Bayesian Compressive Sensing for Ultra-Wideband Channel Models

dc.contributor.author Ozgor, Mehmet
dc.contributor.author Erküçük, Serhat
dc.contributor.author Erküçük, Serhat
dc.contributor.author Cirpan, Hakan Ali
dc.contributor.other Electrical-Electronics Engineering
dc.date.accessioned 2019-06-27T08:04:19Z
dc.date.available 2019-06-27T08:04:19Z
dc.date.issued 2012
dc.department Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü en_US
dc.description.abstract Considering the sparse structure of ultra-wideband (UWB) channels compressive sensing (CS) is suitable for UWB channel estimation. Among various implementations of CS the inclusion of Bayesian framework has shown potential to improve signal recovery as statistical information related to signal parameters is considered. In this paper we study the channel estimation performance of Bayesian CS (BCS) for various UWB channel models and noise conditions. Specifically we investigate the effects of (i) sparse structure of standardized IEEE 802.15.4a channel models (ii) signal-to-noise ratio (SNR) regions and (iii) number of measurements on the BCS channel estimation performance and compare them to the results of l(1)-norm minimization based estimation which is widely used for sparse channel estimation. The study shows that BCS exhibits superior performance at higher SNR regions only for adequate number of measurements and sparser channel models (e. g. CM1 and CM2). Based on the results of this study BCS method or the l(1)-norm minimization method can be preferred over the other for different system implementation conditions. en_US]
dc.identifier.citationcount 6
dc.identifier.doi 10.1109/TSP.2012.6256307 en_US
dc.identifier.endpage 324
dc.identifier.isbn 9781467311182
dc.identifier.scopus 2-s2.0-84866944635 en_US
dc.identifier.startpage 320 en_US
dc.identifier.uri https://hdl.handle.net/20.500.12469/925
dc.identifier.uri https://doi.org/10.1109/TSP.2012.6256307
dc.identifier.wos WOS:000308143100061 en_US
dc.institutionauthor Erküçük, Serhat en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.journal 2012 35th International Conference on Telecommunications and Signal Processing (TSP) en_US
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.scopus.citedbyCount 6
dc.subject Bayesian compressive sensing (BCS) en_US
dc.subject Channel models en_US
dc.subject l(1)-norm minimization en_US
dc.subject Ultra-wideband (UWB) channel estimation en_US
dc.title Bayesian Compressive Sensing for Ultra-Wideband Channel Models en_US
dc.type Conference Object en_US
dc.wos.citedbyCount 6
dspace.entity.type Publication
relation.isAuthorOfPublication 440e977b-46c6-40d4-b970-99b1e357c998
relation.isAuthorOfPublication.latestForDiscovery 440e977b-46c6-40d4-b970-99b1e357c998
relation.isOrgUnitOfPublication 12b0068e-33e6-48db-b92a-a213070c3a8d
relation.isOrgUnitOfPublication.latestForDiscovery 12b0068e-33e6-48db-b92a-a213070c3a8d

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