移动通信2025，Vol.49Issue(4)：96-103,8.DOI:10.3969/j.issn.1006-1010.20250309-0001
一种基于可移动天线和深度强化学习的无人机中继通信方案
A UAV Relay Communication Scheme Based on Movable Antenna and Deep Reinforcement Learning
摘要
Abstract
In the traditional unmanned aerial vehicle(UAV)relay communication architecture,UAVs and user equipment(UE)are equipped with fixed-position antennas,which constrains the adaptive ability of the communication system to dynamic channel variations.To overcome this limitation,movable antennas are equipped on the UAV and UEs to enhance the adaptability of the communication system to time-varying communication environments.This paper employs the soft actor-critic algorithm to jointly optimize the UAV's position,the UAV's movable antenna positions,and the positions of UE movable antennas,aiming to maximize the minimum communication rate among all UEs.The simulation results show that,compared with the fixed-position antenna scheme,the proposed scheme increases the minimum UE communication rate by approximately 16%.关键词
中继通信/无人机/可移动天线/深度强化学习Key words
relay communication/UAV/movable antenna/deep reinforcement learning分类
信息技术与安全科学引用本文复制引用
郭天昊,尹瑞龙,李仙钟,闫远超,陈桢..一种基于可移动天线和深度强化学习的无人机中继通信方案[J].移动通信,2025,49(4):96-103,8.基金项目
山西省基础研究计划资助项目(202303021212014) （202303021212014）
山西省回国留学人员科研资助项目(2023-005) （2023-005）
