An online adaptive cooperation scheme for spectrum sensing based on a second-order statistical method

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dc.contributor.authorYarkan, Serkan
dc.contributor.authorTöreyin, Behçet Uğur
dc.contributor.authorQaraqe, Khalid A.
dc.contributor.authorÇetin, A. Enis
dc.date.accessioned2020-11-21T15:53:14Z
dc.date.available2020-11-21T15:53:14Z
dc.date.issued2012en_US
dc.departmentİstanbul Ticaret Üniversitesien_US
dc.description.abstractSpectrum sensing is one of the most important features of cognitive radio (CR) systems. Although spectrum sensing can be performed by a single CR, it is shown in the literature that cooperative techniques, including multiple CRs/sensors, improve the performance and reliability of spectrum sensing. Existing cooperation techniques usually assume a static communication scenario between the unknown source and sensors along with a fixed propagation environment class. In this paper, an online adaptive cooperation scheme is proposed for spectrum sensing to maintain the level of sensing reliability and performance under changing channel and environmental conditions. Each cooperating sensor analyzes second-order statistics of the received signal, which undergoes both correlated fast and slow fading. Autocorrelation estimation data from sensors are fused together by an adaptive weighted linear combination at the fusion center. Weight update operation is performed online through the use of orthogonal projection onto convex sets. Numerical results show that the performance of the proposed scheme is maintained for dynamically changing characteristics of the channel between an unknown source and sensors, even under different physical propagation environments. In addition, it is shown that the proposed cooperative scheme, which is based on second-order detectors, yields better results compared with the same fusion mechanism that is based on conventional energy detectors. © 2012 IEEE.en_US
dc.description.sponsorshipQatar National Research Fund NPRP -- Manuscript received April 27, 2011; revised September 27, 2011; accepted November 11, 2011. Date of publication December 9, 2011; date of current version February 21, 2012. This work was supported by Qatar National Research Fund (QNRF) Grant through National Priority Research Program (NPRP) 08-101-2-025. QNRF is an initiative of the Qatar Foundation. The review of this paper was coordinated by Prof. O. B. Akan. -- --en_US
dc.identifier.doi10.1109/TVT.2011.2179325en_US
dc.identifier.endpage686en_US
dc.identifier.issn0018-9545
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-84857265505en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage675en_US
dc.identifier.urihttps://doi.org/10.1109/TVT.2011.2179325
dc.identifier.urihttps://hdl.handle.net/11467/3507
dc.identifier.volume61en_US
dc.identifier.wosWOS:000300427400022en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofIEEE Transactions on Vehicular Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAdaptive data fusion (ADF)en_US
dc.subjectFast fadingen_US
dc.subjectMobilityen_US
dc.subjectOnline learningen_US
dc.subjectProjection onto convex sets (POCS)en_US
dc.subjectShadowingen_US
dc.subjectSpectrum sensingen_US
dc.titleAn online adaptive cooperation scheme for spectrum sensing based on a second-order statistical methoden_US
dc.typeArticleen_US

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