Enhancing the Energy Efficiency Utilizing Reconfigurable Intelligent Surfaces in Next Generation Communication Networks

Abstract

Next generation networks (5G and beyond) face significant challenges in improving energy efficiency without sacrificing performance. This paper investigates the enhancement of energy efficiency (EE) in a Multi-Input Single-Output (MISO) system under Rician fading channels using Reconfigurable Intelligent Surfaces (RIS). Unlike traditional fully-active models, we investigate a different optimization framework combining Maximum Ratio Transmission (MRT) beamforming, genetic algorithms, and RIS phase shift optimization under selective RIS element activation. Two activation schemes are evaluated: random ON/OFF and Top-contributing 30% element selection based on channel gain to balance reflection gain against hardware power overhead. Simulations using MATLAB demonstrate that activating only the Top-contributing 30% of RIS elements achieves high EE with acceptable SNR. Among all techniques, phase shift optimization with selective RIS activation yields the highest EE of 5.3 × 10⁶ bits/Joule, highlighting its potential for energy-efficient 6G communications.

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