Hayder Almosa, R. Shafin, S. Mosleh, Zhou Zhou, Yi Li, Jianzhong Zhang, Lingjia Liu
{"title":"Downlink channel estimation and precoding for FDD 3D Massive MIMO/FD-MIMO systems","authors":"Hayder Almosa, R. Shafin, S. Mosleh, Zhou Zhou, Yi Li, Jianzhong Zhang, Lingjia Liu","doi":"10.1109/WOCC.2017.7929002","DOIUrl":null,"url":null,"abstract":"Accurate downlink channel state information at the transmitter (CSIT) is essential to utilize the benefit of 3D Massive MIMO/FD-MIMO systems. Conventional approaches to obtain CSIT for FDD MIMO systems require downlink training and CSI feedback. However, such training will cause a large overhead for 3D Massive MIMO/FD-MIMO systems because of the large dimensionality of the channel matrix. In this paper, we design an efficient downlink beamforming method based on partial CSI. By exploiting the relationship between uplink (UL) direction-of-arrivals (DoAs) and downlink (DL) direction-of-departures (DoDs), we derive an expression for estimated downlink DoDs, which will be used for downlink beamforming to compare the performance with traditional method in terms of downlink achievable rate that we derived. Simulation results also verifies that, in terms of achievable rate, our proposed method outperform the traditional beamforming method.","PeriodicalId":6471,"journal":{"name":"2017 26th Wireless and Optical Communication Conference (WOCC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 26th Wireless and Optical Communication Conference (WOCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOCC.2017.7929002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Accurate downlink channel state information at the transmitter (CSIT) is essential to utilize the benefit of 3D Massive MIMO/FD-MIMO systems. Conventional approaches to obtain CSIT for FDD MIMO systems require downlink training and CSI feedback. However, such training will cause a large overhead for 3D Massive MIMO/FD-MIMO systems because of the large dimensionality of the channel matrix. In this paper, we design an efficient downlink beamforming method based on partial CSI. By exploiting the relationship between uplink (UL) direction-of-arrivals (DoAs) and downlink (DL) direction-of-departures (DoDs), we derive an expression for estimated downlink DoDs, which will be used for downlink beamforming to compare the performance with traditional method in terms of downlink achievable rate that we derived. Simulation results also verifies that, in terms of achievable rate, our proposed method outperform the traditional beamforming method.