Joint Phase Shift Optimization and Precoder Selection for RIS-Assisted 5G NR MIMO Systems

TL;DR

This paper introduces a novel joint optimization method for RIS phase shifts and MIMO precoding in 5G systems, improving signal quality and reducing complexity through a singular value-based approach.

Contribution

It proposes a $oldsymbol{ extlambda}$-based RIS optimization strategy combined with a singular value approach for precoder selection, reducing computational complexity in 5G MIMO systems.

Findings

Proposed method outperforms conventional approaches in simulations.

The $oldsymbol{ extlambda}$-based optimization enhances channel conditions.

The approach reduces time complexity by avoiding mutual information calculations.

Abstract

By intelligently reconfiguring wireless propagation environment, reconfigurable intelligent surfaces (RISs) can enhance signal quality, suppress interference, and improve channel conditions, thereby serving as a powerful complement to multiple-input multiple-output (MIMO) architectures. However, jointly optimizing the RIS phase shifts and the MIMO transmit precoder in 5G and beyond networks remains largely unexplored. This paper addresses this gap by proposing a singular value ($\lambda$)-based RIS optimization strategy, where the phase shifts are configured to maximize the dominant singular values of the cascaded channel matrix, and the corresponding singular vectors are utilized for MIMO transmit precoding. The proposed precoder selection does not require mutual information computation across subbands, thereby reducing time complexity. To solve the $\lambda$-based optimization problem, maximum cross-swapping algorithm (MCA) is applied while an effective rank-based method is utilized for benchmarking purposes. The simulation results show that the proposed precoder selection method consistently outperforms the conventional approach under $\lambda$-based RIS optimization.