Resource allocation in wireless access network

130 Pages·2016·1.59 MB·English

by  Prajwal Osti

Department of Communications and Networking
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DOCTORAL s DISSERTATIONS
DISSERTATIONS ity

2016
Aalto University publication series
DOCTORAL DISSERTATIONS 137/2016
Resource allocation in wireless access
network
A queueing theoretic approach
Prajwal Osti
A doctoral dissertation completed for the degree of Doctor of
Science (Technology) to be defended, with the permission of the
Aalto University School of Electrical Engineering, at a public
examination held at the lecture hall T2 of the school on 11 August
2016 at 12.
Aalto University
School of Electrical Engineering
Department of Communications and Networking
Supervising professor
Professor Riku Jäntti

Thesis advisors
Docent Samuli Aalto, Aalto University
Docent Pasi Lassila, Aalto University

Preliminary examiners
Professor Gustavo de Veciana, University of Texas at Austin, USA
Professor Dr Rudesindo Núñez-Queija, University of Amsterdam, the Netherlands

Opponent
Doctor Konstantin Avrachenkov, INRIA Sophia Antipolis, France
Aalto University publication series
DOCTORAL DISSERTATIONS 137/2016

© Prajwal Osti

ISBN 978-952-60-6915-9 (printed)
ISBN 978-952-60-6914-2 (pdf)
ISSN-L 1799-4934
ISSN 1799-4934 (printed)
ISSN 1799-4942 (pdf)
http://urn.fi/URN:ISBN:978-952-60-6914-2

Unigrafia Oy
Helsinki 2016

Finland
Abstract
Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto.fi
Author
Prajwal Osti
Name of the doctoral dissertation
Resource allocation in wireless access network: A queueing theoretic approach
Publisher School of Electrical Engineering
Unit Department of Communications and Networking
Series Aalto University publication series DOCTORAL DISSERTATIONS 137/2016
Field of research Communications Engineering
Manuscript submitted 10 February 2016 Date of the defence 11 August 2016
Permission to publish granted (date) 9 May 2016 Language English
Monograph Article dissertation Essay dissertation
Abstract

To meet its performance targets, the future 5G networks need to greatly optimize the Radio
Access Networks (RANs), which connect the end users to the core network. In this thesis, we
develop mathematical models to study three aspects of the operation of the RAN in modern
wireless systems. The models are analyzed using the techniques borrowed mainly from
queueing theory and stochastic control. Also, simulations are extensively used to gain further
insights.
First, we provide a detailed Markov model of the random access process in LTE. From this,
we observe that the bottleneck in the signaling channel causes congestion in the access when
a large number of M2M devices attempt to enter the network. Then, in the context of the so-
called Heterogeneous networks (HetNets), we suggest dynamic load balancing schemes that
alleviate this congestion and reduce the overall access delay.
We then use flow-level models for elastic data traffic to study the problem of coordinating
the activities of the neighboring base stations. We seek to minimize the flow-level delay when
there are various classes of users. We classify the users based on their locations, or, in dynamic
TDD systems, on the direction of service the network is providing to them. Using interacting
queues and different operating policies of running such queues, we study the amount of gain
the dynamic policies can provide over the static probabilistic policies. Our results show that
simple dynamic policies can provide very good performance in the cases considered.
Finally, we consider the problem of opportunistically scheduling the flows of users with time-
varying channels taking into account the size of data they need to transfer. Using flow-level
models in a system with homogeneous channels, we provide the optimal scheduling policy
when there are no new job arrivals. We also suggest the method to implement such a policy in
a time-slotted system.
With heterogeneous channels, the problem is intractable for the flow-level techniques.
Therefore, we utilize the framework of the restless-multi-armed-bandit (RMAB) problems
employing the so-called Whittle index approach. The Whittle index approach, by relaxing the
scheduling constraints, makes the problem separable, and thereby provides an exact solution
to the modified problem. Our simulations suggest that when this solution is applied as a
heuristic to the original problem, it gives good performance, even with dynamic job arrivals.
Keywords Resource allocation, Wireless network, Queueing theory, Scheduling
ISBN (printed) 978-952-60-6915-9 ISBN (pdf) 978-952-60-6914-2
ISSN-L 1799-4934 ISSN (printed) 1799-4934 ISSN (pdf) 1799-4942
Location of publisher Helsinki Location of printing Helsinki Year 2016
Pages 277 urn http://urn.fi/URN:ISBN:978-952-60-6914-2

