by Amin Farbod A thesis submitted in conformity with the

155 Pages·2012·0.67 MB·English

STOCHASTIC RESOURCE CONTROL IN HETEROGENEOUS WIRELESS
NETWORKS
by
Amin Farbod
A thesis submitted in conformity with the requirements
for the degree of Doctor of Philosophy
Graduate Department of Electrical and Computer Engineering
University of Toronto
Copyright ⃝c 2012 by Amin Farbod
Abstract
StochasticResourceControlinHeterogeneousWirelessNetworks
AminFarbod
DoctorofPhilosophy
GraduateDepartmentofElectricalandComputerEngineering
UniversityofToronto
2012
In the near future, demand for Heterogeneous Wireless Networking (HWN) is expected to in-
crease. HWNsareformedbyintegrationofdifferentcommunicationtechnologies,forexample
theintegrationofwirelessLANandcellularnetworks,tosupportmobileusers. QoSprovision-
inginthesenetworksisachallengingissuegiventhediversityinwirelesstechnologiesandthe
existence of mobile users with different communication requirements. In this thesis, we con-
sideroptimalresourceplanninganddynamicresourcemanagementforHWNs.
In the first part of this thesis, we examine the optimal deployment of such networks. We pro-
poseamobility-awarenetworkplanningoptimizationinwhichtheobjectiveistominimizethe
rate of upward vertical handovers while maximizing the total number of users accommodated
by the network. The optimal placement of Access Points (AP) with respect to these two ob-
jectives is formulated as an integer programming problem. Our results show that considering
the mobility pattern in the planning phase of network deployment can significantly improve
infrastructureperformance.
In the second part, we investigate optimal admission control policies employed in maintain-
ing QoS in HWNs. Here we consider two cases: integration of cellular overlay with a single
WLAN AP, and integration with a WLAN mesh network. A decision theoretic framework for
theproblemisderivedusingadynamicprogrammingformulation.
In the case of single WLAN AP and cellular overlay, we prove that for this two-tier wireless
network architecture, the optimal policy has a two-dimensional threshold structure. Further-
ii
more, this structural result is used to design two computationally efficient algorithms, Struc-
tured Value Iteration and Structured Update Value Iteration. These algorithms can be used to
determine the optimal policy in terms of thresholds. Although the first one is closer in its op-
eration to the conventional Value Iteration algorithm, the second one has a significantly lower
complexity.
In the second case where the underlay is a complex WLAN mesh network, we develop a
PartiallyObservableMarkov-ModulatedPoissonProcess(PO-MMPP)trafficmodeltocharac-
terize the overflow traffic from the underlaying mesh to the overlay. This model captures the
burstiness of the overflow traffic under the imperfect observability of the mesh network states.
Then, by modeling the overlay network as a controlled PO-MMPP/M/C/C queueing system
and obtaining structured decision theoretic results, it is shown that the optimal control policy
for this class of HWNs can be characterized as monotonic threshold curves. Moreover, these
resultsareusedtodesignacomputationallyefficientalgorithmtodeterminetheoptimalpolicy
intermsofthresholds.
Extensive numerical observations suggest that, in both cases and for all practical parameter
sets, the algorithms converge to the overall optimal policy. Additionally, numerical results
show that the proposed algorithms are efficient in terms of time-complexity and in achieving
optimalperformancebysignificantlyreducingtheprobabilityofdroppedandblockedcalls.
iii
TOMYPARENTSANDMYWIFE
iv
Acknowledgements
I would like to express my gratitude to all those who supported me while I was working on
my thesis. First and foremost, I am deeply grateful to my supervisor, Professor Ben Liang,
for his detailed and insightful comments, and for his great support throughout this work. It
was an honor to work under his supervision, and in addition to his invaluable technical help,
I benefited from the very positive atmosphere that he had established in his research group.
His broad understanding of telecommunications research, and his encouraging and personal
guidancewereinstrumentalinleadingmetocompletingthiswork.
I am also extremely grateful to the members of my supervisory committee, Professor Al-
bertoLeon-GarciaandProfessorBaochunLi,whoseconstructivecommentshelpedtoimprove
thiswork,andtoenhancethewayitwaspresented. Iamalsogratefulfortheirinvaluablefeed-
backonthedirectionofmywork.
I would like to take this opportunity to thank administrative staff and other members of
the Electrical and Computer Engineering department for their invaluable services and help
throughoutthecourseofmygraduatestudiesattheUniversityofToronto.
