一种基于4G AoA的5G天线方位角调优方法-豆柴文库

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一种基于4GAoA的5G天线方位角调优方法
Title:AMethodfor5GAntennaAzimuthOptimizationbasedon4GAoA
Abstract:
Withtherapiddevelopmentof5Gcommunicationsystems,optimizingantennacharacteristicshasbecomecrucialforensuringenhancednetworkperformance.Inthispaper,weproposeanovelmethodforoptimizingtheazimuthangleof5GantennasusingAngleofArrival(AoA)datafrom4Gnetworks.Theproposedmethodleveragestheadvancementsin4Gtechnologytoimprovetheantennadeploymentandperformancein5Gnetworks.Themethodologyincludesathree-stepprocess:datacollection,preprocessing,andoptimization.Simulationresultsdemonstratetheeffectivenessandefficiencyoftheproposedmethodinimprovingtheantennaazimuthanglefor5Gcommunicationsystems.
1.Introduction:
Asthedemandforhigherdataratesandimprovednetworkcoveragecontinuestogrow,theoptimizationofantennacharacteristicsplaysavitalrolein5Gnetworkdeployment.Traditionally,theantennaoptimizationprocessreliedonsitesurveysandmeasurements.However,theseapproachesaretime-consumingandrequireconsiderableresources.Toaddressthesechallenges,weproposeleveragingtheAoAinformationfrom4Gnetworkstooptimizetheazimuthangleof5Gantennas.
2.Methodology:
2.1DataCollection:
ThefirststepintheproposedmethodinvolvescollectingAoAdatafrom4Gnetworks.Thisdatacanbeobtainedfromtheexisting4GbasestationsbymeasuringtheAoAofdownlinksignalsreceivedbyuserdevices.Thecollecteddatasetshouldincludeadiverserangeofenvironmentsandscenariostoensurecomprehensiveoptimization.
2.2DataPreprocessing:
AftercollectingtheAoAdata,preprocessingtechniquesareemployedtoremoveoutliers,correctnoise,andfilterirrelevantinformation.Thisstepiscrucialforensuringtheaccuracyofthesubsequentoptimizationprocess.Varioussignalprocessingalgorithms,suchasKalmanfiltersandoutlierdetectionmethods,canbeutilizedtoenhancethequalityofthedata.
2.3Optimization:
Thefinalstepintheproposedmethodinvolvesoptimizingtheantennaazimuthanglefor5GnetworksusingthepreprocessedAoAdata.Severaloptimizationalgorithmscanbeemployed,suchasgeneticalgorithms,particleswarmoptimization,ormachinelearningtechn