to make sure that this will not lead to that already admittedusers cannot be provided an acceptable quality of service. This task ismuch more delicate than in speech only systems. For example, to decidewhether a phone call can be admitted or not the amount of best effort data,

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which can be rescheduled to give room for the call, has to be estimated. Itis also possible to give different users different priorities. A best effortdata user can be dropped to give room for a phone call.

2.6 Congestion ControlEven though admission control is used, the system can still becomeoverloaded. The task of the congestion control is to quickly stabilize thesystem at such occasions. There are several ways of doing this. The firstaction is to reschedule data, which can be transmitted later. Next step canbe to hand over users to other frequency bands, cells or systems. As a lastway out, it is possible to drop calls.

2.7 SchedulingScheduling is the process of determining the amount of data to transmit toor from each user, and the order in which to transmit them. Data aredivided into blocks, which are transmitted in an order determined by thescheduling algorithm. In WCDMA, the highest scheduling time resolutionis one 10 ms frame. This means that the smallest block size is the amountof data, which can be transmitted within one frame. Some services uselarger blocks.A lot of factors have to be considered in the scheduling. Real time (RT)services such as speech and streaming require low delays, and have to beprioritized before non-real time (NRT) services such as WWW data.Furthermore, measures such as throughput and delay have to beoptimized.

2.8 Power ControlOne of the strengths of WCDMA is the efficient power control, whichensures that an appropriate power level is used for the communicationbetween the base station and each mobile. This is important since a toohigh power level would present too much interference to other mobiles,while a too low power level compared to the interference would result inhigh error rates for the specific mobile.The power control has two main mechanisms. The inner power loopincreases or decreases the power setting every slot, i.e. 15 times per frame,to keep the Signal to Interference Ratio (SIR) close to a target value. Theouter power loop makes adjustments to the SIR target based on error rates.Pathgain is defined as received power divided by transmitted power and isa function of a lot of factors, which can vary rapidly. Due to aphenomenon called fading, small movements of the mobile can causepathgain variations of several orders of magnitude in a fraction of asecond. To compensate for this the power control has to be very fast.Since every frame is 10 ms, and the power setting is updated 15 times perframe, the inner loop works at 1500 Hz. This is fast enough to follow mostvariations in the pathgain.

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There is one additional constraint on the power control. Due to hardwarelimitations there is a maximum transmit power, which in this study is20W per beam. Transmitting more than this is however rarely needed.

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3 ModelsHere the models used in the simulations are described. First the system isdescribed. The following two sections specify how the users are simulatedand the last section is an explanation of the channel model used tosimulate the radio environment.

3.1 System ModelA homogenous hexagon cell pattern with base stations positioned as wasdepicted in figure 2.1 is assumed. Each of the seven base stations servethree cells, which gives a total of 21 cells. The base stations are equippedwith antennas using four fixed beams to cover each cell.

3.2 Traffic ModelThe mix of users trying to set up calls is according to table 3.1. This is thesame mix as was used in [1], [2]. However, since RT services have higherpriority in the admission control in this study, this is not necessarily theactual mix of users in the system. In this study, speech and streaming areconsidered RT services while WWW is considered an NRT service. Thisis also indicated in table 3.1.

Speech 60% RTStreaming 20% RTWWW 20% NRT

Table 3.1 User mix and classification.

A 12.2 kbps speech model based on measurements in GSM (GlobalSystem for Mobile communications) systems is used. Streaming is simplysimulated using a continuous 64 kbps data stream. Finally, the WWWmodel is based on modem-pool measurements, where the values arescaled to simulate users with a 384 kbps channel. For a more detaileddescription of the WWW model the reader is referred to [8].In WCDMA it is for some services possible for users to share channels. Inthis study however, all users are assigned their own (dedicated) channel.