Completing a doctoral thesis research is an extensive undertaking requiring sacrifices and
broad support from family. It would have certainly been impossible to bring this work to
fruition without the support of my parents and my wife. My parents, Touran and Shahin,
ignited the desire to learn, and an inner and deep appreciation for science and knowledge that
shapedmylifemorethanIcanexpress,andmotivatedmetocompletethiswork. Finally,itwas
my wife, Nasrin, who stood by me with endless love and understanding while I was focused
onmyresearch.
v
Contents
1 Introduction 1
1.1 Motivations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 ThesisOutline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2 RelatedWork 7
2.1 QoSandCACinHeterogenousWirelessNetworks . . . . . . . . . . . . . . . 7
2.2 MDPOptimizationofCACforWirelessNetworks . . . . . . . . . . . . . . . 10
2.3 StructuralResultforCAC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.4 OverflowModeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3 Backgrounds 18
3.1 DynamicProgrammingFramework . . . . . . . . . . . . . . . . . . . . . . . 18
3.2 DiscreteEventSimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4 OptimalDeploymentofHWNs 26
4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.3 AssumptionsandSystemModel . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.4 MobilityandEquilibriumstate . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.5 OptimizationProblemFormulation . . . . . . . . . . . . . . . . . . . . . . . . 32
vi
4.6 SimulationResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
4.6.1 SimulationSetup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
4.6.2 EffectofInitialDeployment . . . . . . . . . . . . . . . . . . . . . . . 35
4.6.3 EffectofParametersSelection . . . . . . . . . . . . . . . . . . . . . . 37
4.7 ChapterSummary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
4.8 Nomenclature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
5 OverlayandIEEE802.11Integration 42
5.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
5.2 NetworkModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
5.3 OptimalCACPolicy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
5.3.1 OptimalityofThreshold-BasedPolicy . . . . . . . . . . . . . . . . . . 47
5.3.2 CACAlgorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.3.3 FindingPolicyπ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.4 EfficientComputationalAlgorithms . . . . . . . . . . . . . . . . . . . . . . . 52
5.4.1 ConventionalVIAlgorithm . . . . . . . . . . . . . . . . . . . . . . . 52
5.4.2 SVIAlgorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.4.3 SUVIAlgorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5.5 NumericalResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5.5.1 TheOptimalPolicy . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
5.5.2 ConvergenceSpeed . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
5.5.3 OptimalPolicyvs. CompleteSharing(CS) . . . . . . . . . . . . . . . 62
5.5.4 QoSPerformance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
5.6 ChapterSummary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
5.7 Nomenclature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
6 OverlayandWirelessMeshNetworkIntegration 71
6.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
vii
6.2 RelatedWorkandResearchContribution . . . . . . . . . . . . . . . . . . . . 73
6.3 SystemModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6.3.1 NetworkModelandUnderlyingProcesses . . . . . . . . . . . . . . . . 75
6.3.2 CallHandlingPolicy . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
6.3.3 UnderlayMeshNetworkOperation . . . . . . . . . . . . . . . . . . . 78
6.4 OptimizationFramework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
6.5 AnalysisModelforUnderlayOverflow . . . . . . . . . . . . . . . . . . . . . 81
6.5.1 AnalysisofMeshUnderlay . . . . . . . . . . . . . . . . . . . . . . . 81
6.5.2 AnalysisofOverflowTraffic . . . . . . . . . . . . . . . . . . . . . . . 83
6.6 StructuredControlofOverlayBS . . . . . . . . . . . . . . . . . . . . . . . . 88
6.7 StructuredCoordinateSearchAlgorithm . . . . . . . . . . . . . . . . . . . . . 91
6.8 NumericalResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
6.8.1 OptimalityofStructuredAdmissionControl . . . . . . . . . . . . . . . 100
6.8.2 ConvergenceSpeed . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
6.8.3 SCSAvs. CompleteSharingandGuard-ChannelPolicies . . . . . . . . 104
6.8.4 PartiallyObservablevs. PoissonOverflowModeling . . . . . . . . . . 105
6.8.5 QoSPerformance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
6.8.6 EffectofUserMobilityRate . . . . . . . . . . . . . . . . . . . . . . . 108
6.8.7 Exactvs. ApproximateModel . . . . . . . . . . . . . . . . . . . . . . 111
6.9 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
6.10 ChapterSummary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
6.11 Nomenclature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
7 ConcludingRemarks 121
7.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
7.2 FutureWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
viii
A IntegrationwithSingleAccessPoint 125
A.1 ProofofLemma5.3.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
B IntegrationwithWirelessMeshNetwork 131
B.1 ProofofLemma6.6.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
B.2 ProofofLemma6.6.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
Bibliography 134
ix
Chapter 1
Introduction
Existing wireless communication technologies can generally be classified by their service
model into two types: Local services providing high-bandwidth and low latency communi-
cations over a small area, and global services providing lower bandwidth to a wider area [1].
Currently, no single technology is capable of simultaneously providing high bandwidth to a
large number of mobile users over a wide area, and advances in the near future are unlikely
to change that given fundamental constraints imposed by power, and by signal-to-noise and
signal-to-interferenceratios[2].
Heterogeneous wireless networking is a paradigm that can overcome this limitation by us-
ing a combination of existing technologies. It is expected that such networks will be deployed
extensively in the near future to redefine our understanding and expectations of wireless com-
municationsbysimultaneouslyprovidinguniversalcoverageandhighbandwidthaccesswhere
available[3–5]. HeterogeneousWirelessNetworks(HWN)consistofseverallayersofdifferent
overlapping access technologies. This multi-layer architecture provides users with the option
ofchoosingbetweenavailableservicesbasedontrafficprofiles,mobilitypatterns,andQuality
ofService(QoS)preferences.
Currently, the most commonly deployed HWN architecture is the integration of 3G at the
overlaywithIEEE802.11attheunderlay[6]. AnexampleisshowninFig.1.1. Atthetoplayer,
1