基于深度强化学习的UAV-RIS辅助鲁棒海上无线通信  

Robust maritime wireless communication assisted by UAV-RIS based on deep reinforcement learning

作　　者：夏薇 唐冬[1] XIA Wei;TANG Dong(Guangzhou University,Guangzhou 510700,China)

机构地区：[1]广州大学,广州510700

出　　处：《计算机应用文摘》2025年第6期73-77,共5页

摘　　要：随着我国综合实力的提升,海上紧急救援、科研考察及军事行动对无线通信的需求日益增长,提升海上通信系统的可靠性尤为重要。为模拟实际海况,在基站到RIS再到用户的级联信道信息不完美的假设下,文章提出了一种UAV-RIS辅助的海上无线通信系统,旨在改善非固定海上用户(OMU)的服务质量。通过DRL算法联合优化MU-MISO系统中的无人机轨迹、波束成形矩阵及RIS相移,以最大化下行链路速率。With the improvement of China̓s comprehensive strength,the demand for wireless communication in maritime emergency rescue,scientific research and military operations is increasing day by day,and improving the reliability of maritime communication systems is particularly important.To simulate actual sea conditions,under the assumption of imperfect cascade channel information from base stations to RIS and then to users,this article proposes a UAV-RIS assisted maritime wireless communication system aimed at improving the service quality of offshore mobile users(OMU).By jointly optimizing the UAV trajectory,beamforming matrix,and RIS phase shift in the MU-MISO system using the DRL algorithm,the downlink rate can be maximized.

关 键 词：UAV-RIS 海上通信 深度强化学习 无人机轨迹 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]