Low-Complexity Channel Estimation for Intelligent Reflecting Surface-Enhanced Massive MIMO

被引：63
作者：
Chen, Xiao [1 ,2 ]
Shi, Jianfeng [2 ,3 ]
Yang, Zhaohui [4 ]
Wu, Liang [2 ]
机构：
[1] Nanjing Univ Informat Sci & Technol, Coll Artificial Intelligence, Nanjing 210044, Peoples R China
[2] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
[3] Nanjing Univ Informat Sci & Technol, Sch Elect & Informat Engn, Nanjing 210044, Peoples R China
[4] Kings Coll London, Ctr Telecommun Res, Dept Engn, London WC2R 2LS, England
来源：
IEEE WIRELESS COMMUNICATIONS LETTERS | 2021年 / 10卷 / 05期
关键词：
Channel estimation; intelligent reflecting surface; low complexity; separate channel information;
D O I：
10.1109/LWC.2021.3054004
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Intelligent reflecting surface (IRS) consisting of massive passive elements is a promising technology to save the hardware cost and energy consumption, but with a challenging channel estimation of IRS transmission links. In this letter, a low-complexity channel estimation method is first proposed for IRS-enhanced multi-user massive multiple-input and multiple-output systems, which can attain the separate channel state information (CSI) of the cascaded link. The acquisition of the separate CSI contributes to the flexibility of channel estimations for the multi-user case with user mobility. The proposed channel estimation consists of direction-of-arrival and path gain estimations, which are implemented by using the limited radio frequency chains and pilots, respectively. Besides, the computational complexity is analyzed for the proposed and existing methods for comparison. Numerical results show that the proposed method can achieve accurate channel estimation with a low complexity.
引用
收藏
页码：996 / 1000
页数：5
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