Signal Detection for QPSK Based Cognitive Radio Systems using Support Vector Machines

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dc.contributor.authorMushtaq, M. Tahir
dc.contributor.authorKhan, Inayatullah
dc.contributor.authorKhan, M. S.
dc.contributor.authorKoudelka, Otto
dc.coverage.issue1cs
dc.coverage.volume24cs
dc.date.accessioned2015-05-21T12:10:00Z
dc.date.available2015-05-21T12:10:00Z
dc.date.issued2015-04cs
dc.description.abstractCognitive radio based network enables opportunistic dynamic spectrum access by sensing, adopting and utilizing the unused portion of licensed spectrum bands. Cognitive radio is intelligent enough to adapt the communication parameters of the unused licensed spectrum. Spectrum sensing is one of the most important tasks of the cognitive radio cycle. In this paper, the auto-correlation function kernel based Support Vector Machine (SVM) classifier along with Welch's Periodogram detector is successfully implemented for the detection of four QPSK (Quadrature Phase Shift Keying) based signals propagating through an AWGN (Additive White Gaussian Noise) channel. It is shown that the combination of statistical signal processing and machine learning concepts improve the spectrum sensing process and spectrum sensing is possible even at low Signal to Noise Ratio (SNR) values up to -50 dB.en
dc.formattextcs
dc.format.extent192-198cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 2015 vol. 24, č. 1, s. 192-198. ISSN 1210-2512cs
dc.identifier.doi10.13164/re.2015.0192en
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/38750
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2015/15_01_0192_0198.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectCognitive radioen
dc.subjectautocorrelation functionen
dc.subjectmachine learningen
dc.subjectSupport Vector Machineen
dc.subjectspectrum sensingen
dc.subjectstatistical signal processingen
dc.subjectopportunistic dynamic spectrum accessen
dc.titleSignal Detection for QPSK Based Cognitive Radio Systems using Support Vector Machinesen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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