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ID:46263613
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页数:4页
时间:2019-11-22
《CPSO在配电网OFDM系统比特功率分配中的应用》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、ComputerEngineeringandAppli(’ations计算机工程与应用201I,47(21)239CPSO在西已电网OFDM系统比特功率分配中的应用张锐“2,刘世辉2ZHANGRup2,LIUShihui21.哈尔滨INk大学电气J:程及自动化学院,哈尔滨1500102.哈尔滨理I:大学自动化学院。哈尔滨1500801.SchoolofElectricalEngineering&Automation,HarbinInstituteofTechnology,Harbin150010.China2.SchoolofAutomation,
2、HarbinUniversityofScienceandTechnology,Harbin150080,ChinaZHANGRui.LIUShihui.ApplicationofCPSOinbitandpowerallocationforOFDMsystemoverdistributionnet-work.ComputerEngineeringandApplications。2011.47(21):239—242.Abstract:BitandpowerallocationinadaptiveOrthogonaiFrequencyDivisionM
3、ultiplexing(OFDM)systemsisacrucialtechniquetoimprovespectralefficiency.Bitandpowerallocationbasedonwater-fillingalgorithmcanobtainoptimalsolutionintheory.Duetothemodulationmannerandactualintegerprogrammingrequirement。optimalresultsofbitandpoweralloca—tioncannotbeobmined.CloudP
4、articleSwarmOptimization(CPSO)algorithmisproposed.Anovelevolutionarymodeisgiv·enusinguncertainpropertyofcloudmodeltoimprovediversityofpopulationandovercometheshortcomingofrunningin-tolocalminimuminParticleSwarmOptimization(PSO)algorithm,whichcanrealizethebalancebetweenexplorat
5、ionandex·ploitationinsearchspace.Dynamicallyreducingsearchspaceinevolutionaryprocesscanimproveconvergencespeedofaigo—rithmproposed.AccordinglytheproblemofbitallocationmaximizingdatarateunderthepowerandbiterrorrateconstraintsoverthedistributionnetworkiSsolvedinCPS0.Simulationre
6、sultsdemonstratetheperformanceofproposedalgorithmisthesameasthatofbitaddingalgorithm,reducingcalculationtime,andthesavablepowerinCPSOalgorithmis4.7-14.8dBmcomparedwiththewater-fillingalgorithmatthesametransmissionrate.Keywords:lowvoltagedistributionnetwork;OrthogonalFrequencyD
7、ivisionMultiplexing(OFDM);bitandpowerallocation;cloudparticle$warnloptimizationalgorithm摘要:自适应OFDM系统的比特功率分配是提高频谱利用率的关键技术,基于注水原理的注水迭代算法能够达到比特功率分配的理论上线,但实际系统中由于调制方式及传输比特整数规划的要求,不能达到比特功率分配的优化结果。鉴于此提出了云粒子群优化算法(CloudParticleSwarmOptimization,CPSO),利用云模型的不确定特性增加群体多样性,解决粒子群优化算法易于陷入局部
8、极值的缺点。通过给出的云粒子群进化模式,实现搜索空间的全局搜索和局部搜索;采用进化过程中动态缩小搜索空间策略提高算法收敛速
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