Multi-user passive beamforming in RIS-aided communications and experimental validations

TL;DR

This paper presents a comprehensive approach for multi-user RIS-aided wireless systems, including channel estimation, beamforming, and experimental validation, demonstrating significant spectral efficiency and power gains in real-world tests.

Contribution

It introduces a novel channel estimation and beamforming framework for multi-user RIS systems, validated through real-world experiments with a custom testbed.

Findings

Average spectral efficiency increase of 13.48bps/Hz

Received power gains of 26.6dB and 17.5dB for two users

Successful experimental validation at 5.8GHz

Abstract

Reconfigurable intelligent surface (RIS) is a promising technology for future wireless communications due to its capability of optimizing the propagation environments. Nevertheless, in literature, there are few prototypes serving multiple users. In this paper, we propose a whole flow of channel estimation and beamforming design for RIS, and set up an RIS-aided multi-user system for experimental validations. Specifically, we combine a channel sparsification step with generalized approximate message passing (GAMP) algorithm, and propose to generate the measurement matrix as Rademacher distribution to obtain the channel state information (CSI). To generate the reflection coefficients with the aim of maximizing the spectral efficiency, we propose a quadratic transform-based low-rank multi-user beamforming (QTLM) algorithm. Our proposed algorithms exploit the sparsity and low-rank properties of the channel, which has the advantages of light calculation and fast convergence. Based on the universal software radio peripheral devices, we built a complete testbed working at 5.8GHz and implemented all the proposed algorithms to verify the possibility of RIS assisting multi-user systems. Experimental results show that the system has obtained an average spectral efficiency increase of 13.48bps/Hz, with respective received power gains of 26.6dB and 17.5dB for two users, compared with the case when RIS is powered-off.