Preface
This thesis is the outcome of my work done at the Department of Com-
municationsandNetworking,AaltoUniversitySchoolofElectricalEngi-
neeringbetween2010–2015. Theresearchworkshavebeencarriedoutas
partsofAWA,EXAM,HEWINETS,HIIFNS,IoT,ITTECH5G,M2MRISE
and TOP-Energy projects funded by various organizations such as the
AcademyofFinland, CassidianSystems, EITDigital, EITICTLabs, Er-
icsson,Nokia-SiemensNetworks,TEKES,etc.
At this point, I would like to express my sincere gratitude to my in-
structorsDr.SamuliAalto—myoriginalsupervisorunderwhosetutelage
I started my doctoral work—and Dr.Pasi Lassila for their constant and
generoussupportandencouragementduringthewholeprocess. Iwould
alsoliketothankProf. RikuJänttiforagreeingtobemysupervisorfor
the dissertation. A special word of appreciation goes out to Dr.Tuomas
Tirronen,Ms.AnnaLarmoandDr.AleksiPenttinen,who,besidesmyad-
visors, haveco-authoredthepaperscompiledinthisthesis. Iwouldalso
like to thank the anonymous reviewers who have helped me to improve
thecontentofthesepapers.
In addition, I appreciate the kind gestures of Prof.Gustavo de Veciana
andProf.RudesindoNúñez-Queijaforagreeingtobemypreliminaryex-
aminersandpointingoutthepossibleareasofimprovementinthethesis
after having read the initial draft. Moreover, I would like to express my
sinceregratitudetoDr.KonstantinAvrachenkovforwillingtobemyop-
ponent.
I am also very humbled by the great support I have received from my
colleagues at the department over the years. I thank Dr.Pekka Lampio
forthewonderfulvarietiesofteasheofferedduringthecoffeebreaksand
hisdiscussionsaboutvariousrandomtopics. Myspecialthanksgooutto
thesecretariesMs.SannaPatana,Ms.SariKivelöandMs.HeliLiukkofor
1
Preface
theirhelpinadministrativeandofficialmatters, andtoMr.VictorNässi
forprovidingeverykindofsupport,alwayswithabroadsmileonhisface.
Furthermore, I thank Ms.Marja Leppäharju and Ms.Anne-Mari Karro
fromtheStudentServiceformakingthedissertationprocesssosmooth.
Iwouldliketoexpressmydeepestgratitudeforthewarmfriendshipof
manypeoplehereinFinland,whohaveprovidedthemuchneededdistrac-
tion from the work at appropriate times through various forms of social
gatherings. IamalsohumbledbythegenerosityoftheFinnishpeoplefor
theirsupportwhencarryingoutmystudies,andforprovidingmeanop-
portunitytobroadenmyhorizonsbyintroducingmetoasuchadifferent
wayoflifethanIwasusedto. Finally, Iwouldliketothankmyparents
and sister—Mamu, Baba and Lora—for always being there for me, even
iftheylivethousandsofkilometersaway.
Espoo,July8,2016,
PrajwalOsti
2
Contents
Preface 1
Contents 3
ListofPublications 7
Author’sContribution 9
1. Introduction 21
1.1 Researchproblems . . . . . . . . . . . . . . . . . . . . . . . . 24
1.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
1.3 Contributionsofthethesis . . . . . . . . . . . . . . . . . . . . 28
1.4 Structureofthethesis . . . . . . . . . . . . . . . . . . . . . . 30
2. Machine-to-machinerandomaccess 31
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.2 Relatedwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.3 PDCCHcongestion . . . . . . . . . . . . . . . . . . . . . . . . 34
2.3.1 Researchproblem . . . . . . . . . . . . . . . . . . . . . 34
2.3.2 LTErandomaccessprocedure . . . . . . . . . . . . . . 35
2.3.3 Modelandanalysis . . . . . . . . . . . . . . . . . . . . 36
2.3.4 Numericalresults . . . . . . . . . . . . . . . . . . . . . 39
