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dc.contributor.authorΕφραίμ, Χρίστος-
dc.description.abstractThe proliferation of connected devices has led to very strict requirements for next-generation wireless networks, taking into consideration environmental as well as economic concerns. In particular, one of the primary goals in the design of fifth-generation (5G) wireless networks is to satisfy the extremely high data rate (traffic demand) of users with the minimum energy consumption. For this purpose, a new performance indicator, namely, energy efficiency (EE), has been proposed in the literature which is measured in bits/Joule and expresses the amount of information that can be reliably transmitted per unit of consumed energy. This Dissertation deals with the design of efficient optimization algorithms for next-generation wireless networks, including terrestrial as well as satellite communication systems. More specifically, the theory of sequential convex optimization (SCO) is applied to solve challenging optimization problems, such as the maximization of several EE-metrics, so as to develop energy-efficient power allocation strategies. SCO is a powerful mathematical tool that can be used to solve nonconvex optimization problems by solving a sequence of convex optimization problems. This method is theoretically guaranteed to converge for any initial feasible point and, under suitable constraint qualifications, achieves a stationary point (i.e., a point that satisfies the Karush-Kuhn-Tucker (KKT) conditions) of the original problem. Furthermore, we study some combinatorial optimization problems in satellite networks (SatNets), which are proven to be NP-hard. In particular, we focus on the optimum selection of ground stations (GSs) in SatNets with site diversity (SD), satisfying given availability requirements. SD technique is used to improve the availability of satellite systems by mitigating the atmospheric impairments, such as rain (for radio frequencies) and cloud coverage (for optical frequencies). Moreover, we present global optimization algorithms, based on the branch-and-bound (B&B) method and dynamic programming (DP), as well as a polynomial-time approximation algorithm with provable performance guarantee. Finally, we examine a load-sharing smart gateway diversity (LS-SGD) architecture in SatNets, which has been recently proposed in the literature. For this diversity scheme, we define the system outage probability (SOP) based on the Poisson binomial distribution (PBD) and taking into account the traffic demand as well as the gateway (GW) capacity. In addition, we present several methods for the exact and approximate calculation of SOP.en_US
dc.subjectwireless networksen_US
dc.subjectsatellite communicationsen_US
dc.subjectenergy efficiencyen_US
dc.subjectresource allocationen_US
dc.subjectsite diversityen_US
dc.subjectsmart gateway diversityen_US
dc.subjectoutage probabilityen_US
dc.subjectground station selectionen_US
dc.subjectsequential convex optimizationen_US
dc.subjectcombinatorial optimizationen_US
dc.subjectcomputational complexityen_US
dc.subjectbranch-and-bound methoden_US
dc.subjectdynamic programmingen_US
dc.titleOptimization Algorithm Design and Performance Analysis for Next-Generation Wireless Networksen_US
dc.contributor.supervisorΠαναγόπουλος Αθανάσιοςen_US
dc.departmentΤομέας Συστημάτων Μετάδοσης Πληροφορίας και Τεχνολογίας Υλικώνen_US
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