Sparsity Learning Based Blind Signal Detection for Massive MIMO with Generalized Spatial Modulation

被引:0
|
作者
Kuai, Xiaoyan [1 ]
Yuan, Xiaojun [1 ]
Yan, Wenjing [1 ]
Liu, Hang [2 ]
Zhang, Ying Jun [2 ]
机构
[1] Univ Elect Sci & Tech China, Ctr Intelligent Networking & Commun, Natl Key Lab Sci & Tech Commun, Chengdu, Peoples R China
[2] Chinese Univ Hong Kong, Dept Informat Engn, Hong Kong, Peoples R China
来源
2019 IEEE/CIC INTERNATIONAL CONFERENCE ON COMMUNICATIONS IN CHINA (ICCC) | 2019年
关键词
Massive MIMO; double sparsity; spatial modulation; message passing; blind detection;
D O I
10.1109/iccchina.2019.8855874
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we study joint antenna activity detection, channel estimation, and multiuser detection for massive multiple-input multiple-output (MIMO) systems with general spatial modulation (GSM). We establish a double-sparsity massive MIMO model by considering the channel sparsity of the massive MIMO channel and the signal sparsity of GSM. Based on the double-sparsity model, we develop the message-passing based blind channel-and-signal estimation (BCSE) algorithm to efficiently exploit the channel and the signal sparsity. We show that BCSE significantly outperforms the state-of-the-art blind detection and training-based algorithms for massive MIMO systems with GSM.
引用
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页数:6
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