基于匹配理论的LoRa参数双重匹配优化*杨茂恒,章辉,周超(南开大学电子信息与光学工程学院,天津300350)摘要:将LoRaWAN中的资源分配设定为扩频因子分配和信道分配的优化问题,特别是在LoRaWAN中有大量连接设备的情况下,以保证有限频谱资源的LoRa用户之间的吞吐量公平性。首先,引入匹配理论,将LoRa用户与信道和LoRa用户与扩频因子视为匹配双方,为了最大化它们的效用,提出了一种基于匹配的信道与扩频因子分配算法MSFCAA。然后,以匹配理论为基础,以最大化效用为目标,以最优化网络信道与扩频因子分配为结果,最大限度地提高LoRaWAN中实现的最小信道容量。同时,还提出一种公平传输时间初始化算法,以保证每组参数的吞吐量公平性。仿真结果表明,公平传输时间初始化算法能获得优于其他分配方案的初始分配结果,基于匹配的信道与扩频因子分配算法能显著提升LoRa网络数据提取率并极大降低网络能耗。关键词:LoRaWAN;LoRa;匹配理论;数据提取率中图分类号:TN914文献标志码:Adoi:10.3969/j.issn.1007-130X.2023.06.006DoublematchingoptimizationofLoRaparametersbasedonmatchingtheoryYANGMao-heng,ZHANGHui,ZHOUChao(CollegeofElectronicInformationandOpticalEngineering,NankaiUniversity,Tianjing300350,China)Abstract:ResourceallocationinLoRaWANisexpressedasanoptimizationproblemofspreadingfactorallocationandchannelallocation,especiallywhentherearealargenumberofconnecteddevicesinLoRaWAN,toensurethefairnessofthroughputamongLoRauserswithlimitedspectrumresources.Firstly,thematchingtheoryisintroduced.LoRausersandchannels,andLoRausersandspreadingfac-torsareusedasmatchingpartiestomaximizetheirutility.Therefore,amatching-basedchannelandspreadingfactorassignmentalgorithmisproposed.Basedonthematchingtheory,withthegoalofmax-imizingutility,byoptimizingtheresultsofnetworkchannelandspreadingfactorallocation,themini-mumchannelcapacityachievedinLoRaWANismaximized.Afairairtimeinitializationalgorithmispro-posedtoensurethefairnessofthethroughputofeachgroupofparameters.Thesimulationresultsshowthatthefairairtimeinitializationalgorithmcanobtainbetterinitialallocationresultsthanotheralloca-tionschemes.Thematching-basedchannelsandspreadingfactorsassignmentalgorithmcansignificantlyincreasetheLoR...