3.3 Mobility ModelUsers are generated with initial positions spread over the area. Two casesare simulated. In the first the users are uniformly spread, while in thesecond they are concentrated to a number of hotspots.From their initial position, users move with low speed and accelerationcorresponding to pedestrian behavior. Due to the low average speed (~ 0.8m/s) and the short simulations (2 s), the results of the study do not reflecteffects of users moving between beams or cells.

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3.4 Channel ModelAs was pointed out in section 2.8, pathgain variations of several orders ofmagnitude can exist. Most of these variations are compensated for by thepower control. This will instead cause varying interference to othermobiles. It is thus important to have a realistic model of the radioenvironment.To simulate this the simulator uses the COST259 channel model, whichwas specifically developed for wideband systems such as WCDMA. Aswas mentioned in previous section the users in these simulations moveslowly, and the fading will thus also be slow. To save simulation time thepathgain is therefore constant during the simulations.COST259 is directional which means that the pathgain is dependent onthe angle from the mobile to the base station. This is important to giverealistic simulations when using AA. It does furthermore take line of sightinto account. This means that radio waves propagating directly to thereceiver are considered as well as reflected waves.Important for the propagation is also the terrain and surrounding objectssuch as buildings and vehicles. For the simulations in this study, themodel is parameterized to simulate a typical urban environment.More information on the model can be found on the COST259 web site[7].

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4 Radio Resource Management AlgorithmsIn this chapter the admission control and scheduling algorithms developedfor and used in the simulations are described. These are the two mostimportant radio resource management algorithms for this study. The aimof the study is to compare the case where the position of the mobile withinthe cell is known to the case where it is not. This is simply done by in thefirst case performing admission control and scheduling on beam level andin the second, where it is not known in which beam the user is located, oncell level.The descriptions of the algorithms are preceded by a general discussion onload measures.

4.1 Load MeasuresAs was explained in chapter 2, transmitting too much data simultaneouslycauses a too high interference level. Scheduling is used to guarantee anacceptable interference level in a cell when there is more data in thebuffers than can be transmitted simultaneously. This is done byscheduling some of the transmissions later.Since the interference is highly dependent on the transmitted power, thiswould be a good measure to use when determining the amount of data,which can be transmitted simultaneously. However, the power needed tocommunicate with each user varies rapidly, and it is thus difficult to keepthe RNC updated. Because of this it is hard to make decisions about theamount of data, which can be transmitted simultaneously, based on powerlevels.For this reason, the measure used in this study is simply bit rate.Interference is assumed to increase with the total number of bitstransmitted per frame in a cell or beam. To prevent the interference frombecoming too high, a maximum total bit rate per beam or cell is used. Thesum of the bit rates used for transmissions to users in a beam or cell mustbe less than or equal to this rate.

4.2 Admission ControlAttempts to set up calls or data connections are queued and handled every10 ms. The admission control algorithm used in this study is performed intwo steps:

1. New RT users are admitted if it, after the admission, is possible totransmit simultaneously to all RT users at the full capacity of theirchannels without exceeding the maximum total bit rate of eachcell/beam. If all new users cannot be admitted, speech users havehigher priority than streaming users. Users within the same service areprioritized on a first-come-first-served basis. The reason why it mustbe possible to transmit to all RT users simultaneously is that theycannot tolerate delays. It is thus necessary to be able to transmit their

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data immediately, regardless if other users use the full capacities oftheir channels or not.

2. NRT users are admitted if, after the admission, delays for alreadyadmitted NRT users do not exceed a maximum tolerated delay, even ifthe new user(s) and all RT users use the full capacity of their channelsduring one frame.

The delay criterion for already admitted NRT users is

delayusersRTofcapacitieschannelratebit

averagesbufferusersnewofcapacitieschannelmax

)()(max

)()(≤

−+

∑∑∑

where

)(max ratebit is the maximum total bit rate [bits/s]. This is the maximumamount of bits which can be transmitted in a beam or cell per second, andis the load measure discussed in 4.1.

