论文标题
智能反射性表面辅助Terahertz-RSMA系统的能源效率优化
Energy Efficiency Optimization of Intelligent Reflective Surface-assisted Terahertz-RSMA System
论文作者
论文摘要
本文研究了智能反射表面（IRS）辅助的多用户率分部多访问（RSMA）下行链路系统的能源效率优化问题。使用SALP群算法（SSA）优化了能源效率的目标函数，并将其与连续的凸近似（SCA）技术进行了比较。 SCA技术需要多次迭代来解决非convex资源分配问题，而SSA可以减少有效提高能源效率的时间。模拟结果表明，在提高系统能效时，SSA大于SCA，并且所需的时间大大减少，从而优化了系统的整体性能。
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.
