Performance Analysis of Switching Based Techniques for Wireless Applications

Handle URI:
http://hdl.handle.net/10754/224977
Title:
Performance Analysis of Switching Based Techniques for Wireless Applications
Authors:
Gaaloul, Fakhreddine
Abstract:
Switching techniques have been first proposed as a spacial diversity techniques. These techniques have been shown to reduce considerably the processing load while letting multi-antenna systems achieve a specific target performance. In this thesis, we take a different look at the switching schemes by implementing them for different other wireless applications. More specifically, this thesis consists of three main parts, where the first part considers a multiuser environment and an adaptive scheduling algorithm based on the switching with post-selection scheme for statistically independent but non-identically distributed channel conditions. The performance of this switched based scheduler is investigated and a multitude of performance metrics are presented. In a second part, we propose and analyze the performance of three switched-based algorithms for interference reduction in the downlink of over-loaded femtocells. For instance, performance metrics are derived in closed-form and these metrics are used to compare these three proposed schemes. Finally in a third part, a switch based opportunistic channel access scheme is proposed for a cognitive radio system and its performance is analyzed in terms of two new proposed metrics namely the average cognitive radio access and the waiting time duration.
Advisors:
Alouini, Mohamed-Slim ( 0000-0003-4827-1793 )
Committee Member:
Radaydeh, Redha M.; Shihada, Basem ( 0000-0003-4434-4334 ) ; Sultan Salem, Ahmed Kamal
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Program:
Electrical Engineering
Issue Date:
May-2012
Type:
Thesis
Appears in Collections:
Theses; Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.advisorAlouini, Mohamed-Slimen
dc.contributor.authorGaaloul, Fakhreddineen
dc.date.accessioned2012-05-21T11:48:55Z-
dc.date.available2012-05-21T11:48:55Z-
dc.date.issued2012-05en
dc.identifier.urihttp://hdl.handle.net/10754/224977en
dc.description.abstractSwitching techniques have been first proposed as a spacial diversity techniques. These techniques have been shown to reduce considerably the processing load while letting multi-antenna systems achieve a specific target performance. In this thesis, we take a different look at the switching schemes by implementing them for different other wireless applications. More specifically, this thesis consists of three main parts, where the first part considers a multiuser environment and an adaptive scheduling algorithm based on the switching with post-selection scheme for statistically independent but non-identically distributed channel conditions. The performance of this switched based scheduler is investigated and a multitude of performance metrics are presented. In a second part, we propose and analyze the performance of three switched-based algorithms for interference reduction in the downlink of over-loaded femtocells. For instance, performance metrics are derived in closed-form and these metrics are used to compare these three proposed schemes. Finally in a third part, a switch based opportunistic channel access scheme is proposed for a cognitive radio system and its performance is analyzed in terms of two new proposed metrics namely the average cognitive radio access and the waiting time duration.en
dc.language.isoenen
dc.titlePerformance Analysis of Switching Based Techniques for Wireless Applicationsen
dc.typeThesisen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
thesis.degree.grantorKing Abdullah University of Science and Technologyen_GB
dc.contributor.committeememberRadaydeh, Redha M.en
dc.contributor.committeememberShihada, Basemen
dc.contributor.committeememberSultan Salem, Ahmed Kamalen
thesis.degree.disciplineElectrical Engineeringen
thesis.degree.nameMaster of Scienceen
dc.person.id113276en
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