∑ )( usersRTofcapacitieschannel is the sum of the channel capacities

of all RT users [bits/s].

∑ )( averagesbuffer is the sum of the average buffer length of each NRT

user [bits]. The average is taken over the entire session of the user.

∑ )( usersnewofcapacitieschannel is the sum of the channel capacities

of the new NRT users [bits/frame]. This does not mean that new users areadmitted only if there is room for all new users. The term referes to theusers which will be admitted. If all new users cannot be admitted, usersare admitted on a first-come-first-served basis.

The formula is semi-empirical and is interpreted as described below:• The denominator is the number of bits of NRT data that can be

transmitted in a cell or beam in one second.• The numerator is the buffer length that would result if during one

frame, the buffer(s) of the new user(s) would increase by the amountof data, which can be transmitted to the new user(s) during one frame.

• The buffer length divided by the number of bits, which can betransmitted during one second, equals the time data have to wait inbuffers before they are transmitted. This should be less than themaximum tolerated delay.

The maximum tolerated delay for NRT data is 6 seconds. This value wasused in [6] as the maximum allowed delay for NRT packets. 6 secondsmight seem high, but the probability for a new user to use the full capacity

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of its channel is very small, so a higher value can be tolerated for theserare occasions since it makes it possible to admit more users.

4.3 SchedulingAs the admission control, the scheduling treats realtime and non-realtimedata separately:

1. RT data are transmitted without delay as long as the capacity of thechannel of each user is not exceeded. The admission control describedabove guarantees that this does not lead to that the maximum total bitrate is exceeded. This is of course not true if users start movingbetween beams or cells, which they do not in this study. In a morerealistic case a safety margin might be used in the admission control.Congestion control would also be necessary for cases where themargin is not enough.

2. NRT data are sent as long as the total amount of transmitted data (RTand NRT) in the beam or cell does not exceed the maximum total bitrate. The users are prioritized according to the size of their buffers.Users with short buffers have highest priority. This was in [6] foundsuperior to giving users with long buffers highest priority. The prioritylist is updated every 10 ms. Data from the buffer of the first user onthe list will be transmitted. If there is less data in the buffer than canbe transmitted during the next 10 ms, data from the buffer of thesecond user will be transmitted. And so on.

It shall be pointed out that there are other scheduling algorithms, such asfirst-come-first-served and round-robin approaches, which could havebeen used. Using these may give results differing from the ones obtainedin this study.

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5 SimulationsIn this chapter the simulations are described. First an overview of thesimulator is given and then the setup of the simulations is described. Afterthis the actual simulations are described. Sections 5.3-5.6 describe thesimulation of a case with uniform user distribution whereas section 5.7discusses conclusions drawn from simulations using a non-uniformdistribution.The maximum total bit rate is central for the algorithms used in this study.Section 5.3 thoroughly describes how it is determined. The following twosections compare the troughput and delays respectively for the per beamand per cell concepts. Finally, section 5.6 focuses on how the fraction ofNRT data is affected by the load and scheduling concept.

5.1 Simulation EnvironmentThe system simulator uses realistic radio network algorithms includingpower control, handovers, admission control and scheduling. However, nocongestion control is used.The core of the simulator is to approximate the Block Error Rate, BLER.It is done by first calculating the signal strength and the interference foreach mobile. To eliminate border effects, signals and interference crossingthe outer borders of the simulated area are wrapped around to another partof the outer border. The signal to interference ratio, SIR, is then used tointerpolate the BLER from a look-up table obtained from detailed linklevel simulations.The time resolution is one frame (10ms) with exception for the powercontrol, which is updated every slot i.e. 15 times per frame.

5.2 Simulation SetupTo obtain more accurate results, a Monte-Carlo approach is used. Forevery point in the graphs, 10 simulations are run and the arithmetic meanof the specific value is plotted.The length of each simulation is 200 frames. New users are added duringthe first 20 frames to achieve normal load in the system. This period iscalled the slow-start period. For the rest of the simulation the call arrival isPoisson distributed with inter-arrival times according to the traffic models.However, due to the short simulation time, only a few users will attemptto set up new calls during the remaining time of the simulation.

