Poisson Line Cox Process: Foundations and Applications to Vehicular Networks Synthesis Lectures PDF
Preview Poisson Line Cox Process: Foundations and Applications to Vehicular Networks Synthesis Lectures
Series ISSN: 2690-4306 D H Synthesis Lectures on I L L Learning, Networks, and Algorithms O N • C H E T Series Editors: R. Srikant, University of Illinois at Urbana-Champaign L U Lei Yang, University of Michigan, Ann Arbor R Poisson Line Cox Process FHaoruprneedt aS.t Diohnillso na, nVidrg iAniap Tpeclhications to Vehicular Networks Vishnu Vardhan Chetlur, Virginia Tech This book provides a comprehensive treatment of the Poisson line Cox process (PLCP) and its applications to P O vehicular networks. The PLCP is constructed by placing points on each line of a Poisson line process (PLP) as I S per an independent Poisson point process (PPP). For vehicular applications, one can imagine the layout of the S O road network as a PLP and the vehicles on the roads as the points of the PLCP. First, a brief historical account N of the evolution of the theory of PLP is provided to familiarize readers with the seminal contributions in this L I area. In order to provide a self-contained treatment of this topic, the construction and key fundamental properties N E of both PLP and PLCP are discussed in detail. The rest of the book is devoted to the applications of these C models to a variety of wireless networks, including vehicular communication networks and localization networks. O X Specifically, modeling the locations of vehicular nodes and roadside units (RSUs) using PLCP, the signal-to- P interference-plus-noise ratio (SINR)-based coverage analysis is presented for both ad hoc and cellular network R O models. For a similar setting, the load on the cellular macro base stations (MBSs) and RSUs in a vehicular C network is also characterized analytically. For the localization networks, PLP is used to model blockages, which is E S shown to facilitate the characterization of asymptotic blind spot probability in a localization application. Finally, S tqs huuege gspteaisotthnio sdBn iisasn tso aentndh c feleua tcraughrreeaealry sad coiotrnefe r cttitrshiatoeinnc sossp r foioogfrr it rnaae atssilepo arenerc csinehaael. rtccwahso ero kofs ft PhanLe dCa uPutr haboraerns a, nptahlaliynsz niesid nt,g hw.e hTh fiicrehs t b cbaoonoo kbk e i tslh ecvaoet nrsacpgleuecddi fietdoc a awlnlyist whfo eccruo csnreicstri ecotanel the self-contained mathematical treatment of the PLCP. The ideal audience of this book is graduate students apso iwnet lpl raos creessseeasr, cahnedr sa irne ianctaedreemsteiad ainnd t hine dfiuesltdr yo fw shtoo cahraes ftaicm gielioamr wetirtyh apnrdo bvaebhiilcituyl atrh neoertwy, ohrakvse. Gsoimveen e txhpeo dsuivreer tsoe backgrounds of the potential readers, the focus has been on providing an accessible and pedagogical treatment of this topic by consciously avoiding the measure theoretic details without compromising mathematical rigor. M O About Synthesis R G This volume is a printed version of a work that appears in the Synthesis Digital Library of Engineering A and Computer Science. Synthesis books provide concise, original presentations of important research and N development topics, published quickly, in digital and print formats. & C L A Y P O store.morganclaypool.com O L Poisson Line Cox Process Foundations and Applications to Vehicular Networks Synthesis Lectures on Learning, Networks, and Algorithms Editor LeiYing,UniversityofMichigan,AnnArbor EditorEmeritus R.Srikant,UniversityofIllinoisatUrbana-Champaign FoundingEditorEmeritus JeanWalrand,UniversityofCalifornia,Berkeley SynthesisLecturesonLearning,Networks,andAlgorithmsisanongoingseriesof75-to150-page publicationsontopicsonthedesign,analysis,andmanagementofcomplexnetworkedsystems usingtoolsfromcontrol,communications,learning,optimization,andstochasticanalysis.Each lectureisaself-containedpresentationofonetopicbyaleadingexpert.Thetopicsincludelearning, networks,andalgorithms,andcoverabroadspectrumofapplicationstonetworkedsystems includingcommunicationnetworks,data-centernetworks,social,andtransportationnetworks. Theseriesisdesignedto: • Providethebestavailablepresentationsofimportantaspectsofcomplexnetworkedsystems. • Helpengineersandadvancedstudentskeepupwithrecentdevelopmentsinarapidly evolvingfieldofscienceandtechnology. • Facilitatethedevelopmentofcoursesinthisfield. PoissonLineCoxProcess:FoundationsandApplicationstoVehicularNetworks HarpreetS.DhillonandVishnuVardhanChetlur 2020 AgeofInformation:ANewMetricforInformationFreshness YinSun,IgorKadota,RajatTalak,andEytanModiano 2019 Multi-ArmedBandits:TheoryandApplicationstoOnlineLearninginNetworks QingZhao 2019 iv DiffusionSourceLocalizationinLargeNetworks LeiYingandKaiZhu 2018 CommunicationsNetworks:AConciseIntroduction,SecondEdition JeanWalrandandShyamParekh 2017 BATSCodes:TheoryandPractice