Title:
Resource allocation for vehicular communications

dc.contributor.advisor Li, Geoffrey Ye
dc.contributor.author Liang, Le
dc.contributor.committeeMember Stuber, Gordon L.
dc.contributor.committeeMember Ma, Xiaoli
dc.contributor.committeeMember Weitnauer, Mary Ann
dc.contributor.committeeMember Yu, Xingxing
dc.contributor.department Electrical and Computer Engineering
dc.date.accessioned 2019-01-16T17:24:12Z
dc.date.available 2019-01-16T17:24:12Z
dc.date.created 2018-12
dc.date.issued 2018-11-09
dc.date.submitted December 2018
dc.date.updated 2019-01-16T17:24:12Z
dc.description.abstract This thesis aims to develop efficient and effective resource allocation schemes to meet the diverse quality-of-service requirements of vehicular communications while taking into account the strong dynamics in vehicular environments. Specifically, we study the spectrum and power allocation problem in device-to-device (D2D)-enabled vehicular networks. We design low-complexity algorithms to maximize the capacity of vehicle-to-infrastructure (V2I) links while guaranteeing the reliability of each vehicle-to-vehicle (V2V) link, evaluated in terms of outage probabilities, using only slowly varying large-scale fading information or delayed rapidly varying small-scale fading information from periodic feedback. To further improve spectrum utilization, we investigate the case where each V2I link shares spectrum with multiple V2V links and exploit graph theoretic tools to develop high performance approximation algorithms to support flexible spectrum sharing in vehicular communications. For ease of (semi-)distributed resource management, we exploit recent results in multi-agent reinforcement learning to develop a learning-based resource allocation algorithm for vehicular agents. Resource sharing decisions are made based on a mix of slowly-varying global large-scale channel information and fast-varying local observations. The four proposed schemes, including both centralized and semi-distributed designs with varying complexity-performance tradeoffs, constitute a comprehensive study of the resource allocation problem in vehicular communications.
dc.description.degree Ph.D.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/60780
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Resource allocation
dc.subject Vehicular communications
dc.title Resource allocation for vehicular communications
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.corporatename School of Electrical and Computer Engineering
local.contributor.corporatename College of Engineering
relation.isOrgUnitOfPublication 5b7adef2-447c-4270-b9fc-846bd76f80f2
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level Doctoral
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