Radio network planning and resource optimization : mathematical models and algorithms for UMTS, WLANs, and ad hoc networks

249 Pages·2008·4.85 MB·English

by  Iana Siomina.

Link¨opingStudiesinScienceandTechnology
DissertationsNo.1116
Radio Network Planning and
Resource Optimization:
Mathematical Models and Algorithms for
UMTS, WLANs, and Ad Hoc Networks
Iana Siomina
DepartmentofScienceandTechnology
Linko¨pingUniversity,SE-60174Norrko¨ping,Sweden
Norrko¨ping2007
Link¨opingStudiesinScienceandTechnology,DissertationsNo.1116
Radio Network Planning and Resource Optimization:
MathematicalModelsandAlgorithmsforUMTS,WLANs,andAdHocNetworks
IanaSiomina
ImageonfrontcoverwasdesignedbyIanaSiomina.
ISBN978-91-85831-44-9
ISSN0345-7524
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-9158
Copyright(cid:2)c2007,IanaSiomina,unlessotherwisenoted
PrintedbyLiU-Tryck,Linko¨ping,Sweden,2007
i
Abstract
Thetremendouspopularityofwirelesstechnologiesduringthelastdecadehascreatedacon-
siderable expansion of wireless networks both in size and use. This fact, together with a
great variety of mobile devices and numerous different services that are becoming increas-
ingly resource-demanding, have attracted the attention of many researchers into the area of
radio resource planning and optimization. Due to network complexity, these tasks require
intelligent,automatedapproachesthatareabletodealwithmanyfactorsinordertoenable
designofhighcapacitynetworkswithahighservicequalityatthelowestpossiblecost. This
isaperfectapplicationofoptimizationtheory.
Inthisthesis,mathematicaloptimizationisconsideredasthemainapproachtodesigning
and improving the performance of wireless networks such as Universal Mobile Telecommu-
nications System (UMTS), Wireless Local Area Networks (WLANs) and ad hoc networks.
Due to different underlying access technologies, the optimization goals, design parameters
andsystemlimitationsvarybynetworktype. Therefore,thegoalsofthepresentedworkare
to identify a relevant optimization problem for each type of network, to model the problem
and to apply the optimization approach in order to facilitate wireless network planning and
improveradioresourceutilization.
The optimization problems addressed in this thesis, in the context of UMTS networks,
focusonminimizingthetotalamountofpilotpowerwhich,fromthemodelingpointofview,
is not just an amount of power consumed by a certain type of control signal, but also an
indicatoroftheinterferencelevelinthenetworkandmeansofcontrollingcellcoverage. The
presentedmodelsandalgorithmsenableflexiblecoverageplanningandoptimizationofpilot
powerandradiobasestationantennaconfigurationinlargenetworks.
For WLANs, in the first part of the study, the access point placement and the channel
assignmentproblemsareconsideredjointlytomaximizenetuserthroughputandminimizeco-
and adjacent channel interference and contention. The second part of the study addresses
the contention issue and involves, among the other decisions, optimization of access point
transmitpower.
Due to the dynamic and infrastructureless nature of ad hoc networks, static resource
planningislesssuitableforthistypeofnetwork. Twoalgorithmicframeworkswhichenable
dynamictopologycontrolforpower-efficientbroadcastinginstationaryandmobilenetworks
are presented. In both frameworks, the performance of the presented algorithms is studied
bysimulations.
Keywords: planning, optimization, wireless networks, radio resources, UMTS, WLAN, ad
hoc,pilotpower,accesspointlocation,channelassignment,powerallocation,power-efficient
broadcast.
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Popul¨arvetenskaplig
Sammanfattning
Tr˚adlo¨san¨atverkharunderdetsenaste˚artiondetblivitenormtpopula¨ra. Ikombinationmed
attdetfinnsm¨angderavmobilaenheterochresurskra¨vandetja¨nsterhardensnabbautbyg-
gnaden av nya na¨tverk medf¨ort ¨okad forskningsverksamhet inom planering och optimering
av radioresurser. Tr˚adlo¨sa n¨atverk ¨ar v¨aldigt komplexa och fo¨r att utforma dessa s˚a att de
har ho¨g kapacitet och p˚alitlighet till en l˚ag kostnad kra¨vs intelligenta tillva¨gag˚angss¨att som
tarh¨ansyntillflertaletfaktorer;dettautgo¨renperfekttilla¨mpningfo¨roptimeringsteori.