ShenghaoYangandRaymondW.Yeung 2017 AnalyticalMethodsforNetworkCongestionControl StevenH.Low 2017 AdvancesinMulti-ChannelResourceAllocation:Throughput,Delay,andComplexity BoJi,XiaojunLin,andNessB.Shroff 2016 APrimeronPhysical-LayerNetworkCoding SoungChangLiew,LuLu,andShengliZhang 2015 SharingNetworkResources AbhayParekhandJeanWalrand 2014 WirelessNetworkPricing JianweiHuangandLinGao 2013 PerformanceModeling,StochasticNetworks,andStatisticalMultiplexing,Second Edition RaviR.Mazumdar 2013 PacketswithDeadlines:AFrameworkforReal-TimeWirelessNetworks I-HongHouandP.R.Kumar 2013 Energy-EfficientSchedulingunderDelayConstraintsforWirelessNetworks RandallBerry,EytanModiano,andMurtazaZafer 2012 NSSimulatorforBeginners EitanAltmanandTaniaJiménez 2012 v NetworkGames:Theory,Models,andDynamics IshaiMenacheandAsumanOzdaglar 2011 AnIntroductiontoModelsofOnlinePeer-to-PeerSocialNetworking GeorgeKesidis 2010 StochasticNetworkOptimizationwithApplicationtoCommunicationandQueueing Systems MichaelJ.Neely 2010 SchedulingandCongestionControlforWirelessandProcessingNetworks LibinJiangandJeanWalrand 2010 PerformanceModelingofCommunicationNetworkswithMarkovChains JeonghoonMo 2010 CommunicationNetworks:AConciseIntroduction JeanWalrandandShyamParekh 2010 PathProblemsinNetworks JohnS.BarasandGeorgeTheodorakopoulos 2010 PerformanceModeling,LossNetworks,andStatisticalMultiplexing RaviR.Mazumdar 2009 NetworkSimulation RichardM.Fujimoto,KalyanS.Perumalla,andGeorgeF.Riley 2006 Copyright©2020byMorgan&Claypool Allrightsreserved.Nopartofthispublicationmaybereproduced,storedinaretrievalsystem,ortransmittedin anyformorbyanymeans—electronic,mechanical,photocopy,recording,oranyotherexceptforbriefquotations inprintedreviews,withoutthepriorpermissionofthepublisher. PoissonLineCoxProcess:FoundationsandApplicationstoVehicularNetworks HarpreetS.DhillonandVishnuVardhanChetlur www.morganclaypool.com ISBN:9781681738420 paperback ISBN:9781681738437 ebook ISBN:9781681738444 hardcover DOI10.2200/S01007ED1V01Y202004LNA024 APublicationintheMorgan&ClaypoolPublishersseries SYNTHESISLECTURESONLEARNING,NETWORKS,ANDALGORITHMS Lecture#24 Editor:LeiYing,UniversityofMichigan,AnnArbor EditorEmeritus:R.Srikant,UniversityofIllinoisatUrbana-Champaign FoundingEditorEmeritus:JeanWalrand,UniversityofCalifornia,Berkeley SeriesISSN Print2690-4306 Electronic2690-4314 Poisson Line Cox Process Foundations and Applications to Vehicular Networks Harpreet S. Dhillon and Vishnu Vardhan Chetlur VirginiaTech SYNTHESISLECTURESONLEARNING,NETWORKS,ANDALGORITHMS #24 M &C Morgan &cLaypool publishers ABSTRACT ThisbookprovidesacomprehensivetreatmentofthePoissonlineCoxprocess(PLCP)andits applications to vehicular networks. The PLCP is constructed by placing points on each line of aPoissonlineprocess(PLP)asperanindependentPoissonpointprocess(PPP).Forvehicular applications,onecanimaginethelayoutoftheroadnetworkasaPLPandthevehiclesonthe roadsasthepointsofthePLCP.First,abriefhistoricalaccountoftheevolutionofthetheory ofPLPisprovidedtofamiliarizereaderswiththeseminalcontributionsinthisarea.Inorderto provideaself-containedtreatmentofthistopic,theconstructionandkeyfundamentalproperties ofbothPLPandPLCParediscussedindetail.Therestofthebookisdevotedtotheapplications ofthesemodelstoavarietyofwirelessnetworks,includingvehicularcommunicationnetworks andlocalizationnetworks.Specifically,modelingthelocationsofvehicularnodesandroadside units (RSUs) using PLCP, the signal-to-interference-plus-noise ratio (SINR)-based coverage analysisispresentedforbothadhocandcellularnetworkmodels.Forasimilarsetting,theload onthecellularmacrobasestations(MBSs)andRSUsinavehicularnetworkisalsocharacterized analytically.Forthelocalizationnetworks,PLPisusedtomodelblockages,whichisshownto facilitatethecharacterizationofasymptoticblindspotprobabilityinalocalizationapplication. Finally,thepathdistancecharacteristicsforaspecialcaseofPLCPareanalyzed,whichcanbe leveragedtoanswercriticalquestionsintheareasoftransportationnetworksandurbanplanning. Thebookisconcludedwithconcretesuggestionsonfuturedirectionsofresearch. Basedlargelyontheoriginalresearchoftheauthors,thisisthefirstbookthatspecifically focuses on the self-contained mathematical treatment of the PLCP. The ideal audience of this bookisgraduatestudentsaswellasresearchersinacademiaandindustrywhoarefamiliarwith probability theory, have some exposure to point processes, and are interested in the field of stochastic geometry and vehicular networks. Given the diverse backgrounds of the potential readers,thefocushasbeenonprovidinganaccessibleandpedagogicaltreatmentofthistopicby consciouslyavoidingthemeasuretheoreticdetailswithoutcompromisingmathematicalrigor. KEYWORDS stochasticgeometry,PoissonlineCoxprocess(PLCP),Poissonlineprocess(PLP), coverageprobability,vehicularnetworks,vehicularadhocnetwork(VANET),cel- lularvehicle-to-everything(C-V2X)
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