Yueyun Chen, Yanqing Xia, Yaxin Xing, Liuqing Yang
{"title":"Low complexity hybrid precoding for mmWave Massive MIMO systems","authors":"Yueyun Chen, Yanqing Xia, Yaxin Xing, Liuqing Yang","doi":"10.1109/WOCC.2017.7929004","DOIUrl":null,"url":null,"abstract":"Massive MIMO has the advantage of providing excellent multiplexing/diversity gain and data rate due to the large antenna array equipped at the BS or UEs. However, the high hardware cost and computational complexity limit the practical implementation of large antenna array. In this paper, we formulate a Minimum Mean Square Error (MMSE) based optimization model under the partially-connected structure to reduce the hardware cost, and propose a low complexity hybrid precoding algorithm based on the Particle Swarm Ant Colony Optimization (HP-PSACO). Simulation results show that the proposed algorithm with low computational complexity achieves higher energy efficiency than the fully digital baseband precoding.","PeriodicalId":6471,"journal":{"name":"2017 26th Wireless and Optical Communication Conference (WOCC)","volume":"8 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 26th Wireless and Optical Communication Conference (WOCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOCC.2017.7929004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Massive MIMO has the advantage of providing excellent multiplexing/diversity gain and data rate due to the large antenna array equipped at the BS or UEs. However, the high hardware cost and computational complexity limit the practical implementation of large antenna array. In this paper, we formulate a Minimum Mean Square Error (MMSE) based optimization model under the partially-connected structure to reduce the hardware cost, and propose a low complexity hybrid precoding algorithm based on the Particle Swarm Ant Colony Optimization (HP-PSACO). Simulation results show that the proposed algorithm with low computational complexity achieves higher energy efficiency than the fully digital baseband precoding.