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基于信令大数据支撑用户VoLTE感知分析方法.docx

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基于信令大数据支撑用户VoLTE感知分析方法 Title:UserVoLTEPerceptionAnalysisMethodSupportedbySignalingBigData Abstract: VoiceoverLTE(VoLTE)hasbecomethemainstreamtechnologyfordeliveringhigh-qualityvoiceservicesinmodernmobilenetworks.However,ensuringasuperioruserexperienceandunderstandingthefactorsthataffectVoLTEperformanceremainsachallenge.ThispaperpresentsamethodforanalyzinguserVoLTEperceptionusingsignalingbigdata.Byleveragingthemassiveamountofsignalingdatacollectedfrommobilenetworks,thismethodprovidesinsightsintothecausesofuser-perceivedvoicequalitydegradationandhelpsoptimizenetworkperformancetoenhanceusersatisfaction.Theproposedmethodinvolvesdatacollection,preprocessing,featureextraction,andperceptionanalysis.ExperimentalresultsdemonstratetheeffectivenessandreliabilityoftheproposedmethodinidentifyingpotentialissuesaffectingVoLTEuserexperience. 1.Introduction VoiceservicesoverLTEnetworkshavegainedsignificantpopularityduetotheirhighdatarates,lowlatency,andseamlessintegrationwithotherinternet-basedservices.However,ensuringhigh-qualityvoicecallsremainsachallenge.VoLTEperceptionanalysisplaysacrucialroleinunderstandingthefactorsthataffectuserexperienceandprovidingvaluableinsightsfornetworkoptimization. 2.SignalingBigDataCollection Thefirststepintheproposedmethodinvolvescollectingandprocessingmassivesignalingdatafrommobilenetworks.Signalingdataincludesvarioustypesofmessagesexchangedbetweennetworkelementsduringcallsetup,tear-down,andhandoverprocedures.Thesedatasetsprovideacomprehensiveviewofthenetworkperformanceanduserexperience. 3.PreprocessingandDataCleaning Rawsignalingdatacollectedfromdifferentsourcesmaycontainnoise,errors,andredundancy,whichcanaffecttheaccuracyofperceptionanalysis.Preprocessingtechniques,suchasdatacleaning,filtering,andaggregation,areappliedtoremoveirrelevantorredundantinformationandensuredataquality. 4.FeatureExtraction Afterdatapreprocessing,relevantfeaturesthatreflectuserVoLTEperceptionareextracted.Theselectionoffeaturesisbasedondomainknowledgeandmayincludecallsetupt