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一种用于数字音频广播的自干扰抵消方法
Title:Self-InterferenceCancellationTechniquesforDigitalAudioBroadcasting
Abstract:
Withtherapiddevelopmentofdigitalaudiobroadcasting,theissueofself-interferencehasbecomeamajorconcern.Self-interferencecansignificantlydegradethequalityofaudiosignals,leadingtounacceptableuserexperience.Thispaperpresentsanin-depthanalysisofself-interferenceindigitalaudiobroadcastingandexploresvarioustechniquesforitscancellation.Thesetechniquesholdthepotentialtoenhancetheoverallaudioqualityandimprovetheperformanceofdigitalaudiobroadcastingsystems.
1.Introduction
Digitalaudiobroadcastinghasgainedimmensepopularityduetoitsabilitytodeliverhigh-qualityaudiosignalsoverlongdistances.However,self-interferenceisanotablechallengeindigitalaudiobroadcastingsystems.Self-interferenceoccurswhenthetransmittedsignalleaksintothereceiver'spath,causingdistortionandnoise.Thispaperaimstoproposeeffectiveself-interferencecancellationmethodstomitigatetheproblem.
2.Self-InterferenceinDigitalAudioBroadcasting
Tocomprehendthecomplexitiesofself-interference,itiscrucialtounderstandtheunderlyingcausesandeffects.Self-interferencecanoccurduetovariousfactors:transmitterleakage,multipathpropagation,receivernonlinearities,neighboringchannelinterference,andspuriousemissions.Thesefactorscandistortthereceivedaudiosignal,resultingindiminishedaudioqualityandincreasednoise.
3.State-of-the-ArtTechniquesforSelf-InterferenceCancellation
Thissectionpresentsacomprehensiveoverviewoftheexistingtechniquesforself-interferencecancellationindigitalaudiobroadcasting.
3.1.AdaptiveFilteringTechniques
Adaptivefilteringtechniquesutilizealgorithmstoestimateandcanceltheself-interferencesignal.Thesealgorithmsadaptivelyupdatethefiltercoefficientstominimizetheresidualself-interference.Widelyusedadaptivefilteringalgorithmsincludeleastmeansquares(LMS),normalizedLMS,andrecursiveleastsquares(RLS).Theeffectivenessofeachalgorithmcandependonthespecificcharacteristicsoftheself-interference.
3.2.DigitalPredistortion
Digitalpredistortionmod