物联网学报2024，Vol.8Issue(2)：46-55,10.DOI:10.11959/j.issn.2096-3750.2024.00389
基于DDPG的智能反射面辅助无线携能通信系统性能优化
DDPG-based performance optimization algorithm for IRS-assisted simultaneous wireless information and power transfer systems
摘要
Abstract
For the intelligent reflecting surface(IRS)-assisted multiple input single output(MISO)simultaneous wireless information and power transfer(SWIPT)system,the beam forming vector at the base station and the reflected beam forming vector of the IRS were jointly optimized,by considering the maximum transmit power of the base station,the unit modulus constraint of the IRS reflection phase shift matrix,and the minimum energy constraint of the energy receiver.The object was to maximize the spectrum efficiency.To solve the non-convex optimization problem,a deep de-terministic policy gradient(DDPG)algorithm based on deep reinforcement learning was proposed.Simulation results show that the average reward of the DDPG algorithm is related to the learning rate.Under the condition of selecting the appropriate learning rate,the DDPG algorithm can obtain an average mutual information similar to that of the traditional optimization algorithm,but the running time is significantly lower than that of the traditional non-convex optimization algorithm.Even if the number of antennas and the number of reflective units are increased,the DDPG algorithm can still converge in a short period of time.This indicates that the DDPG algorithm can effectively improve the computational effi-ciency and is suitable for communication services with high real-time requirements.关键词
多输入单输出/无线携能通信/智能反射面/波束成形/深度确定性策略梯度Key words
multiple input single output/simultaneous wireless information and power transfer/intelligent reflecting surface/beam forming/deep deterministic policy gradient分类
信息技术与安全科学引用本文复制引用
罗丽平,潘伟民..基于DDPG的智能反射面辅助无线携能通信系统性能优化[J].物联网学报,2024,8(2):46-55,10.基金项目
广西科技重大专项(No.AA23073006) （No.AA23073006）
广西民族大学研究生创新计划(No.gxun-chxs2022298) Guangxi Science and Technology Major Project(No.AA23073006),Guangxi Minzu University Graduate Inno-vation Program(No.gxun-chxs2022098) （No.gxun-chxs2022298）
