Huang-Babg Li, Xuying Zhao, Chen Guo, Donglin Wang
{"title":"大规模MIMO系统的高并行检测算法","authors":"Huang-Babg Li, Xuying Zhao, Chen Guo, Donglin Wang","doi":"10.1109/ICEIEC.2017.8076517","DOIUrl":null,"url":null,"abstract":"Due to the asymptotically orthogonal channel, minimum mean square error detection algorithm is near-optimal for uplink massive MIMO systems, but it involves matrix inversion with high complexity. This paper proposes a high-parallelism detection algorithm in an iterative way to avoid the complicated matrix inversion. The parallelism level is analyzed and convergence is proved in detail. The proposed algorithm can be implemented in a high level, which is equal to the max number of received data streams. The complexity can be reduced by one order of magnitude comparing with MMSE algorithm. Simulation results show that the proposed algorithm can closely match the performance of the MMSE algorithm with few number of iterations. It also outperforms Neumann Series approximation algorithm in terms of block error rate (BLER) performance with same number of iterations.","PeriodicalId":163990,"journal":{"name":"2017 7th IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A high-parallelism detection algorithm for massive MIMO systems\",\"authors\":\"Huang-Babg Li, Xuying Zhao, Chen Guo, Donglin Wang\",\"doi\":\"10.1109/ICEIEC.2017.8076517\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the asymptotically orthogonal channel, minimum mean square error detection algorithm is near-optimal for uplink massive MIMO systems, but it involves matrix inversion with high complexity. This paper proposes a high-parallelism detection algorithm in an iterative way to avoid the complicated matrix inversion. The parallelism level is analyzed and convergence is proved in detail. The proposed algorithm can be implemented in a high level, which is equal to the max number of received data streams. The complexity can be reduced by one order of magnitude comparing with MMSE algorithm. Simulation results show that the proposed algorithm can closely match the performance of the MMSE algorithm with few number of iterations. It also outperforms Neumann Series approximation algorithm in terms of block error rate (BLER) performance with same number of iterations.\",\"PeriodicalId\":163990,\"journal\":{\"name\":\"2017 7th IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 7th IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEIEC.2017.8076517\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 7th IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEIEC.2017.8076517","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A high-parallelism detection algorithm for massive MIMO systems
Due to the asymptotically orthogonal channel, minimum mean square error detection algorithm is near-optimal for uplink massive MIMO systems, but it involves matrix inversion with high complexity. This paper proposes a high-parallelism detection algorithm in an iterative way to avoid the complicated matrix inversion. The parallelism level is analyzed and convergence is proved in detail. The proposed algorithm can be implemented in a high level, which is equal to the max number of received data streams. The complexity can be reduced by one order of magnitude comparing with MMSE algorithm. Simulation results show that the proposed algorithm can closely match the performance of the MMSE algorithm with few number of iterations. It also outperforms Neumann Series approximation algorithm in terms of block error rate (BLER) performance with same number of iterations.