Achievable Performance of Bayesian Compressive Sensing Based Spectrum Sensing

dc.contributor.author Başaran, Mehmet
dc.contributor.author Erküçük, Serhat
dc.contributor.author Erküçük, Serhat
dc.contributor.author Çırpan, Hakan Ali
dc.contributor.other Electrical-Electronics Engineering
dc.date.accessioned 2019-06-27T08:03:15Z
dc.date.available 2019-06-27T08:03:15Z
dc.date.issued 2014
dc.department Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü en_US
dc.description.abstract In wideband spectrum sensing compressive sensing approaches have been used at the receiver side to decrease the sampling rate if the wideband signal can be represented as sparse in a given domain. While most studies consider the reconstruction of primary user's signal accurately it is indeed more important to analyze the presence or absence of the signal correctly. Furthermore these studies do not consider the achievable lower bounds of reconstruction error and how well the selected method performs correspondingly. Motivated by these issues we investigate in detail the primary user detection performance of Bayesian compressive sensing (BCS) approach in this paper. Accordingly we (i) determine the BCS signal reconstruction performance in terms of mean-square error (MSE) compression ratio and signal-to-noise ratio (SNR) and compare it with the conventionally used basis pursuit approach (ii) determine how well BCS performs compared with the Bayesian Cramer-Rao lower bound (BCRLB) of the signal reconstruction error and (iii) assess the probability of detection performance of BCS for various SNR and compression ratio values. The results of this study are important for determining the achievable performance of BCS based spectrum sensing. en_US]
dc.identifier.citationcount 6
dc.identifier.doi 10.1109/ICUWB.2014.6958956 en_US
dc.identifier.endpage 90
dc.identifier.isbn 978-1-4799-5396-7
dc.identifier.issn 2167-9967 en_US
dc.identifier.issn 2167-9967
dc.identifier.scopus 2-s2.0-84912125441 en_US
dc.identifier.startpage 86 en_US
dc.identifier.uri https://hdl.handle.net/20.500.12469/761
dc.identifier.uri https://doi.org/10.1109/ICUWB.2014.6958956
dc.identifier.wos WOS:000411477000016 en_US
dc.institutionauthor Erküçük, Serhat en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.journal IEEE International Conference on Ultra-WideBand (ICUWB) 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 7
dc.subject Cognitive radios en_US
dc.subject Ultra wideband (UWB) systems en_US
dc.subject Energy efficiency en_US
dc.subject Bayesian compressive sensing en_US
dc.subject Spectrum sensing en_US
dc.subject Probability of detection en_US
dc.title Achievable Performance of Bayesian Compressive Sensing Based Spectrum Sensing 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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