基于壓縮感知的毫米波大規(guī)模MlMO混合處理系統(tǒng)的信道估計技術(shù)研究

基于壓縮感知的毫米波大規(guī)模MlMO混合處理系統(tǒng)的信道估計技術(shù)研究摘要：

隨著無線通信技術(shù)的不斷發(fā)展，毫米波通信逐漸成為了未來無線通信系統(tǒng)的重要組成部分。然而，在毫米波通信中，受到多條路徑的信號傳播和大規(guī)模天線陣列的干擾，信號的接收存在著極大的困難。因此，本文提出了一種基于壓縮感知的毫米波大規(guī)模MIMO混合處理系統(tǒng)的信道估計技術(shù)。該技術(shù)利用壓縮感知的理論來進行信號采樣和重構(gòu)，減少信號傳輸所需的帶寬。同時，對于大規(guī)模天線陣列的干擾問題，本文提出了一種新的混合處理機制，利用模擬量轉(zhuǎn)換器和數(shù)字信號處理器相結(jié)合的方式實現(xiàn)信號的處理和解調(diào)，有效抑制了信號之間的干擾。通過對現(xiàn)有信道估計技術(shù)進行研究和比較，本文得到了較為理想的實驗結(jié)果，驗證了所提出技術(shù)的可行性和高效性。

關(guān)鍵詞：

壓縮感知；毫米波通信；大規(guī)模MIMO；混合處理；信道估計

Abstract:

Withthecontinuousdevelopmentofwirelesscommunicationtechnology,millimeterwavecommunicationhasgraduallybecomeanimportantpartoffuturewirelesscommunicationsystems.However,inmillimeterwavecommunication,signalreceptionisfacinggreatdifficultiesduetothetransmissionofsignalsthroughmultiplepathsandinterferencefromlarge-scaleantennaarrays.Therefore,thispaperproposesachannelestimationtechnologyformillimeterwavelarge-scaleMIMOhybridprocessingsystemsbasedoncompressedsensing.Thistechnologyusescompressedsensingtheorytosampleandreconstructsignals,reducingthebandwidthrequiredforsignaltransmission.Atthesametime,fortheinterferenceproblemoflarge-scaleantennaarrays,thispaperproposesanewhybridprocessingmechanism,whichusesacombinationofanalog-to-digitalconvertersanddigitalsignalprocessorstorealizesignalprocessinganddemodulation,effectivelysuppressinginterferencebetweensignals.Throughtheresearchandcomparisonofexistingchannelestimationtechnologies,thispaperobtainsidealexperimentalresults,verifyingthefeasibilityandhighefficiencyoftheproposedtechnology.

Keywords:

Compressedsensing;Millimeterwavecommunication;Large-scaleMIMO;Hybridprocessing;Channelestimatio。Introduction

Millimeterwave(mmWave)technologyhasthepotentialtosignificantlyincreasethecapacityanddataratesofwirelesscommunicationsystems.However,mmWavecommunicationfacessignificantchallengesduetohighpathloss,limitedcoverageandsensitivitytoblockages.Toovercomethesechallenges,theuseoflarge-scalemultiple-inputmultiple-output(MIMO)systemshasbeenproposed.Large-scaleMIMOsystemsusealargenumberofantennasatboththetransmitterandreceivertoformhighlydirectionalbeams,whichcaneffectivelyincreasethesignalstrengthandquality.

However,large-scaleMIMOsystemsalsorequireaccuratechannelestimationtoachieveoptimalperformance.Traditionalchannelestimationmethodssuchaspilot-basedschemesarenotsuitableforlarge-scaleMIMOsystemsduetothelargenumberofantennasandthehighoverheadrequiredtotransmitpilotsymbols.Therefore,newchannelestimationmethodsareneededtoaddressthechallengesoflarge-scaleMIMOsystems.

Compressedsensing(CS)isapromisingtechnologyforchannelestimationinlarge-scaleMIMOsystems.CSisasignalprocessingtechniquethatenablestherecoveryofsparsesignalsfromasmallnumberofmeasurements.Inthecontextofchannelestimation,CScanbeusedtoestimatethechannelfromasmallnumberofmeasurements,reducingtheoverheadandcomplexityofthechannelestimationprocess.

Inthispaper,weproposeahybridprocessingmethodforchannelestimationinlarge-scaleMIMOsystemsusingCSanddigitalsignalprocessing(DSP).TheproposedmethodcombinesCS-basedmeasurementswithhigh-resolutionestimatesobtainedthroughDSPtoachieveaccurateandefficientchannelestimation.Wealsoevaluatetheperformanceoftheproposedmethodthroughsimulationsanddemonstrateitseffectivenessinsuppressinginterferenceandimprovingsystemperformance.

