Performance evaluation of cooperative NOMA-IRS network using particle swarm optimization

In this paper, we investigate the performance of intelligent reflecting surface (IRS) aided cooperative non-orthogonal multiple access (NOMA) system in an energy-harvesting (EH) relay network. Particularly, in our proposed system, a base station communicates with two NOMA users with a help of the best EH relay employing a power-splitting (PS) architecture and IRS component. To boost the system performance, an important object is the maximization of sum data rate (SDR) which is proposed by using particle swarm optimization (PSO) based on power allocation (PA) for each destination user and phase shift of IRS. To validate the performance of PSO, another swarm intelligence technique as Genetic Algorithm (GA) and Exhaustive Search (ES) methods are considered. Finally, the outstanding performance of NOMA-supported IRS in comparison with the system without IRS is also shown in this paper.