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

Anh Le Thi, Hong Nguyen Thi, Trung Pham Viet, Vo Nguyen Quoc Bao
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Abstract

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.
基于粒子群优化的协同NOMA-IRS网络性能评价
本文研究了智能反射面(IRS)辅助的协同非正交多址(NOMA)系统在能量收集(EH)中继网络中的性能。特别是,在我们提出的系统中,一个基站与两个NOMA用户通过采用功率分割(PS)架构和IRS组件的最佳EH中继进行通信。为了提高系统的性能,提出了基于目标用户功率分配和IRS相移的粒子群优化算法(PSO),使总数据速率(SDR)最大化。为了验证粒子群算法的性能,考虑了另一种群体智能技术遗传算法和穷举搜索方法。最后,本文还展示了支持noma的IRS与不支持IRS的系统相比的突出性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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