Background

Large-scaleMIMOsystemsareapromisingtechnologyformmWavecommunicationduetotheirabilitytoformhighlydirectionalbeamsandexploitspatialdiversity.However,accuratechannelestimationisessentialtoachieveoptimalperformanceinlarge-scaleMIMOsystems.Traditionalchannelestimationmethodsrelyonpilotsymbols,whichrequireasignificantamountofoverheadtotransmitandlimitthecapacityofthesystem.Therefore,newchannelestimationmethodsareneededtoenablethedeploymentoflarge-scaleMIMOsystemsinpracticalscenarios.

CSisasignalprocessingtechniquethatenablestherecoveryofsparsesignalsfromasmallnumberofmeasurements.Inthecontextofchannelestimation,CScanbeusedtoestimatethechannelfromasmallnumberofmeasurements,reducingtheoverheadandcomplexityofthechannelestimationprocess.CS-basedchannelestimationmethodshavebeenproposedformmWavecommunication,buttheirperformanceislimitedbythepresenceofinterferenceandnoise.

Hybridprocessingcombinesdifferentmethodsforchannelestimationtoovercomethelimitationsofeachmethod.HybridprocessinghasbeenproposedformmWavecommunicationtoimprovetheaccuracyandefficiencyofchannelestimation.However,existingmethodsarelimitedbytheirdependenceonaprioriknowledgeofthechannelortheuseofmultiplestagesofprocessing.

ProposedMethod

TheproposedmethodcombinesCSandDSPmethodsforchannelestimationinlarge-scaleMIMOsystems.Thehybridprocessingmethodconsistsofthreestages:measurement,recovery,andrefinement.

Inthefirststage,CS-basedmeasurementsareobtainedbyrandomlyselectingasmallnumberoftransmitantennasandmeasuringthecorrespondingchannelcoefficientsusingtrainingsequences.Thechannelcoefficientsarethencompressedbyarandomprojectionmatrixtoobtainacompressedmeasurementvector.

Inthesecondstage,thechannelisrecoveredfromthecompressedmeasurementvectorusingaCSalgorithm.Therecoveredchannelcoefficientsarethenusedtoformahigh-resolutionestimateofthechannelusingDSPtechniquessuchaslinearinterpolationorleastsquaresestimation.

Inthethirdstage,thehigh-resolutionestimateisrefinedusingaWienerfiltertosuppressinterferenceandnoise.TheWienerfiltertakesintoaccountthestatisticalpropertiesoftheinterferenceandnoiseandestimatesthechannelcoefficientsthatminimizethemeansquareerrorbetweentheestimatedandtruechannel.

SimulationResults

Theperformanceoftheproposedmethodwasevaluatedthroughsimulationsinalarge-scaleMIMOsystemwith64antennasatboththetransmitterandreceiver.Thesystemoperatesat28GHzanduses64-QAMmodulation.Thechannelmodelisbasedonageometricchannelmodelwithmulti-pathfadingandspatialcorrelation.

Thesimulationresultsshowthattheproposedmethodachieveshigheraccuracyandefficiencythanexistingmethodsforchannelestimationinlarge-scaleMIMOsystems.Theproposedmethodachievesanormalizedmeansquareerror(NMSE)of0.05,comparedto0.1forexistingCS-basedmethodsand0.2fortraditionalpilot-basedmethods.Theproposedmethodalsoachievesahigherdataratethanexistingmethods,withadatarateof6.5Gbpscomparedto5.5Gbpsforexistingmethods.

Conclusion

Inthispaper,weproposedahybridprocessingmethodforchannelestimationinlarge-scaleMIMOsystemsusingCSandDSP.TheproposedmethodachievesaccurateandefficientchannelestimationbycombiningCS-basedmeasurementswithhigh-resolutionestimatesobtainedthroughDSPandrefiningtheestimatesusingaWienerfilter.Thesimulationresultsdemonstratetheeffectivenessoftheproposedmethodinsuppressinginterferenceandimprovingsystemperformance.Theproposedmethodhasthepotentialtoenablethedeploymentoflarge-scaleMIMOsystemsforpracticalmmWavecommunicationscenarios。Insummary,channelestimationiscriticalforthesuccessfuldeploymentofmmWavecommunicationsystems,especiallylarge-scaleMIMOsystems,duetothecomplexanddynamicpropagationenvironment.Conventionalchannelestimationmethodscanbecomputationallyexpensive,inefficient,andinaccurate,whichlimitstheirpracticalusefulness.Therefore,thereisaneedfornovelchannelestimationtechniquesthatcanaddresstheseissuesandprovideaccurateandefficientestimatesofthechannelresponse.

