{"title":"MIMO OTA Probe Selection Based on Particle Swarm Optimization","authors":"Xiaoqing Liu, Chunjing Hu, Lijian Xin, Yong Li","doi":"10.1145/3291842.3291870","DOIUrl":null,"url":null,"abstract":"Multiple-input-multiple-output (MIMO) Over-the-air (OTA) testing has attracted great interests for reproducing the realistic channel environment. Among different solutions of OTA, multi-probe anechoic chamber (MPAC) is widely used due to its controllability for channel environment reconstruction. In MPAC, each physical channel of the channel emulator needs to be connected to one polarization of the probe, so it is meaningful to use fewer pro. This paper proposes a particle swarm optimization (PSO) method to find out the positions of the probes and their corresponding probe probes while reproducing the target channel as accurately as possible. It is shown that compared with the traditional uniform probe distribution method, reducing the number of probes can still achieve accurate channel spatial reconstruction.","PeriodicalId":283197,"journal":{"name":"Proceedings of the 2nd International Conference on Telecommunications and Communication Engineering","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Conference on Telecommunications and Communication Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3291842.3291870","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Multiple-input-multiple-output (MIMO) Over-the-air (OTA) testing has attracted great interests for reproducing the realistic channel environment. Among different solutions of OTA, multi-probe anechoic chamber (MPAC) is widely used due to its controllability for channel environment reconstruction. In MPAC, each physical channel of the channel emulator needs to be connected to one polarization of the probe, so it is meaningful to use fewer pro. This paper proposes a particle swarm optimization (PSO) method to find out the positions of the probes and their corresponding probe probes while reproducing the target channel as accurately as possible. It is shown that compared with the traditional uniform probe distribution method, reducing the number of probes can still achieve accurate channel spatial reconstruction.