Ergodic Rate Analysis of Reconfigurable Intelligent Surface-Aided Massive MIMO Systems with ZF Detectors

Kangda Zhi, Cunhua Pan*, Hong Ren, Kezhi Wang

*Corresponding author for this work

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Abstract

This letter investigates the reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) systems with a two-timescale design. First, the zero-forcing (ZF) detector is applied at the base station (BS) based on instantaneous aggregated channel state information (CSI), which is the superposition of the direct channel and the cascaded user-RIS-BS channel. Then, by leveraging the channel statistical property, we derive the closed-form ergodic achievable rate expression. Using a gradient ascent method, we design the RIS passive beamforming relying only on the long-term statistical CSI. We prove that the ergodic rate scales on the order of O(log2 (MN)), where M and N denote the number of BS antennas and RIS elements, respectively. We also prove the striking superiority of the considered RIS-aided system with ZF detectors over the RIS-free systems and RIS-aided systems with maximum-ratio combining (MRC).

Original languageEnglish
Pages (from-to)264-268
Number of pages5
JournalIEEE Communications Letters
Volume26
Issue number2
Early online date17 Nov 2021
DOIs
Publication statusPublished - Feb 2022

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