可重构智能表面(Reconfigurable Intelligent Surface,RIS)通过改变电磁传播环境来提高无线通信的覆盖范围和容量.然而,RIS技术部署和维护大量的RIS反射元件也会产生大量的能量消耗.基于此,在满足用户的最低速率、基站的最大发射功率以及RIS相位角的单位模数等约束下,研究RIS辅助的多用户多输入单输出(Multiple Input Single Output,MISO)系统中资源优化问题,实现能量效率最大化.具体地,分析多用户下信干噪比(Signal to Interference Noise Ratio,SINR)、系统总功耗与RIS的相位矩阵和开关矩阵的关系;建立以基站的波束赋形、RIS的相位角及开关矩阵为变量的最大化能量效率优化问题;针对优化问题的求解,提出基站端使用最大比发送预编码,使用户接收的SINR最大,并提出一种改进型的粒子群优化(Particle Swarm Optimization,PSO)算法,通过优化RIS的开关矩阵以最小化系统总功耗;进一步设计了相位矩阵、功率和开关矩阵进行交替迭代优化的方案.仿真结果表明,改进型算法得到的最优性能结果比较稳定,特别是在加入开关的系统中,经过优化开关矩阵后获得的系统能量效率相比不带开关的系统提升了约20％,证实了所提方案对系统能量效率提升的有效性.
Energy Efficient Resource Allocation for RIS-aided Multi-user MISO Systems
Reconfigurable Intelligent Surfaces(RIS)enhance wireless communication coverage range and capacity by manipulating the electromagnetic propagation environment.However,the deployment and maintenance of numerous RIS reflecting elements result in significant energy consumption.Therefore,the resource optimization problem in a Multiple Input Single Output(MISO)system assisted by RIS is investigated,with the goal of maximizing energy efficiency while satisfying constraints such as minimum user rate,maximum base station transmission power,and unity modulus of RIS phase angles.Specifically,the relationship between Signal to Interference Noise Ratio(SINR)for multiple users,total system power consumption,and the phase matrix and switch matrix of the RIS is analyzed.Then,the energy efficiency maximization problem is formulated with base station beamforming,RIS phase angles,and switch matrix as variables.To solve the optimization problem,the idea of using maximum ratio transmission precoding at the base station is proposed to maximize the received SINR for users,and an improved Particle Swarm Optimization(PSO)algorithm is introduced to optimize the RIS switch matrix to minimize total system power.Additionally,an iterative scheme is designed to realize alternate optimization between phase matrix,power,and switch matrix.The simulation results demonstrate that the improved algorithm consistently achieves optimal performance,particularly in systems with switches.After optimizing the switch matrix,the system's energy efficiency is improved by approximately 20％compared with the system without switches,confirming the effectiveness of the proposed approach in enhancing system energy efficiency.
万方数据
维普
