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一种改进的基于MME的盲频谱感知算法（英文）.docx

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一种改进的基于MME的盲频谱感知算法（英文） Title:AnImprovedBlindSpectrumSensingAlgorithmBasedonMismatchedMaximumEntropyforCognitiveRadioNetworks Abstract: Withtheincreasingdemandforwirelessspectrum,cognitiveradio(CR)networkshaveemergedasapromisingsolutiontoaddressspectrumscarcity.SpectrumsensingisacriticalcomponentofCRsystems,enablingsecondaryusers(SUs)todetectandutilizetheidleorunderutilizedspectrumwithoutcausingharmfulinterferencetoprimaryusers(PUs).ThispaperproposesanimprovedblindspectrumsensingalgorithmbasedontheMismatchedMaximumEntropy(MME)approach.ThealgorithmaimstoenhancetheperformanceofspectrumsensinginCRnetworksbymitigatingtheeffectsofnoiseuncertaintyandalleviatingtheinfluenceofimperfectstatisticalknowledge. 1.Introduction Cognitiveradionetworkshavegainedattentioninrecentyearsduetotheirabilitytoimprovespectrumutilizationbyexploitingtheunderutilizedfrequencybands.However,spectrumsensingischallengingduetofactorssuchasnoiseuncertainty,fading,andimperfectknowledgeofstatisticalproperties.Inthispaper,weproposeanimprovedblindspectrumsensingalgorithmbasedontheMismatchedMaximumEntropy(MME)approachtoovercomethesechallengesandenhancetheperformanceofCRnetworks. 2.Background Thissectionprovidesanoverviewofcognitiveradionetworks,spectrumsensingtechniques,andtheMismatchedMaximumEntropy(MME)approach.Italsodiscussesthelimitationsofexistingblindspectrumsensingalgorithms. 3.SystemModel Adetailedsystemmodelispresented,describingtheprimaryandsecondaryusers'behavior,channelconditions,andnetworkassumptions.Themathematicalformulationoftheblindspectrumsensingproblemisalsoprovided. 4.ProposedAlgorithm TheproposedalgorithmcombinestheMismatchedMaximumEntropy(MME)approachwithblindspectrumsensing.Itleveragestheinherentstatisticalpropertiesofthereceivedsignalstoestimatethepowerspectraldensity(PSD)oftheprimarysignal.Thealgorithmalsotakesintoaccounttheuncertaintyinnoisepowerestimationandtheimperfectknowledgeofthestatisticalpropertiesofthereceivedsignals.ItemploysamodifiedversionoftheMMEmethodtoestimatethePSD,