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dc.contributor.authorPourgharehkhan, Z.
dc.contributor.authorSedighi, S.
dc.contributor.authorTaherpour, A.
dc.contributor.authorUysal, Murat
dc.date.accessioned2016-02-16T10:25:57Z
dc.date.available2016-02-16T10:25:57Z
dc.date.issued2012
dc.identifier.isbn978-1-4673-0436-8
dc.identifier.issn1525-3511
dc.identifier.urihttp://hdl.handle.net/10679/2506
dc.identifier.urihttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6213922&tag=1
dc.descriptionDue to copyright restrictions, the access to the full text of this article is only available via subscription.
dc.description.abstractIn this paper, we consider the problem of wideband spectrum sensing by using the correlation among the observation samples in different subbands. The Primary User (PU) signal samples in occupied subbands are assumed to be zero-mean correlated Gaussian random variables and additive noise is modeled as colored zero-mean Gaussian random variables independent of the PU signal. It is also assumed that there is at least a minimum given number of subbands that are vacant of PU signals. First we derive the optimal detector and the Generalized Likelihood Ratio (GLR) detector for the case that the covariance matrix of PUs signal samples is unknown and the noise variance in the different subbands is known. Then, we propose an iterative algorithm for GLR test when both the covariance matrix of the PUs signal samples and the noise variances in the different subbands, are unknown. For analytical performance evaluation, we derive some closed-form expressions for detection and false alarm probabilities of the proposed detectors in low Signal to Noise Ratio (SNR) regime. The simulation results are further presented to compare the performance of the proposed detectors.
dc.description.sponsorshipTÜBA
dc.language.isoengen_US
dc.publisherIEEE
dc.relation.ispartofWireless Communications and Networking Conference (WCNC), 2012 IEEE
dc.rightsrestrictedAccess
dc.titleSpectrum sensing of correlated subbands with colored noise in cognitive radiosen_US
dc.typeConference paperen_US
dc.peerreviewedyes
dc.publicationstatuspublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID124615
dc.contributor.ozuauthorUysal, Murat
dc.identifier.startpage1017
dc.identifier.endpage1022
dc.identifier.wosWOS:000324580701021
dc.identifier.doi10.1109/WCNC.2012.6213922
dc.subject.keywordsGaussian processes
dc.subject.keywordsCognitive radio
dc.subject.keywordsCovariance matrices
dc.subject.keywordsSignal detection
dc.subject.keywordsSignal sampling
dc.identifier.scopusSCOPUS:2-s2.0-84864329009


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