Bidirectional Approximate Message Passing for RIS-Assisted Multi-User MISO Communications

TL;DR

This paper introduces a bidirectional approximate message passing algorithm for efficient joint channel estimation and signal recovery in RIS-assisted multi-user MISO wireless systems, improving over existing methods.

Contribution

It proposes a novel bidirectional AMP algorithm utilizing Taylor series and Gaussian approximation for RIS-based systems, addressing key channel estimation challenges.

Findings

The proposed algorithm outperforms benchmark methods in simulations.

Insights on RIS parameter impacts on algorithm performance.

Enhanced channel estimation accuracy in RIS-assisted systems.

Abstract

Reconfigurable intelligent surfaces (RISs) have been recently considered as a promising candidate for energy-efficient solutions in future wireless networks. Their dynamic and lowpower configuration enables coverage extension, massive connectivity, and low-latency communications. Due to a large number of unknown variables referring to the RIS unit elements and the transmitted signals, channel estimation and signal recovery in RIS-based systems are the ones of the most critical technical challenges. To address this problem, we focus on the RIS-assisted multi-user wireless communication system and present a joint channel estimation and signal recovery algorithm in this paper. Specifically, we propose a bidirectional approximate message passing algorithm that applies the Taylor series expansion and Gaussian approximation to simplify the sum-product algorithm in the formulated problem. Our simulation results show that the proposed algorithm shows the superiority over a state-of-art benchmark method. We also provide insights on the impact of different RIS parameter settings on the proposed algorithms.