Energy Efficiency Optimization of Intelligent Reflective Surface-assisted Terahertz-RSMA System

TL;DR

This paper proposes an energy efficiency optimization method for IRS-assisted Terahertz-RSMA systems, demonstrating that the salp swarm algorithm outperforms the successive convex approximation in efficiency and computational time.

Contribution

It introduces the use of the salp swarm algorithm for energy efficiency optimization in IRS-assisted Terahertz-RSMA systems, offering a faster and more effective alternative to traditional methods.

Findings

SSA outperforms SCA in energy efficiency improvements.

SSA reduces computational time significantly.

System performance is optimized with the proposed method.

Abstract

This paper examines the energy efficiency optimization problem of intelligent reflective surface (IRS)-assisted multi-user rate division multiple access (RSMA) downlink systems under terahertz propagation. The objective function for energy efficiency is optimized using the salp swarm algorithm (SSA) and compared with the successive convex approximation (SCA) technique. SCA technique requires multiple iterations to solve non-convex resource allocation problems, whereas SSA can consume less time to improve energy efficiency effectively. The simulation results show that SSA is better than SCA in improving system energy efficiency, and the time required is significantly reduced, thus optimizing the system's overall performance.