I den h¨ar avhandlingen anva¨nds huvudsakligen optimering fo¨r att designa och fo¨rba¨ttra
tr˚adlo¨san¨atverksomUniversalMobileTelecommunicationsSystem(UMTS),WirelessLocal
Area Networks (WLANs) och ad hoc-n¨atverk. Dessa nyttjar olika˚atkomsttekniker, varfo¨r
aspekter som optimeringsfokus, designparametrar och systembegr¨ansningar varierar mellan
na¨tverken. Syftet med avhandlingen a¨r att identifiera och presentera relevanta optimer-
ingsproblemfo¨rolikatr˚adlo¨san¨atverkstyper,modelleraproblemenochda¨reftertill¨ampaop-
timeringf¨orattunderla¨ttaplaneringsamteffektiviseranyttjandetavradioresurser.
Optimeringsproblemensomber¨orUMTS-n¨atverkhandlaromattminimeradeneffektsom
˚atg˚arf¨oruts¨andningavenspeciellsignalsekvenssomblandannatanva¨ndsf¨orattskattaegen-
skapernahosenkommunikationskanal. Deframtagnamodellernaochalgoritmernamo¨jliggo¨r
optimering av utsa¨nd effektniv˚a f¨or dessa signaler, flexibel planering av ta¨ckningsomr˚aden
samtregleringavbasstationersantennkonfigurationisto¨rren¨atverk.
Arbetet g¨allande WLAN handlar dels om hur man la¨mpligen placerar ut accesspunkter
varsuppgifta¨rattsammankopplana¨rliggandeenhetertillettna¨tverk. Dettainnefattara¨ven
hur dessa accesspunkter b¨or tilldelas olika kanaler i syfte att maximera datao¨verfo¨ring samt
minimeraolikast¨orningsfaktorer. Dessutompresenterasenstudiesomblandannatfokuserar
p˚aoptimeringavutsa¨ndningseffekthosutlokaliseradeaccesspunkter.
Statisk resursplanering a¨r ol¨ampligt f¨or ad hoc-n¨atverk, som karakta¨riseras av f¨ora¨nder-
lighet och avsaknad av fast infrastruktur. I avhandlingen presenteras tv˚a algoritmer f¨or
dynamisk topologikontroll som kan nyttjas fo¨r att uppn˚a energieffektiv uts¨andning i s˚ava¨l
station¨arasommobilan¨atverk. Algoritmernaa¨rutv¨arderadegenomsimuleringar.
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Acknowledgments
I wish to express my deepest and sincere gratitude to my supervisor Di Yuan, Associate
ProfessorandtheheadofMobileTelecommunicationsgroupattheDepartmentofScienceand
Technology(ITN),forhisexcellentguidancethroughoutthefouryearsIspentatLinko¨ping
University and continuously challenging me to generate new ideas. It has been a great
pleasure for me to work with such an excellent researcher and extraordinary person, from
whom I tried to learn as much as I could. I also wish to thank Professor Peter Va¨rbrand,
my supervisor and the head of our department, for offering me this PhD position and his
supportandencouragementthroughoutthesefouryears,aswellasforalwaysbeingopento
newideasandreadytohelp.
I am very grateful for the financial support I received enabling my research during the
four years provided by Center for Industrial Information Technology (CENIIT), Linko¨ping
InstituteofTechnology,underproject“OptimalDesignochEffektivePlaneringavTelekom-
munikationssystem”. I also appreciate the financial support I received during the last two
years from Swedish Research Council (Vetenskapsr˚adet) within two projects: “Mathemati-
cal Optimization in the Design of UMTS Networks” and “Energy-efficient Broadcasting in
MobileAdHocNetworks: DistributedAlgorithmsandPerformanceSimulation”.
