Dynamic Reflections: Optimizing Energy Efficiency in Multi-IRS Empowered Green Networks

TL;DR

This paper presents a novel multi-IRS system that optimizes energy efficiency in mm-wave networks through intelligent IRS element control and advanced algorithms, achieving over 132% efficiency gains.

Contribution

It introduces a new multi-IRS assisted mm-wave system with on/off IRS element control and develops an algorithm combining fractional programming and simulated annealing for energy efficiency optimization.

Findings

Up to 132.16% energy efficiency improvement

Effective joint optimization of beamforming and IRS control

Algorithm converges to a suboptimal but efficient solution

Abstract

Intelligent Reflecting Surface (IRS) technology is revolutionizing wireless communications by shifting from channel adaptation to a responsive wireless environment. This paper introduces a multi-IRS assisted millimeter wave (mm-wave) system, allowing intelligent on/off control of individual IRS elements. Our objective is to optimize energy efficiency under Quality of Service (QoS) constraints. We propose an algorithm where the Access Point (AP) adjusts transmit beamforming, and IRS elements control phaseshifts and on/off status until convergence. Utilizing a fractional programming (FP) approach for AP beamforming and Simulated Annealing (SA) for IRS subproblems, we achieve a suboptimum optimal solution. A modified nested FP approach addresses the beamforming subproblem. Performance analysis in a practical scenario reveals a significant up to 132.16\% improvement in energy efficiency compared to scenarios with randomly selected IRS on/off status. This highlights the efficacy of our algorithm in enhancing mm-wave communication systems' overall efficiency.