Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication

TL;DR

This paper investigates energy-efficient design strategies for reconfigurable intelligent surfaces in multi-user wireless communication, proposing algorithms that significantly improve energy efficiency over traditional relaying methods.

Contribution

It introduces novel optimization algorithms for RIS phase shifts and power allocation, along with a realistic power consumption model for RIS-based systems.

Findings

Up to 300% increase in energy efficiency compared to traditional relaying.

Development of computationally affordable algorithms for RIS optimization.

Analysis of RIS performance in realistic outdoor environments.

Abstract

The adoption of a Reconfigurable Intelligent Surface (RIS) for downlink multi-user communication from a multi-antenna base station is investigated in this paper. We develop energy-efficient designs for both the transmit power allocation and the phase shifts of the surface reflecting elements, subject to individual link budget guarantees for the mobile users. This leads to non-convex design optimization problems for which to tackle we propose two computationally affordable approaches, capitalizing on alternating maximization, gradient descent search, and sequential fractional programming. Specifically, one algorithm employs gradient descent for obtaining the RIS phase coefficients, and fractional programming for optimal transmit power allocation. Instead, the second algorithm employs sequential fractional programming for the optimization of the RIS phase shifts. In addition, a realistic power consumption model for RIS-based systems is presented, and the performance of the proposed methods is analyzed in a realistic outdoor environment. In particular, our results show that the proposed RIS-based resource allocation methods are able to provide up to $300\%$ higher energy efficiency, in comparison with the use of regular multi-antenna amplify-and-forward relaying.