Swarm Intelligence Optimization of Multi-RIS Aided MmWave Beamspace MIMO

TL;DR

This paper explores a RIS-assisted mmWave MIMO system with multiple users, using swarm intelligence to optimize beam selection, power, and RIS configuration, especially when direct links are blocked, showing improved rates with increased RIS units.

Contribution

It introduces a PSO-based joint optimization algorithm for beam, power, and RIS configuration in multi-RIS mmWave MIMO systems with blocked direct links.

Findings

PSO-based optimization improves sum rate performance.

Increasing RIS unit cells enhances achievable rates.

Trade-off between complexity and sum rate achieved.

Abstract

We investigate the performance of a multiple reconfigurable intelligence surface (RIS)-aided millimeter wave (mmWave) beamspace multiple-input multiple-output (MIMO) system with multiple users (UEs). We focus on a challenging scenario in which the direct links between the base station (BS) and all UEs are blocked, and communication is facilitated only via RISs. The maximum ratio transmission (MRT) is utilized for data precoding, while a low-complexity algorithm based on particle swarm optimization (PSO) is designed to jointly perform beam selection, power allocation, and RIS profile configuration. The proposed optimization approach demonstrates positive trade-offs between the complexity (in terms of running time) and the achievable sum rate. In addition, our results demonstrate that due to the sparsity of beamspace channels, increasing the number of unit cells (UCs) at RISs can lead to higher achievable rates than activating a larger number of beams at the MIMO BS.