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1、240IEEETRANSACTIONSONSIGNALPROCESSING,VOL.52,NO.1,JANUARY2004ChannelEstimationUsingImplicitTrainingAldoG.Orozco-Lugo,Member,IEEE,M.MauricioLara,Member,IEEE,andDesC.McLernon,Member,IEEEAbstract—Inthispaper,anewmethodtoperformchanneles-channelestimation.Thenotionof“implici
2、ttraining”isusedintimationispresented.Itisshownthataccurateestimationcanbethepapertitletodistinguishtheproposedmethod(wheretheobtainedwhenatrainingsequenceisactuallyarithmeticallyaddedtrainingsequenceisactuallyarithmeticallyaddedtotheinfor-totheinformationdataasopposedto
3、beingplacedinaseparatemationdata)fromonewherethetrainingsequenceisallocatedemptytimeslot:hence,theword“implicit.”Aclosed-formsolutionfortheestimationvarianceisderived,aswellastheCramér–Raoanemptytimeslotthatisseparatefromtheinformationdatalowerbound.Conditionsarederivedf
4、orthetrainingsequences(asinGSM).Thisway,nobandwidthislostinsendingtrainingthatresultinachannelestimationperformancethatisindepen-data,andsincethe“trainingsequence”cannotbeseenexplic-dentofthechannelcharacteristics.Inaddition,estimationperfor-itlyinthetransmittedsignal,ch
5、annelestimationmustbecar-manceisshowntobeindependentofthemodulationformat.Apro-riedoutusingstatisticalinformation.Thecruxofthematteris,ceduretosynthesizeoptimaltrainingsequencesispresented,andtheproblemofsynchronizationissolved.Theperformanceofthehowever,ifthetrainingseq
6、uenceisperiodic,thenthereceivedalgorithmisthencomparedwithothermethodsthatuseexplicitdatawillexhibitcyclostationarystatistics(specifically,aperi-trainingunderGSM-likeenvironmentalconditions,andthenewodicallytime-varyingmean)thatcanbeexploitedtoperformalgorithmisshowntobe
7、competitivewiththese.Finally,compar-accuratechannelestimation.isonsarealsocarriedoutagainstblindmethodsoverrealisticban-Whilewritingthispaper(motivatedbyourearlierpublisheddlimitedchannels,andtheseshowthatthenewmethodexhibitsgoodperformance.results[4]–[6]),webecameawareo
8、ftheworkin[7]andthere-centlypublishedworksin[8]and[9],whichproposeasimilarIndexTerms—Channelestimation,