5.3 Maximum Total Bit RateAs described in previous chapter, the maximum total bit rate is central forthe radio resource algorithms used in this study. The maximum total bitrate is a function of various factors such as radio environment, user mix,number of users and desired quality of service. It is not the aim of thisstudy to find the exact relation to these parameters, but a value is stillneeded for the simulations. For this reason, the maximum value given the

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radio environment, traffic mix, number of users and QoS constraints usedin this study is determined through simulations.The QoS is in this study measured in terms of BLER. The constraints arethat 95 percent of the users must have a mean BLER, which does notexceed an unacceptable level. The acceptable levels are tabulated in table5.1. These values were also used in [1] and [2].

Service Accepted BLERSpeech 2%

Streaming 15%WWW 20%

Table 5.1 Accepted BLER for each user group.

To determine the maximum total bit rate, for which the QoS constraintsare fulfilled, the mean BLER for users at the 95th percentile was plottedversus maximum total bit rate. This was done for each service andscheduling/admission case as well as for a number of load cases. Thechoice of load cases will become apparent when looking at figure 5.4.An example plot is given in figure 5.1, which shows the speech users for anumber of load cases. The scheduling and admission control are in thiscase performed per beam. It can be seen how the power control managesto keep the BLER at the target up to a point where it is no longer possible.At this point the interference is so high that the signal power has to beincreased to reach the SIR target, which will in turn result in even higherinterference. This phenomenon is called party-effect.

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Figure 5.1 BLER (at the 95th percentile) versus maximum total bit rateper beam for speech users. Scheduling per beam, uniform user

distribution.

As was tabulated in table 5.1, the maximum acceptable BLER for speechis 2%. This limit is marked with a horizontal line in figure 5.1. Themaximum total bit rate for which each curve crosses this line is themaximum total bit rate used in this study. Note that for low loads thecurve does not cross the line, and a maximum total bit rate cannot bedetermined using this method.A summary of the maximum total bit rates obtained from BLER plots isgiven in figure 5.2.

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Figure 5.2 Maximum total bit rate versus the amount of users offered tothe system. Uniform user distribution.

Since the QoS constraints have to be fulfilled for all services, the lowestof the three curves at each point is used in the following comparisons.The curves suggest that the maximum total bit rate should be adjustedaccording to the number of users in the cell or beam. It might be hard todo this in a real case, but in order to give a fair comparison of theachievable performance of the two cases this is done in the simulations.The rate is not adjusted for each cell/beam individually but since thedistribution of the users is uniform the effect of this will be negligble.

5.4 ThroughputThe total throughput per cell was plotted versus maximum total bit rate fora number of load cases and for each scheduling/admission case. As anexample, the curves for the per beam case are plotted in figure 5.3.

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Figure 5.3 Throughput versus maximum total bit rate per beam.Scheduling per beam, uniform user distribution.

The figure shows that the throughput increases when the maximum totalbit rate is increased. The rate should thus be chosen as high as the BLERconstraints allow. Using the curves in figure 5.2 the maximal achievablethroughput, given the QoS constraints, for each load case was read fromthe throughput curves and plotted in figure 5.4.

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Figure 5.4 Obtainable throughput per cell given the BLERconstraints.Uniform user distribution.

The shape of the curve is intuitive. Throughput is approximatelyproportional to the offered traffic for low loads. When the capacity of thesystem is reached, the throughput stops increasing. Two things can benoticed. First, the throughput at low loads is almost identical for the twocases. Since the probability of congestion is low here, this is notsurprising. The second thing to notice is that the capacity limit is at least10% higher when the scheduling is performed per beam. This capacityincrease is both due to the scheduling and the admission control.

