RIS Deployment Optimization with Iterative Detection and Decoding in Multiuser Multiple-Antenna Systems

TL;DR

This paper explores how deploying Reconfigurable Intelligent Surfaces (RIS) in multiuser MIMO systems affects detection and decoding performance, providing analytical and simulation results that guide optimal deployment strategies.

Contribution

It offers a comprehensive analysis of RIS deployment impacts on iterative detection and decoding in multiuser MIMO systems, including both theoretical and numerical insights.

Findings

Deployment configuration significantly influences IDD performance.

RIS-assisted systems show robustness to parameter variations.

Insights from SISO extend to multiuser MIMO scenarios.

Abstract

This work investigates a Reconfigurable Intelligent Surface (RIS)-assisted uplink system employing iterative detection and decoding (IDD) techniques. We analyze the impact of tuning system parameter tuning for several deployment configurations, including the number of users, access point (AP) antennas, and RIS elements on the IDD performance. Analytical results for both active and passive RIS in a single-input single-output (SISO) scenario demonstrate how deployment choices affect system performance. Numerical simulations confirm the robustness of the RIS-assisted IDD system to variations in these parameters, showing performance gains in certain configurations. Moreover, the findings indicate that the insights derived from SISO analysis extend to multiuser MIMO IDD systems.