Modeling, Analysis, and Optimization of Random Wireless Networks: Stochastic Geometry Approach

dc.contributor.authorElsawy, Hesham Mahmoud Medhat Mahmoud
dc.contributor.examiningcommitteeIrani, Pourang (Computer Science) Yahampath, Pradeepa (Electrical and Computer Engineering) Alouini, Mohamed-Slim (Physical Science & Engineering, King Abdullah University of Science and Technology)en_US
dc.contributor.supervisorHossain, Ekram (Electrical and Computer Engineering)en_US
dc.date.accessioned2014-03-27T20:42:26Z
dc.date.available2014-03-27T20:42:26Z
dc.date.issued2014-03-27
dc.degree.disciplineElectrical and Computer Engineeringen_US
dc.degree.levelDoctor of Philosophy (Ph.D.)en_US
dc.description.abstractRecently, stochastic geometry has been shown to be a very powerful tool to model, analyze, and design networks with random topologies such as wireless ad hoc and sensor networks as well as multi-tier cellular networks. In stochastic geometry analysis, point processes are used to model the positions and the channel access behaviors of the nodes. The thesis develops analytical frameworks to characterize the performance of large-scale wireless networks with random topologies. In particular, I use stochastic geometry tools to model, analyze, and design ad hoc networks, star-connected sensor networks, and infrastructure-based two-tier cellular networks. I have optimized the tradeoff between outage probability and spatial frequency reuse efficiency in carrier sensing-multiple-access based ad hoc networks. I have developed a novel spectrum efficient design paradigm for star-connected wireless sensor networks. For downlink transmission in cellular networks with cognitive femto access points (FAPs), I have quantified the performance gain imposed by cognition and developed a paradigm to optimize the spectrum sensing threshold for cognitive FAPs. Finally, I have developed a novel modeling paradigm for uplink transmission in cellular networks and obtained simple expressions for network performance metrics including the outage probability and average rate. Furthermore, I have revealed a transition point in the behavior of uplink transmission in cellular networks that depends on the relative values of the network parameters.en_US
dc.description.noteMay 2014en_US
dc.identifier.urihttp://hdl.handle.net/1993/23349
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectWirelessen_US
dc.subjectStochasticen_US
dc.subjectCellularen_US
dc.subjectNetworksen_US
dc.titleModeling, Analysis, and Optimization of Random Wireless Networks: Stochastic Geometry Approachen_US
dc.typedoctoral thesisen_US
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