TDD reciprocity calibration for multi-user massive MIMO systems with iterative coordinate descent

作     者：Hao WEI Dongming WANG Jiangzhou WANG Xiaohu YOU 

作者机构：National Mobile Communications Research Laboratory Southeast University School of Engineering and Digital Arts University of Kent 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2016年第59卷第10期

页      面：93-102页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 081001[工学-通信与信息系统] 

基　　金：supported in part by National Basic Research Program of China (973) (Grant Nos. 2013CB336600, 2012CB316004) National Natural Science Foundation of China (NSFC) (Grant No. 61221002, 61271205) National High Technology Research and Development Program of China (863) (Grant No. 2014AA01A706) Colleges and Universities in Jiangsu Province Plans to Graduate Research and Innovation (Grant No. KYLX15 0075) 

主　　题：TDD reciprocity calibration total least squares coordinate descent large-scale MIMO 

摘      要：For massive multiple-input multiple-output(MIMO) antenna systems, time division duplexing(TDD) is preferred since the downlink precoding matrix can be obtained through the uplink channel estimation,thanks to the channel reciprocity. However, the mismatches of the transceiver radio frequency(RF) circuits at both sides of the link make the whole communication channel non-symmetric. This paper extends the total least square(TLS) method to the case of self-calibration, where only the antennas of the access points(APs) are involved to exchange the calibration signals with each other and the feedback from the user equipments(UEs)is not required. Then, the proof of the equivalence between the TLS method and the least square(LS) method is presented. Furthermore, to avoid the eigenvalue decomposition required by these two methods to obtain the calibration coefficients, a novel algorithm named as iterative coordinate descent(ICD) method is *** analysis and simulation results show that the ICD method significantly reduces the complexity and achieves almost the same performance of the LS method.