2.4 Loadbalancinginheterogeneoussystems . . . . . . . . . . . 41
2.4.1 Stabilityissues . . . . . . . . . . . . . . . . . . . . . . 43
2.4.2 Staticloadbalancing . . . . . . . . . . . . . . . . . . . 43
2.4.3 Dynamicloadbalancing . . . . . . . . . . . . . . . . . 44
2.5 LTE-LTEHetNetloadbalancing . . . . . . . . . . . . . . . . 45
2.5.1 Researchproblem . . . . . . . . . . . . . . . . . . . . . 45
2.5.2 MultichannelSlottedAloha . . . . . . . . . . . . . . . 45
2.5.3 MCSAmodel . . . . . . . . . . . . . . . . . . . . . . . . 46
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Contents
2.5.4 Operatingpolicies . . . . . . . . . . . . . . . . . . . . . 47
2.5.5 NumericalresultsforMCSA-basedfemtos . . . . . . 48
2.6 LTE-WLANHetNetloadbalancing . . . . . . . . . . . . . . . 50
2.6.1 Researchproblem . . . . . . . . . . . . . . . . . . . . . 50
2.6.2 CSMAprotocol. . . . . . . . . . . . . . . . . . . . . . . 50
2.6.3 CSMAmodel . . . . . . . . . . . . . . . . . . . . . . . . 50
2.6.4 Operatingpolicies . . . . . . . . . . . . . . . . . . . . . 51
2.6.5 NumericalresultsforCSMA-basedfemtos . . . . . . 53
2.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3. Intercellcoordinationinwirelesssystems 55
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
3.2 Relatedwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.3 Coordinationwithlocation-baseduserclasses. . . . . . . . . 58
3.3.1 Researchproblem . . . . . . . . . . . . . . . . . . . . . 58
3.3.2 Systemmodel . . . . . . . . . . . . . . . . . . . . . . . 59
3.3.3 Optimalcoordinationproblem . . . . . . . . . . . . . . 60
3.3.4 Stabilityissues . . . . . . . . . . . . . . . . . . . . . . 62
3.3.5 Dynamicpolicies . . . . . . . . . . . . . . . . . . . . . 63
3.3.6 Numericalresults . . . . . . . . . . . . . . . . . . . . . 65
3.4 CoordinationindynamicTDD-LTEsystems. . . . . . . . . . 66
3.4.1 Researchproblem . . . . . . . . . . . . . . . . . . . . . 66
3.4.2 Systemmodel . . . . . . . . . . . . . . . . . . . . . . . 67
3.4.3 Optimalcoordinationproblem . . . . . . . . . . . . . . 68
3.4.4 Stabilityissues . . . . . . . . . . . . . . . . . . . . . . 70
3.4.5 Dynamicpolicies . . . . . . . . . . . . . . . . . . . . . 71
3.4.6 Stochasticoptimalityresults . . . . . . . . . . . . . . 76
3.4.7 Physicalmodel. . . . . . . . . . . . . . . . . . . . . . . 77
3.4.8 Numericalresults . . . . . . . . . . . . . . . . . . . . . 78
3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
4. Opportunisticschedulinginwirelesssystems 85
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
4.2 Relatedwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
4.3 Size-awareopportunisticschedulingproblem . . . . . . . . . 88
4.4 Homogeneoususerpopulation . . . . . . . . . . . . . . . . . . 90
4.4.1 Flow-levelproblemdescription . . . . . . . . . . . . . 90
4.4.2 Optimizationattheflowlevel . . . . . . . . . . . . . . 92
4.4.3 SolvingOPatthetimeslotlevel . . . . . . . . . . . . . 96
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Contents
4.4.4 Numericalresults . . . . . . . . . . . . . . . . . . . . . 96
4.5 Heterogeneoususerpopulation . . . . . . . . . . . . . . . . . 99
4.5.1 Relaxedopportunisticschedulingproblem. . . . . . . 100
4.5.2 HeuristicforOPatthetimeslotlevel. . . . . . . . . . 103
4.5.3 Numericalresults . . . . . . . . . . . . . . . . . . . . . 103
4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
5. Conclusions 109
References 113
Errata 121
Publications 125
5