可重构智能表面辅助的毫米波无线携能通信系统研究

Research on Reconfigurable Intelligent Surface-assisted Millimeter Wave Simultaneous Wireless Information and Power Transfer System

提出一种可重构智能表面(Reconfigurable Intelligent Surface,RIS)辅助的毫米波无线携能通信(Simultaneous Wireless Information and Power Transfer,SWIPT)系统,构建了一种以多用户最小用户速率最大化为目标的资源分配优化方案。通过对RIS进行分模块设计,同时进行信息和能量的辅助传输,考虑基站的发射功率限制、所有能量接收设备最低能量需求限制和RIS不同模块的相移约束,建立联合发射波束设计、RIS模块分割比决策及相移设计的混合资源分配优化模型。通过交替优化算法、半正定松弛算法、高斯随机化算法以及黎曼流形优化算法来解决这一非凸的多变量耦合约束优化问题。仿真结果表明,与现有的资源分配方案相比,所提出的联合优化算法在信息传输和能量收集方面均可显著提高系统性能。

A Reconfigurable Intelligent Surface(RIS)assisted Millimeter Wave Simultaneous Wireless Information and Power Transfer(SWIPI)system is proposed,and a multi-user resource allocation optimization scheme is constructed with the objective of maximizing the minimum user rate.A hybrid resource allocation optimization model combining transmit beamforming design,RIS module split ratio decision and phase shift design is developed by sub-modular design of the RIS with both information and energy assisted transmission,taking into account the transmit power limit of the base station,the minimum energy demand limit of all energy receiving devices and the phase shift constraint of different modules of the RIS.This non-convex multivariate coupled constrained optimization problem is solved by an alternating optimization algorithm,a semi-positive definite relaxation algorithm,a Gaussian randomization algorithm and a Riemann flow shape optimization algorithm.Simulation results show that the proposed joint optimization algorithm significantly improves the system performance in terms of both information transfer and energy harvesting compared to existing resource allocation schemes.