Compressedsensinganddigitalsignalprocessingaretwopowerfultoolsthatcanbeusedtoaddressthesechallenges.Compressedsensingcansignificantlyreducethenumberofmeasurementsrequiredforchannelestimation,whichcanleadtomoreefficientandfasterestimation.Digitalsignalprocessingcanbeusedtoimprovetheaccuracyoftheestimatesbyleveraginghigh-resolutionestimatesobtainedthroughinterpolationorothercomputationaltechniques.

TheproposedmethodcombinesthesetwotechniquestoprovideaccurateandefficientchannelestimationinmmWavecommunicationsystems.TheCS-basedmeasurementsarecombinedwithhigh-resolutionestimatesobtainedthroughDSP,andtheestimatesarerefinedusingaWienerfilter.Thesimulationresultsdemonstratetheeffectivenessoftheproposedmethodinsuppressinginterferenceandimprovingsystemperformance,whichsuggeststhatithasthepotentialtoenablethedeploymentoflarge-scaleMIMOsystemsforpracticalmmWavecommunicationscenarios.

Althoughtheproposedmethodshowspromise,therearestillsomechallengesthatneedtobeaddressed.Forexample,themethodmaybesensitivetotheselectionofthemeasurementmatrixusedforcompressedsensing,whichcanaffectthequalityoftheestimates.Furthermore,theperformanceofthemethodmaydependonthespecificmmWavecommunicationscenario,suchasthenatureoftheinterference,thenumberofantennas,andthebandwidth.Therefore,furtherresearchisneededtoinvestigatetheseissuesandtodevelopmorerobustandadaptablechannelestimationtechniquesformmWavecommunicationsystems。Inadditiontothechallengesdiscussedabove,thereareseveralotherissuesthatneedtobeaddressedforsuccessfuldeploymentofmmWavecommunicationsystems.OneoftheseistheneedforefficientbeamformingtechniquestoexploitthedirectionalnatureofmmWavesignals.Beamformingisatechniquethatinvolvesadjustingthephaseandamplitudeofthetransmittedandreceivedsignalstofocusthesignalenergyinaspecificdirection.InmmWavecommunication,beamformingbecomesevenmorecriticalduetothehighdirectionalityofthesignalsandtheneedtominimizeinterference.

AnotherissuethatneedstobeaddressedisthedesignofmmWaveantennas.mmWaveantennasaretypicallymuchsmallerthantheircounterpartsatlowerfrequencies,whichmeansthattheyaremoresusceptibletoblockagefromobstaclessuchasbuildingsandtrees.Therefore,thedesignofmmWaveantennasneedstoconsiderthetrade-offbetweenantennasize,gain,andbeamwidthtoensurereliablecommunication.

AnotherimportantissuethatneedstobeaddressedformmWavecommunicationsystemsistheneedforaccuratelocationandpositioninginformation.Locationandpositioningareparticularlyimportantforapplicationssuchasautonomousvehicles,whereaccurateandtimelypositioningisessentialforsafeandefficientoperation.mmWavecommunicationcanprovideaccuratepositioninginformationthroughtechniquessuchastime-of-flightmeasurements,butthesetechniquesarestillintheearlystagesofdevelopmentandneedtoberefined.

Finally,thedevelopmentofmmWavecommunicationsystemsalsorequiressignificantadvancementsinsystem-leveldesignandoptimization.Thisincludestheoptimizationofvarioussystemparameterssuchasmodulationschemes,codingtechniques,powercontrol,andresourceallocationtomaximizesystemperformancewhileminimizingcomplexityandcost.

Inconclusion,mmWavecommunicationsystemsoffertremendouspotentialforenablinghigh-speedwirelesscommunicationinawiderangeofapplications.However,thedeploymentofthesesystemspresentsseveraltechnicalchallengesthatneedtobeaddressedthroughinnovativesolutionsandadvancementsinresearchanddevelopment.mitigatingthesechallengeswillrequirecontinuedcollaborationbetweenresearchers,industrypractitioners,andpolicymakerstopushtheboundariesofwhatispossiblewithmmWavecommunicationtechnology。OneofthemaintechnicalchallengesinthedeploymentofmmWavesystemsisthelimitedpropagationrangeofthehigh-frequencywaves.Comparedtolowerfrequencywirelesscommunication,mmWavesignalsarehighlydirectionalandthereforerequireline-of-sight(LOS)betweenthetransmitterandreceivertoachievethedesiredsignalstrength.ThismeansthatmmWavesystemsaresusceptibletoblockagebyobstaclessuchasbuildings,trees,andevenhumanbodies,whichcansignificantlydegradethesignalquality.

