Training Signal Design for Sparse Channel Estimation in Intelligent Reflecting Surface-Assisted Millimeter-Wave Communication

被引：19

作者：

Noh, Song ^{[1
]}

Yu, Heejung ^{[2
]}

Sung, Youngchul ^{[3
]}

机构：

[1] Incheon Natl Univ, Dept Informat & Telecommun Engn, Incheon 22012, South Korea

[2] Korea Univ, Dept Elect & Informat Engn, Sejong 30019, South Korea

[3] Korea Adv Inst Sci & Technol, Sch Elect Engn, Daejeon 305701, South Korea

来源：

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS | 2022年 / 21卷 / 04期

基金：

新加坡国家研究基金会;

关键词：

Channel estimation; Training; Transmission line matrix methods; Transmitters; Bayes methods; Wireless communication; Sparse matrices; Millimeter wave (mmWave) communication; intelligent reflecting surface (IRS); signal design; sparse channel estimation; Cramer-Rao bounds; MASSIVE MIMO; CAPACITY; ANTENNA;

D O I：

10.1109/TWC.2021.3112173

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, the problem of training signal design for intelligent reflecting surface (IRS)-assisted millimeter-wave (mmWave) communication under a sparse channel model is considered. The problem is approached based on the Cramer-Rao lower bound (CRB) on the mean-square error (MSE) of channel estimation. By exploiting the sparse structure of mmWave channels, the CRB for the channel parameter composed of path gains and path angles is derived in closed form under Bayesian and hybrid parameter assumptions. Based on the derivation and analysis, an IRS reflection pattern design method is proposed by minimizing the CRB as a function of design variables under constant modulus constraint on reflection coefficients. Extensions of the proposed design to a multi-antenna transceiver, a uniform planar array (UPA)-based IRS, and multi-user case are discussed. Numerical results validate the effectiveness of the proposed design method for sparse mmWave channel estimation.

引用

页码：2399 / 2413

页数：15

共 43 条

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