TY - JOUR
T1 - Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis
AU - Wang, Zhaorui
AU - Liu, Liang
AU - Cui, Shuguang
N1 - Funding Information:
Manuscript received December 24, 2019; revised April 13, 2020; accepted June 15, 2020. Date of publication June 30, 2020; date of current version October 9, 2020. This work was supported in part by The Hong Kong Polytechnic University under Grant P0030001, in part by the Key Area Research and Development Program of Guangdong Province under Grant 2018B030338001, in part by the National Key Research and Development Program of China under Grant 2018YFB1800800, in part by the Natural Science Foundation of China under Grant NSFC-61629101, and in part by the Guangdong Zhujiang Project under Grant 2017ZT07X152. This article was presented in part at the IEEE Wireless Communications and Networking Conference 2020, May [1]. The associate editor coordinating the review of this article and approving it for publication was I. Bergel. (Corresponding author: Liang Liu.) Zhaorui Wang and Liang Liu are with the Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong (e-mail: [email protected]; [email protected]).
Publisher Copyright:
© 2002-2012 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/10
Y1 - 2020/10
N2 - In intelligent reflecting surface (IRS) assisted communication systems, the acquisition of channel state information is a crucial impediment for achieving the beamforming gain of IRS because of the considerable overhead required for channel estimation. Specifically, under the current beamforming design for IRS-Assisted communications, in total KMN+KM channel coefficients should be estimated, where K , N and M denote the numbers of users, IRS reflecting elements, and antennas at the base station (BS), respectively. For the first time in the literature, this paper points out that despite the vast number of channel coefficients that should be estimated, significant redundancy exists in the user-IRS-BS reflected channels of different users arising from the fact that each IRS element reflects the signals from all the users to the BS via the same channel. To utilize this redundancy for reducing the channel estimation time, we propose a novel three-phase pilot-based channel estimation framework for IRS-Assisted uplink multiuser communications, in which the user-BS direct channels and the user-IRS-BS reflected channels of a typical user are estimated in Phase I and Phase II, respectively, while the user-IRS-BS reflected channels of the other users are estimated with low overhead in Phase III via leveraging their strong correlation with those of the typical user. Under this framework, we analytically prove that a time duration consisting of K+N+\max (K-1,\lceil (K-1)N/M \rceil) pilot symbols is sufficient for perfectly recovering all the KMN+KM channel coefficients under the case without receiver noise at the BS. Further, under the case with receiver noise, the user pilot sequences, IRS reflecting coefficients, and BS linear minimum mean-squared error channel estimators are characterized in closed-form.
AB - In intelligent reflecting surface (IRS) assisted communication systems, the acquisition of channel state information is a crucial impediment for achieving the beamforming gain of IRS because of the considerable overhead required for channel estimation. Specifically, under the current beamforming design for IRS-Assisted communications, in total KMN+KM channel coefficients should be estimated, where K , N and M denote the numbers of users, IRS reflecting elements, and antennas at the base station (BS), respectively. For the first time in the literature, this paper points out that despite the vast number of channel coefficients that should be estimated, significant redundancy exists in the user-IRS-BS reflected channels of different users arising from the fact that each IRS element reflects the signals from all the users to the BS via the same channel. To utilize this redundancy for reducing the channel estimation time, we propose a novel three-phase pilot-based channel estimation framework for IRS-Assisted uplink multiuser communications, in which the user-BS direct channels and the user-IRS-BS reflected channels of a typical user are estimated in Phase I and Phase II, respectively, while the user-IRS-BS reflected channels of the other users are estimated with low overhead in Phase III via leveraging their strong correlation with those of the typical user. Under this framework, we analytically prove that a time duration consisting of K+N+\max (K-1,\lceil (K-1)N/M \rceil) pilot symbols is sufficient for perfectly recovering all the KMN+KM channel coefficients under the case without receiver noise at the BS. Further, under the case with receiver noise, the user pilot sequences, IRS reflecting coefficients, and BS linear minimum mean-squared error channel estimators are characterized in closed-form.
KW - channel estimation
KW - Intelligent reflecting surface (IRS)
KW - massive MIMO
KW - multiple-input multiple-output (MIMO)
UR - http://www.scopus.com/inward/record.url?scp=85092775314&partnerID=8YFLogxK
U2 - 10.1109/TWC.2020.3004330
DO - 10.1109/TWC.2020.3004330
M3 - Journal article
AN - SCOPUS:85092775314
SN - 1536-1276
VL - 19
SP - 6607
EP - 6620
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 10
M1 - 9130088
ER -