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Resource allocation in wireless access network PDF

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Department of Communications and Networking This thesis summarizes the works related to A P Resource allocation in three different aspects of resource alto-D rajw allocation at the radio access nework, which D 1 al a(5rGe u) sweifruell eins st hnee tdwesoirgkns .o f fifth generation 37/201 Osti wireless access network 6 R e First, the random access procedure of LTE is s o A queueing theoretic approach u analyzed when massive number of machine- r c to-machine (M2M) users are present. The e a l causes of congestion are investigated and lo c possible remedies using heterogeneous a t i networks (HetNets) is suggested. on Prajwal Osti in w The problem of intercell coordination i r e between interfering base stations is then l e s considered. In different problem settings, s a various policies to mitigate to this cc e interference that aid in minimizing delays of s s n the users are studied. e t w o Finally, the problem of scheduling downlink rk users in a cell is analyzed when the station is fully aware of the channel conditions of the users and the size of their jobs. The aim again is to minimize the delay. ISBN 978-952-60-6915-9 (printed) BUSINESS + 9 ISBN 978-952-60-6914-2 (pdf) ECONOMY H ISSN-L 1799-4934 S ISSN 1799-4934 (printed) ART + T F ISSN 1799-4942 (pdf) DESIGN + M ARCHITECTURE G* Aalto University Aa agj SDcehpoaortlm oef nEtl eocf tCricoaml mEunngiicnaeteiorinnsg and Networking STECCIEHNNCOEL +O GY lto U b www.aalto.fi n fj CROSSOVER iv + er DOCTORAL 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 3 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 4 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

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We then use flow-level models for elastic data traffic to study the problem of coordinating Keywords Resource allocation, Wireless network, Queueing theory, Scheduling . 3.4 Coordination in dynamic TDD-LTE systems . DL. Downlink. eNB. eNodeB. EVDO. Evolution-Data Optimized. FP.
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