5.5 DelayFor short transmissions such as requests and acknowledgements, waitingtimes represent a major part of the transmission time. It is thus importantto keep delays as short as possible.For the delay comparison, mean values for the average user as well as forusers at the 95th percentile were plotted versus maximum total bit rate. Asan example, the curves for the per beam case are plotted in figure 5.5. Thecurves are based on delays for transmitted blocks. If a block at the end ofthe simulation is still waiting to be transmitted, it will not be visible in thestatistics.

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Figure 5.5 Delay versus maximum total bit rate for various amounts ofoffered traffic. Scheduling per beam, uniform user distribution.

The figure shows how the maximum total bit rate affects the delays.Higher rate means that the time needed to transmit the data in the buffersis decreased. Like in previous section, the maximum total bit rate shouldbe as high as the BLER constraints allow.Using the maximum total bit rates of figure 5.2 the best achievable delayswere read from the curves. The result is plotted in figure 5.6 and 5.7.

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Figure 5.6 Obtainable mean delay for the average user given the BLERconstraints. Uniform user distribution.

Figure 5.6 depicts the mean delay for the average user. For low loadswhere the throughput is approximately equal for the two cases, the delaysare lower when the scheduling is performed per beam. The reason that thisis not true for high loads is that a higher throughput is achieved when thescheduling is performed on beam level. Delays will of course increasewhen the amount of data is increased. In the region where the curves arecomparable, i.e. for low loads, the delays are decreased by 35-45%.In figure 5.7 the mean delays for users at the 95th percentile are plotted.

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Figure 5.7 Obtainable mean delay for users at the 95th percentile giventhe BLER constraints.

The plot shows that the improvement for worst-end users is even betterthan for the average at high loads. Delays are even improved for highloads where the throughput is increased. For low loads the delay isdecreased by 35-45%.

5.6 Throughput Distribution Among ServicesIn Figure 5.8 the fraction of the total amount of transmitted data, whichconsists of NRT data, is plotted versus offered traffic.

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Figure 5.8 Fraction of NRT data versus offered traffic.

The first thing to notice is that the fraction decreases when the loadincreases. The reason for this is that RT data have higher priority. Whenthe amount of RT data increases there is less room for NRT data. Anotherthing to notice is that the fraction NRT data is up to 20% higher when thescheduling is performed per beam. This indicates that the utilization of theresources not used by RT users is more efficient when the scheduling isperformed per beam.

5.7 Hotspot User DistributionAs a comparison to the results obtained for a uniform user distribution inprevious sections, a hotspot scenario was also evaluated. The samesimulations were run, but the users were concentrated to a number ofequally spaced hotspots located as depicted in figure 5.9. An extreme casewas chosen rather than a realistic so that any differences in the resultsshould be clearly visible.

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Figure 5.9 Users are concentrated to hotspots.

Throughput and delays were determined the same way as for the uniformdistribution.

5.7.1 ThroughputThe total throughput obtainable in a cell, given the BLER constraints, isplotted in figure 5.10.

Figure 5.10 Obtainable throughput per cell given the BLER constraints.

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As expected, the throughput is lower than for the uniform distribution.More interesting though, is that the throughput seems to be lower whenthe scheduling and admission control are performed per beam. The reasonfor this was found to be the choice of maximum total bit rate.When looking at figure 5.9 it can be concluded that there is approximatelyone hotspot per cell, but that the variation among beams is larger. Somebeams contain an entire hotspot, some one half hotspot and others almostno users at all. Because of this it is not optimal to use the same maximumtotal bit rate for all beams, whereas for the per cell case almost all cellshave the same conditions and a common maximum total bit rate based onBLER is close to optimal.The per cell approach seems to collapse for high loads. This might be aresult of that the per cell algorithm transmits more than it should in thehotspots since it on average is possible to transmit more in the cell. Themaximum total bit rate must consequently be lowered, which decreasesthe throughput.

