Spectrum Sensing for Cognitive Radio Networks

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dc.contributor.advisorMark, Brian L.
dc.contributor.advisorEphraim, Yariv
dc.contributor.authorSun, Yuandao
dc.creatorSun, Yuandao
dc.date.accessioned2016-04-19T19:29:44Z
dc.date.available2016-04-19T19:29:44Z
dc.date.issued2015
dc.description.abstractCognitive radio has been proposed as a technology for reclaiming highly under-utilized spectrum resources to satisfy the increasing spectrum demand. In a cognitive radio network, unlicensed or secondary users (SUs) are permitted to make use of portions of a licensed spectrum band that are left idle by the licensed or primary users (PUs). These idle portions of spectrum, called spectrum holes, exist in the dimensions of space, time, and frequency. In this thesis, we develop mathematical models and algorithms for detecting spectrum holes in a fixed frequency band, which are characterized either in space or in time.
dc.format.extent97 pages
dc.identifier.urihttps://hdl.handle.net/1920/10196
dc.language.isoen
dc.rightsCopyright 2015 Yuandao Sun
dc.subjectElectrical engineering
dc.subjectComputer engineering
dc.subjectComputer science
dc.subjectAggregate interference
dc.subjectCognitive Radio Network
dc.subjectCollaboration
dc.subjectHidden Markov Model
dc.subjectOnline parameter estimation
dc.subjectSpectrum Sensing
dc.titleSpectrum Sensing for Cognitive Radio Networks
dc.typeDissertation
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral

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