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

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buir.contributor.authorÇetin, A. Enis
buir.contributor.orcidÇetin, A. Enis|0000-0002-3449-1958
dc.citation.epage686en_US
dc.citation.issueNumber2en_US
dc.citation.spage675en_US
dc.citation.volumeNumber61en_US
dc.contributor.authorYarkan S.en_US
dc.contributor.authorTöreyin, B. U.en_US
dc.contributor.authorQaraqe, K. A.en_US
dc.contributor.authorÇetin, A. Enisen_US
dc.date.accessioned2016-02-08T09:48:34Z
dc.date.available2016-02-08T09:48:34Z
dc.date.issued2012en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_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.en_US
dc.identifier.doi10.1109/TVT.2011.2179325en_US
dc.identifier.issn0018-9545
dc.identifier.urihttp://hdl.handle.net/11693/21596
dc.language.isoEnglishen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/TVT.2011.2179325en_US
dc.source.titleIEEE Transactions on Vehicular Technologyen_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.subjectAdaptive data fusionen_US
dc.subjectFast fadingen_US
dc.subjectOnline learningen_US
dc.subjectProjection onto convex setsen_US
dc.subjectShadowingen_US
dc.subjectSpectrum sensingen_US
dc.subjectCarrier mobilityen_US
dc.subjectData fusionen_US
dc.subjectSensorsen_US
dc.subjectOnline systemsen_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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