5.7.2 DelayThe delay curves presented in figure 5.11 show that the delays are higherfor the per beam approach. This is a result of that the maximum total bitrate is lower than necessary for most beams, which was discussed inprevious section.

Figure 5.11 Obtainable mean delay given the BLER constraints.

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6 ConclusionsIn this chapter the results are summarized and evaluated. A number ofideas for further studies are also presented.

6.1 SummaryThe aim of this thesis has been to evaluate how much capacity and delayscould be improved if information about the location of each user weretransferred to the RNC and used in the radio resource managementalgorithms. Simulations show that in a scenario where the mobiles areuniformly distributed the capacity can increase by at least 10%, and thatdelay improvements of up to 45% can be achieved. The capacity increaseand delay improvements are due to efficiency improvements in bothadmission control and scheduling.Simulations where the users are concentrated to hotspots point out that themaximum amount of data, which is transmitted simultaneously in a beam,has to be carefully chosen in order to achieve good system performance.When the users are non-uniformly distributed it might be necessary to usedifferent amounts for different beams or cells. The choice of maximumtotal bit rate is harder when admission control and scheduling areperformed per beam since the variations among beams in general arelarger than among cells. If the maximum total bit rate is not carefullychosen, the per beam approach may hamper the performance rather thanimproving it.

6.2 Further StudiesHere a number of ideas which came up during this study and which can beinteresting to study further are described.

6.2.1 Taking Spreading Codes into AccountIn this study it has been assumed that there are always enough spreadingcodes available. Taking into account that the amount of codes is limitedmight affect the results.

6.2.2 The Choice of Maximum Total Bit RateAs discussed in section 5.7, the maximum total bit rate has to be carefullychosen in order to achieve good system performance. When the users arenon-uniformly distributed if might be necessary to use different rates fordifferent beams. Exactly how to chose the maximum total bit rate and theobtainable performance gain are topics where further study is needed.

6.2.3 Impact of System Delays and Measurement ErrorsThe impact of measurement errors and system delays has been neglectedin this study. This is clearly a topic for further study.

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6.2.4 Scheduling Taking Pathgain into AccountThe aim of this study is to compare the capacity gain, which can beachieved if the locations of the mobiles within the cell can be used in thescheduling and admission control. Next step could be to investigate whatcan be achieved if the pathgain to each user can be used as well. Mobileswith low pathgain require more power, so transmitting to them will resultin more interference than transmitting to mobiles with high pathgain.Transmissions to single mobiles should thus be scheduled when thepathgain is good. The throughput can also be increased if users withconstant bad pathgain are assigned less resource or are neglected totally.This does of course pose some policy problems.

6.2.5 Scheduling Taking Adjacent Beams into AccountThe maximal amount of data, which is transmitted simultaneously, ismainly determined by the interference signals sent to different userspresent to each other. To decrease the downlink interference the conceptusing fixed beams was introduced. Since each beam is narrower,transmitting to one mobile will present interference to a smaller number ofusers, mostly to users in the same and adjacent beams. Schedulingtransmissions to frames when the adjacent beams do not transmit at theirmaximum rate can decrease the interference even further.

6.2.6 Interference Aware Beam SelectionThe obvious beam selection criterion is to use the beam with bestpathgain. However, what really determines the quality of a link is the SIR.By trading high pathgain for low interference, the throughput in the cellcan increase.Consider an example with two users. One of them is in the middle of abeam, and the other is on the border between this beam and an adjacentbeam. For the second user, the gain is the same, regardless of which beamhe uses. The interference from the first user does not depend on the beamchoice, so the SIR will be the same no matter which beam he is assignedto. The first user however, will experience less interference if they are notin the same beam. In this case a capacity gain can obviously be obtainedby an interference aware beam selection.The most straightforward way to implement this is to move the beamselection to the RNC. This means that pathgain for all users in all beamshave to be transferred to the RNC, and that information about which beamto use has to be transferred back to the base station.

