无线电工程2025，Vol.55Issue(4)：749-756,8.DOI:10.3969/j.issn.1003-3106.2025.04.007
基于深度强化学习的RIS辅助NOMA网络隐蔽通信方案
Deep Reinforcement Learning Based Covert Communication for RIS Assisted NOMA Networks
摘要
Abstract
Aiming at the issues of poor adaptability and high complexity of traditional convex optimization methods in covert communication scenarios within Reconfigurable Intelligent Surface(RIS)-assisted Non-Orthogonal Multiple Access(NOMA)networks,a general-purpose optimization algorithm based on Deep Reinforcement Learning(DRL)is proposed to break through the performance bottlenecks of existing methods in dynamic environments and provide efficient solutions for complex communication scenarios.A Twin Delayed Deep Deterministic policy gradient algorithm(TD3)is presented,which integrates truncated action mechanisms and delayed update strategies.By leveraging the Actor-Critic architecture,it realizes joint optimization of base station power allocation and RIS phase shifts to maximize the covert rates.Simulation results show that the proposed TD3,integrating truncated action mechanisms and delayed update strategies,effectively suppresses policy overestimation errors and enhances the stability of the Actor-Critic architecture.Under user Quality of Service(QoS)constraints,this algorithm significantly improves the covert communication rate by jointly optimizing the base station power allocation and RIS phase shifts.Furthermore,the proposed scheme can dynamically adapt to the changes in channel environment,meeting the core requirements of covert communication scenarios.关键词
隐蔽通信/深度强化学习/非正交多址接入/可重构智能表面Key words
covert communication/DRL/NOMA/RIS分类
电子信息工程引用本文复制引用
张伟,王振军,孙路,崔雅茹,聂础辉,李一鸣,杨刚..基于深度强化学习的RIS辅助NOMA网络隐蔽通信方案[J].无线电工程,2025,55(4):749-756,8.基金项目
湖南省自然科学基金(2024JJ7218,2025JJ70287) （2024JJ7218,2025JJ70287）
深圳市科技计划资助项目(JCYJ20220530164814032) （JCYJ20220530164814032）
湖南省教育厅项目(23C0217) Hunan Provincial Natural Science Foundation of China(2024JJ7218,2025JJ70287) （23C0217）
Project Funded by Shenzhen Science and Tech-nology Plan China(JCYJ20220530164814032) （JCYJ20220530164814032）
Project of Hunan Provincial Educational Committee(23C0217) （23C0217）
