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dc.contributor.advisorVishwanath, Sriramen
dc.creatorJose, Jubinen
dc.date.accessioned2011-10-21T19:27:56Zen
dc.date.available2011-10-21T19:27:56Zen
dc.date.issued2011-08en
dc.date.submittedAugust 2011en
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2011-08-4015en
dc.descriptiontexten
dc.description.abstractWireless networks promise ubiquitous communication, and thus facilitate an array of applications that positively impact human life. At a fundamental level, these networks deal with compression and transmission of sources over channels. Thus, accomplishing this task efficiently is the primary challenge shared by these applications. In practice, sources include data and video while channels include interference and relay networks. Hence, effective source and channel aware resource allocation for these scenarios would result in a comprehensive solution applicable to real-world networks. This dissertation studies the problem of source and channel aware resource allocation in certain scenarios. A framework for network resource allocation that stems from rate-distortion theory is presented. Then, an optimal decomposition into an application-layer compression control, a transport-layer congestion control and a network-layer scheduling is obtained. After deducing insights into compression and congestion control, the scheduling problem is explored in two cross-layer scenarios. First, appropriate queue architecture for cooperative relay networks is presented, and throughput-optimality of network algorithms that do not assume channel-fading and input-queue distributions are established. Second, decentralized algorithms that perform rate allocation, which achieve the same overall throughput region as optimal centralized algorithms, are derived. In network optimization, an underlying throughput region is assumed. Hence, improving this throughput region is the next logical step. This dissertation addresses this problem in the context of three significant classes of interference networks. First, degraded networks that capture highly correlated channels are explored, and the exact sum capacity of these networks is established. Next, multiple antenna networks in the presence of channel uncertainty are considered. For these networks, robust optimization problems that result from linear precoding are investigated, and efficient iterative algorithms are derived. Last, multi-cell time-division-duplex systems are studied in the context of corrupted channel estimates, and an efficient linear precoding to manage interference is developed.en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.subjectNetworkingen
dc.subjectNetwork controlen
dc.subjectQueueing theoryen
dc.subjectRate allocationen
dc.subjectDistributed algorithmsen
dc.subjectWireless communicationen
dc.subjectInterference channelen
dc.subjectCapacityen
dc.subjectMultiple antennasen
dc.titleSource and channel aware resource allocation for wireless networksen
dc.date.updated2011-10-21T19:28:09Zen
dc.identifier.slug2152/ETD-UT-2011-08-4015en
dc.contributor.committeeMemberAndrews, Jeffrey G.en
dc.contributor.committeeMemberShakkottai, Sanjayen
dc.contributor.committeeMemberde Veciana, Gustavoen
dc.contributor.committeeMemberMorton, Daviden
dc.description.departmentElectrical and Computer Engineeringen
dc.type.genrethesisen
thesis.degree.departmentElectrical and Computer Engineeringen
thesis.degree.disciplineElectrical and Computer Engineeringen
thesis.degree.grantorUniversity of Texas at Austinen
thesis.degree.levelDoctoralen
thesis.degree.nameDoctor of Philosophyen


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