• 算法设计与分析 •

### 基于大规模MIMO的散射信道估计技术

1. （中国电子科技集团公司第五十四研究所,河北石家庄050081）
• 出版日期:2023-01-04 发布日期:2023-01-04
• 作者简介:史清林(1994—),男,河北衡水人,硕士研究生,研究方向:无线通信系统,E-mail: sqldyk@163.com; 刘丽哲(1978—),女,研究员,硕士生导师,研究方向:无线通信系统,E-mail: Liu_lizhe@sina.com; 李行健(1992—),男,博士,研究方向:无线通信系统,E-mail: lixingjianjan@163.com。
• 基金资助:
通信网信息传输与分发技术重点实验室基金资助项目(6142104210212)

### Troposcatter Channel Estimation Based on Massive MIMO

1. （The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang 050081, China）
• Online:2023-01-04 Published:2023-01-04

Abstract: With the increasing demand of users for communication speed, the communication capacity of tropospheric scattering communication needs to be improved. Massive multiple input multiple output (MIMO) technology is an important way to improve capacity. This paper studies the channel estimation problem of troposcatter communication system based on massive MIMO. Firstly, a massive MIMO troposcatter channel model based on two-dimensional uniform rectangular array is established. Secondly, a channel covariance matrix estimation algorithm is proposed to improve the traditional minimum mean square (MMSE) channel estimation algorithm. Finally, the accuracy of channel estimation algorithm is compared with that of least square (LS), traditional MMSE and ideal MMSE. The simulation results show that when the SNR is 0~25 dB, the accuracy of the traditional MMSE algorithm is not significantly improved compared with that of LS algorithm, and there is a certain gap between the accuracy of the ideal MMSE algorithm and that of the traditional MMSE algorithm. However, the accuracy of the improved MMSE channel estimation algorithm is better than that of the traditional MMSE algorithm. Under the same conditions, when the NMSE is the same, the SNR of the improved MMSE algorithm can be improved by 3~5 dB, and gradually approaches the ideal MMSE algorithm with the increase of SNR.