Energy Efficient Resource Allocation in RIS Aided 6G Networks

Abstract

Reconfigurable Intelligent Surfaces (RISs) are emerging as a potential solution for Tera- Hertz communication. Which pave the way to envision high energy efficiency and capacity targets beyond 5G (B5G)/6G generation. Energy-efficient resource allocation in RID-based B5G/6G wireless network is examined in this thesis. The goal is to reduce energy consumption while maintaining the quality of service (QoS) of the network. In the last decade of wireless communication, energy efficiency (EE) has emerged as a significant performance evaluation metric of the network. This thesis presents a novel mathematical framework to maximize the EE of a RIS-based multiuser network, which is a fractional programming problem (FP). We have proposed, Charnes–Cooper transformation (CCT) to transform this fractional programming problem into a concave program. The newly formulated EE maximization problem is subjected to power, QoS, phase shift, and amplitude constraints. Then an outer approximation algorithm (OAA) is proposed for this type of concave problem, which has not been investigated yet in the literature. Proposed algorithm is assessed in terms of convergence and complexity analysis. Results achieved from the simulation testify that the impact of incorporating RIS in the system increases throughput and EE both; increasing the number of RIS elements increases the throughput and EE; on increasing the required data rate both throughput and EE decrease; and when the power is reduced, throughput decreases while EE increases. Finally, the comparison analysis suggests our proposed algorithm outperforms the mesh adaptive direct search algorithm (MADS).