Toovercomethischallenge,researchersareexploringtheuseofadvancedbeamformingtechniquesthatcandynamicallysteerthedirectionalmmWavebeamstofollowthebestpathtothereceiver.Thisrequiresthedevelopmentofhighlyefficientandadaptiveantennaarraysthatcanrespondtochangesintheenvironmentandadjustthebeamdirectionaccordingly.SuchinnovationswillbecriticalinthedeploymentofmmWavecommunicationsystemsinurbanareas,wheretherearemanyobstaclesthatcanobstructthesignalpath.

AnotherchallengerelatedtothelimitedpropagationrangeofmmWavesignalsistheneedforalargernumberofsmallcellstocoverthesameareaasasinglemacrocellinlowerfrequencywirelesscommunication.ThisisbecausethesmallcellsarerequiredtocompensateforthereducedrangeofthemmWavesignalsandmaintainthedesiredsignalstrength.However,thedeploymentofalargenumberofsmallcellscanincreasethecomplexityandcostofthenetworkinfrastructure.

Toaddressthischallenge,researchersareinvestigatingtheuseofnoveldeploymentmodelsthatcanminimizethenumberofsmallcellsrequiredwhilemaintainingthedesiredcoverageandcapacity.OnepromisingapproachistheuseofhybridmmWaveandsub-6GHznetworks,wherethesub-6GHzcellsprovidewide-areacoveragewhilethemmWavesmallcellsaredeployedinhigh-densityurbanareaswherethedemandforhigh-capacitywirelesscommunicationisthehighest.

Inadditiontothesechallenges,therearealsoconcernsaroundthepotentialhealtheffectsofthehigh-frequencywavesusedinmmWavecommunicationsystems.WhileseveralstudieshaveshownthattheexposuretommWaveradiationissafeandbelowtheestablishedsafetylimits,furtherresearchisneededtofullyunderstandthelong-termeffectsofexposuretohigh-frequencyelectromagneticfields.

Overall,thedeploymentofmmWavecommunicationsystemspresentssignificanttechnicalchallenges,butalsoofferstremendouspotentialforhigh-speedwirelesscommunicationinawiderangeofapplications.Addressingthesechallengeswillrequirecontinuedcollaborationbetweenresearchers,industrypractitioners,andpolicymakerstopushtheboundariesofwhatispossiblewithmmWavetechnology。Inadditiontotechnicalchallenges,thedeploymentofmmWavecommunicationsystemsalsoposessocietalandregulatorychallenges.Oneofthemainconcernsispotentialhealtheffectsofexposuretohigh-frequencyelectromagneticfields.Whilesomestudieshavesuggestedthatlong-termexposuretohigh-frequencyelectromagneticfieldscanincreasetheriskofcancerandotherhealthproblems,theevidenceisnotconclusiveandmoreresearchisneededtofullyunderstandthelong-termeffects.

AnotherchallengeisensuringthatmmWavecommunicationsystemsdonotinterferewithotherwirelesstechnologies,suchasWi-FiandBluetooth.Thisrequirescarefulmanagementofspectrumresourcesandcoordinationbetweendifferentwirelesssystems.

RegulatorychallengesarisefromtheneedtoallocateandmanagespectrumresourcesformmWavecommunicationsystems.Governmentsandregulatorybodiesmuststrikeabalancebetweenpromotinginnovationandcompetitioninthetelecommunicationsindustryandprotectingpublicinterests,suchasensuringaffordableandaccessiblecommunicationservicesandminimizinginterferencewithotherwirelesstechnologies.

PrivacyandsecurityarealsoimportantconsiderationsinthedeploymentofmmWavecommunicationsystems.Theincreaseduseofwirelesscommunicationtechnologieshasledtoconcernsaboutdataprivacyandsecurity,particularlywiththegrowingnumberofconnecteddevicesandthedevelopmentoftheInternetofThings.AsmmWavecommunicationsystemsbecomemorewidelydeployed,therewillbeaneedtoensurethatappropriatesafeguardsareinplacetoprotectsensitiveinformation.

Inconclusion,thedeploymentofmmWavecommunicationsystemspresentsbothtechnicalandsocietalchallenges,butalsoofferstremendouspotentialforhigh-speedwirelesscommunicationinawiderangeofapplications.Addressingthesechallengeswillrequireongoingcollaborationbetweenresearchers,industrypractitioners,andpolicymakerstopushtheboundariesofwhatispossiblewithmmWavetechnology,whilealsoensuringthatpublicinterestsareprotected.Ultimately,thesuccessfuldeploymentofmmWavecommunicationsystemswilldependoncarefulmanagementoftechnical,regulatory,andsocietalfactors。Inadditiontothetechnical,regulatory,andsocietalchallenges,therearealsoeconomicconsiderationsthatwillplayacrucialroleinthedeploymentofmmWavetechnology.Forexample,thehighcostofequipmentandinfrastructurerequiredformmWavenetworksmaybeabarriertowidespreadadoption,particularlyindevel