I also wish to thank my current manager at Ericsson Research, Johan Lundsjo¨, and
the Spirit project for financially supporting my travel to two recent conferences: the 5th
IEEE Intl. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless
Networks(WiOpt2007)andthe8thIEEEIntl.SymposiumonaWorldofWireless,Mobile
andMultimediaNetworks(WoWMoM2007).
MyresearchworkonUMTSnetworksdefinitelybenefittedfromtechnicaldiscussionswith
Dr.FredrikGunnarsson and his colleagues at Ericsson Research in Linko¨ping, who are also
acknowledgedforprovidingatestdataset. Also,IamverygratefultoDr.FredrikGunnarsson,
who was the opponent at my Licentiate seminar in March 2005, for his valuable comments
andsuggestionsontheLicentiatethesis.
My special thanks go to the group of the EU project Momentum IST-2000-28088 for
making publicly available the data sets for several European cities, which definitely made
theresultsofmyworkonUMTSnetworkplanningandoptimizationmorevaluablefromthe
applicationpointofview.
I am very thankful to COST (European Cooperation in the field of Scientific and Tech-
nical Research) Action TIST 293 “Graphs and Algorithms in Communication Networks”
for a financial support of my Short-Term Scientific Mission, and the optimization group at
Zuse Institute of Berlin, in particular Dr.AndreasEisenbla¨tter and Hans-FlorianGeerdes,
for hosting the STSM which resulted in a joint paper that won the Best Paper Award in
HelsinkiattheWoWMoM2007Symposium. Also,IwishtothankHans-Florianforprovid-
inghisvisualizationsoftwareIusedforgeneratingnicefiguresinChapter7. JaouharJemai
from Braunschweig Technical University is also acknowledged for generating radio propaga-
tiondataforaWLAN.
I am grateful to Dr. Peter Brostro¨m, Dr. Sandro Bosio, and Dr. Anders Peterson for
vi
their detailed comments and practical suggestions that were very helpful in improving the
presentation quality of this thesis. I would also like to thank my colleagues at ITN for a
friendlyandinspiringatmosphereinthedepartment.
Finally,Iwouldliketoexpressmythankstomyfamilyfortheirloveandcontinuedcare,
supportandencouragement,andtomyfriendsfortheirbeliefinmeandbeingnear.
Norrk¨oping,September2007
IanaSiomina
vii
Contents
Abbreviations xv
1 Introduction 1
1.1 RadioNetworkPlanningandResourceOptimization . . . . . . . . . . . . . . 1
1.1.1 Planning,OptimizationorBoth? . . . . . . . . . . . . . . . . . . . . . 1
1.1.2 Some Classical Optimization Problems in Radio Network Design and
RecentTrends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 MathematicalProgrammingasanOptimizationTool. . . . . . . . . . . . . . 4
1.2.1 LinearProgramming . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.2.2 IntegerandMixed-IntegerProgramming . . . . . . . . . . . . . . . . . 5
1.2.3 Solution Methods and Techniques for Integer and Mixed-Integer Pro-
grams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.3 ScopeandStructureoftheThesis . . . . . . . . . . . . . . . . . . . . . . . . 13
1.3.1 ThesisOutlineandOrganization . . . . . . . . . . . . . . . . . . . . . 13
1.3.2 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.3.3 Publications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Bibliography 16
I Network Planning and Resource Optimization for UMTS 25
2 Introduction to UMTS Networks and CPICH Power Management 27
2.1 3GNetworks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.1.1 TheEvolutiontowards3G. . . . . . . . . . . . . . . . . . . . . . . . . 27
2.1.2 WidebandCodeDivisionMultipleAccess(WCDMA) . . . . . . . . . 29
2.1.3 UMTSNetworkArchitecture . . . . . . . . . . . . . . . . . . . . . . . 30
2.2 PlanningandOptimizationforUMTSNetworks . . . . . . . . . . . . . . . . 31
2.2.1 ChallengesArisinginUMTSNetworks . . . . . . . . . . . . . . . . . . 32
2.2.2 AutomatedNetworkPlanningandOptimization . . . . . . . . . . . . 33
2.2.3 RadioBaseStationConfigurationParameters . . . . . . . . . . . . . . 35
2.3 PilotPowerManagementinUMTSNetworks . . . . . . . . . . . . . . . . . . 37
