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基于Kalman滤波的WCDMA上行链路衰落信道跟踪 Introduction Inwirelesscommunication,signalpropagationisaffectedbyvariousfadingconditions.Fadingconditionsrefertothelossofsignalpowerandsignaldistortionthatoccurwhenaradiosignalpropagatesthroughthecommunicationchannel.Thefadingconditionisamajorreasonforsignaldistortioninwirelesscommunication,whicheventuallyleadstoadecreaseinthequalityofservicethattheuserexperiences.Fadingsignalscanbeclassifiedintotwotypes,namelymultipathfadingandshadowfading.Inthispaper,wefocusonthemultipathfadingcondition,whichcausesfluctuationsinsignalstrengthovertimeanddelayspread. KalmanFilter Kalmanfilterisawidelyusedtoolforestimationandpredictioninuncertainandtime-varyingsystems.Thisfilterisamathematicalmodelthatusesaseriesofmeasurementsobservedovertimetoestimateunknownvariables.TheprimaryobjectiveoftheKalmanfilteristoremovenoisefromthemeasurementdataandprovideamoreaccurateestimateofthesystemstate.Itisarecursivefilterthatupdatestheestimateeachtimeanewmeasurementisreceived. WCDMAUplinkChannel TheWCDMA(WidebandCodeDivisionMultipleAccess)isacommunicationstandardusedin3Gwirelesscommunicationsystems.TheuplinkchannelinWCDMAissubjecttomultipathfading,whichaffectsthequalityofthereceivedsignalatthebasestation.Theuplinkchannelhasatime-varyingnature,whichmeansthatthetransmittedsignalexperiencesdifferentdelaysandphasesduetothereflectionsfromnearbyobstacles.Toovercometheeffectsofmultipathfading,channelestimationisnecessarytoadaptthemodulationandcodingschemesaccordingtothechannelstate.TheestimationoftheuplinkchannelisakeyproblemthatneedstobeaddressedinWCDMAsystems. KalmanFilter-basedChannelEstimation TheKalmanfilterhasbeenwidelyusedforchannelestimationinwirelesscommunicationsystems.TheKalmanfilter-basedchannelestimationmethodisbasedontheassumptionthatthechannelisalinearandtime-varyingsystem.Thefilterconsidersthecurrentstateofthechannelandthepreviousstatetoestimatethecurrentstateofthechannel.Theprocessofchannelestimationinvolvestwomainsteps,namelypredictionandupdate. Prediction The