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References

[1] Harri Holma, Antti Toskala, “WCDMA FOR UMTS, Radio AccessFor Third Generation Mobile Communications”, John Wiley &Sons, 2000

[2] József Barta, Mårten Ericson, Bo Göransson, Bo Hagerman, AfifOsseiran, “Capacity Study for Fixed Multi Beam Antenna Systemsin a Mixed Service WCDMA System”, Proceedings InternationalSymposium on Personal, Indoor and Mobile RadioCommunications (PIMRC 2001), San Diego, USA, Oct 2001.

[3] József Barta, Mårten Ericson, Bo Göransson, Bo Hagerman, AfifOsseiran, “Downlink Capacity Comparison between DifferentSmart Antenna Concepts in a Mixed Service WCDMA System”,Proceedings IEEE Vehicular Technology Conference (VTC 2001fall), Atlantic City, USA, October 2001

[4] Hujun Yin, Hui Liu, “Dynamic Scheduling in Antenna ArrayPacket Radio”, Proceedings IEEE Signals, Systems andComputers Conference, Pacific Grove, USA, October 1999

[5] Ulrich Vornefeld, “Packet Scheduling in SDMA Based WirelessNetworks”, Proceedings IEEE Vehicular Technology Conference(VTC 2000 fall), Boston, USA, September 2000

[6] Muhammad Kazmi, Philippe Godlewski, “Admission ControlStrategy and Scheduling Algorithms for Downlink PacketTransmission in WCDMA”, Proceedings IEEE VehicularTechnology Conference (VTC 2000 fall), Boston, USA,September 2000

[7] The COST 259 Web site, http://www.lx.it.pt/cost259/

[8] Attila Vidács, József Bartha, Zsolt Kenesi, Tamás Éltetö,“Measurement-Based WWW User Traffic Model for Radio AccessNetworks”, International Workshop on Mobile MultimediaCommunications (MoMuC), Tokyo, Japan, October 2000

[9] Erik Dahlman, Per Beming, Jens Knutsson, Fredrik Ovesjö,Magnus Persson, Christiaan Roobol, “WCDMA—The RadioInterface for Future Mobile Multimedia Communications”, IEEETransactions on Vehicular Technology, vol 47, no. 4, November1998

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[10] Yoshitaka Hara. “Call Admission Control Algorithm for CDMASystems with Adaptive Antennas”, Proceedings IEEE VehicularTechnology Conference (VTC 2000 fall), Boston, USA,September 2000

[11] Christer Johansson, Lisa de Verdier, Farooq Khan, “Performanceof Different Scheduling Strategies in a Packet Radio System”,Proceedings IEEE Conference on Universal PersonalCommunications, October 1998

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Appendix A: Abbreviations

3GPP 3rd Generation Partnership ProjectAA Advanced Antenna, Adaptive AntennaBLER BLock Error RateCDMA Code Division Multiple AccessDL DownlinkGPRS General Packet Radio ServiceGSM Global System for Mobile communicationsNRT Non Real-timeQoS Quality of ServiceRNC Radio Network ControllerRT Real-timeSIR Signal to Interference RatioUL UplinkWCDMA Wideband Code Division Multiple AccessWLAN Wireless Local Area NetworkWWW World Wide Web

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Appendix B: Simulation Parameters

Parameter ValueNumber of Cells 21Cell Radius 1000 mBeams per Cell 4

Maximum Tolerated Delay 6 s

User Mix (Speech/Streaming/WWW) 60/20/20 %Maximum Bit Rate, Speech 12.2 kbpsMaximum Bit Rate, Streaming 64 kbpsMaximum Bit Rate, WWW 384 kbps

Simulation Length 200 frames (2 s)Slow-start Period 20 frames (0.2 s)Number of Simulations Per Point 10

Time Resolution (Except Power Control) 10 msPower Control Frequency 1500 Hz

Maximum Transmit Power per Beam 20 W

Table A.1 Simulation Parameters