2.3.1 CommonPilotChannel . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2.3.2 PilotPowerControlChallenges . . . . . . . . . . . . . . . . . . . . . . 39
2.3.3 PilotPowerAssignmentApproachesandRelatedWork . . . . . . . . 41
3 A Basic Model for CPICH Coverage Optimization 45
3.1 SystemModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.2 EnsuringSmoothHandoverbyAdjustingPowerGainParameters. . . . . . . 48
3.3 OptimizationProblem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.4 TwoAdHocSolutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.4.1 UniformPilotPower . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.4.2 Gain-basedPilotPower . . . . . . . . . . . . . . . . . . . . . . . . . . 52
viii Contents
3.5 MathematicalProgrammingFormulations . . . . . . . . . . . . . . . . . . . . 53
3.5.1 Cell-binFormulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.5.2 EnhancedFormulations . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.6 ASolutionApproachBasedonLagrangianRelaxation . . . . . . . . . . . . . 58
3.6.1 AlgorithmOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
3.6.2 LagrangianRelaxation . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.6.3 APrimalHeuristicProcedure . . . . . . . . . . . . . . . . . . . . . . . 61
3.7 ASolutionApproachBasedonColumnGeneration . . . . . . . . . . . . . . . 63
3.7.1 TheColumnGenerationMethod . . . . . . . . . . . . . . . . . . . . . 64
3.7.2 AnIterativeRoundingProcedure . . . . . . . . . . . . . . . . . . . . . 65
3.8 NumericalStudies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
3.8.1 Numerical Experiments without Ensuring Smooth Handover and Dis-
cretizingtheCPICHPowerRange . . . . . . . . . . . . . . . . . . . . 67
3.8.2 NumericalSolutionsObtainedbyDiscretizingtheCPICHPowerRange 72
3.8.3 NumericalResultsforSmoothHandover . . . . . . . . . . . . . . . . . 74
3.9 DiscussionandConclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4 Pilot Power Optimization for Partial Coverage 77
4.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
4.2 SystemModelandOptimizationProblem . . . . . . . . . . . . . . . . . . . . 77
4.3 AdHocSolutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
4.3.1 UniformPilotPower . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
4.3.2 Gain-basedPilotPower . . . . . . . . . . . . . . . . . . . . . . . . . . 79
4.4 IntegerProgrammingFormulations . . . . . . . . . . . . . . . . . . . . . . . . 79
4.4.1 AFormulationBasedonDirectAssignment . . . . . . . . . . . . . . . 80
4.4.2 AFormulationBasedonIncrementalPower . . . . . . . . . . . . . . . 80
4.5 ASolutionApproachBasedonLagrangianRelaxation . . . . . . . . . . . . . 80
4.6 NumericalResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
5 OptimizationofRadioBaseStationAntennaConfigurationandPilotPower 87
5.1 SystemModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
5.2 OptimizationProblem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
5.3 SolutionApproach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
5.3.1 GeneratingNewSolutions . . . . . . . . . . . . . . . . . . . . . . . . . 92
5.3.2 AlgorithmParameters . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
5.3.3 TheOptimizationAlgorithm . . . . . . . . . . . . . . . . . . . . . . . 94
5.4 PerformanceMetrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
5.5 NumericalExperiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
5.5.1 TestNetwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
5.5.2 OptimizationResults. . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
5.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
Bibliography 102
II Coverage Planning and Radio Resource Optimization for Wireless
LANs 107
6 Introduction to Wireless LANs 109
6.1 TechnicalBackground . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
6.2 IEEE802.11WLANArchitecture. . . . . . . . . . . . . . . . . . . . . . . . . 110
6.3 MediaAccessControlinIEEE802.11WLANs . . . . . . . . . . . . . . . . . 112