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dc.contributor.advisorKaraşan, Ezhan
dc.contributor.authorÜnal, Deniz
dc.date.accessioned2018-08-31T12:32:21Z
dc.date.available2018-08-31T12:32:21Z
dc.date.copyright2018-08
dc.date.issued2018-08
dc.date.submitted2018-08-28
dc.identifier.urihttp://hdl.handle.net/11693/47759
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.): Bilkent University, Department of Electrical and Electronics Engineering, İhsan Doğramacı Bilkent University, 2018.en_US
dc.descriptionIncludes bibliographical references (leaves 62-65).en_US
dc.description.abstractImproving spectral efficiency is a key objective in next generation wireless networks. Recent advances in self-interference cancellation techniques made in-band full-duplex wireless communications possible. Unlike half-duplex systems which require orthogonal frequency or time resources to separate transmission and reception, in-band full-duplex radios utilize the channel bidirectionally and theoretically can double the ergodic capacity. However due to cost, power consumption and complexity constraints, mobile stations may not support this technology. In this work, operation of full-duplex base stations with legacy half-duplex mobile stations is considered. An inherent issue of this topology is the presence of signi cant inter-user interference between half-duplex mobile stations. In order to manage this at network level, an optimization problem is formulated for a cellular network topology. Solution methods and their corresponding sum throughput are compared with respect to the number of mobile stations. An analytic solution is presented to evaluate the throughput and full-duplex gains of random pairing method for the same scenario. Then the case of limited channel state information is evaluated and a learning strategy is introduced to extend the user pairing problem to a continuous case. Performance evaluation with 100 mobile stations show that the proposed learning strategy can reduce the overhead airtime more than 80%. A weighted random sequential algorithm which is integrated to the learning process is proposed, and its performance evaluation under random walk and random waypoint mobility cases are performed.en_US
dc.description.statementofresponsibilityby Deniz Ünal.en_US
dc.format.extentxii, 65 leaves : charts ; 30 cm.en_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectWireless Networksen_US
dc.subjectFull-Duplexen_US
dc.subjectMobilityen_US
dc.subjectStation Pairingen_US
dc.titleUser grouping in wireless networks with full duplex base stations and legacy mobile stationsen_US
dc.title.alternativeTam çift yönlü baz istasyonlu ve eski mobil istasyonlu kablosuz ağlarda kullanıcı gruplamasıen_US
dc.typeThesisen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US
dc.identifier.itemidB158923


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