Is RIS-Aided Massive MIMO Promising with ZF Detectors and Imperfect CSI?

2021/11/02 by Kangda Zhi, Cunhua Pan, Zhi, Kangda +9 · 3 citations
Computer Science · Engineering · Mathematics · #Advanced Wireless Communication Technologies #FOS: Computer and information sciences #FOS: Electrical engineering #Information Theory (cs.IT) #Satellite Communication Systems #Signal Processing (eess.SP) #Underwater Vehicles and Communication Systems #cs.IT #eess.SP #electronic engineering #information engineering #math.IT

paper · pdf · doi:10.48550/arxiv.2111.01585

Submitted to IEEE journal. Keywords: Reconfigurable Intelligent Surface, Intelligent Reflecting Surface, Massive MIMO, Channel estimation, zero-forcing

arxiv created 2021/11/02 · openalex publication_date 2021/11/02 · arxiv updated 2021/11/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper provides a theoretical framework for understanding the performance of reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) with zero-forcing (ZF) detectors under imperfect channel state information (CSI). We first propose a low-overhead minimum mean square error (MMSE) channel estimator, and then derive and analyze closed-form expressions for the uplink achievable rate. Our analytical results demonstrate that: 1) regardless of the RIS phase shift design, the rate of all users scales at least on the order of O(log₂(MN)), where M and N are the numbers of antennas and reflecting elements, respectively; 2) by aligning the RIS phase shifts to one user, the rate of this user can at most scale on the order of O(log₂(MN²)); 3) either M or the transmit power can be reduced inversely proportional to N, while maintaining a given rate. Furthermore, we propose two low-complexity majorization-minimization (MM)-based algorithms to optimize the sum user rate and the minimum user rate, respectively, where closed-form solutions are obtained in each iteration. Finally, simulation results validate all derived analytical results. Our simulation results also show that the maximum sum rate can be closely approached by simply aligning the RIS phase shifts to an arbitrary user.

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