摘要
针对空地一体化网络(air-ground integrated networks,AGIN)中快速动态变化的移动用户导致信道过时及难以估计等问题,构建双RIS辅助的认知UAV协作NOMA传输系统。提出基于深度学习的认知UAV中继选择策略,分析双瑞利、瑞利与双瑞利混合信道下主用户的安全中断性能。仿真结果表明,基于深度学习中继选择策略相较于随机中继选择能够实现更高的系统安全性能。
A dual RIS-assisted cognitive UAV collaborative NOMA transmission system is constructed to address the issues of channel outdated as well as difficult estimation due to rapidly and dynamically changing mobile users in Air-Ground Integrated Networks(AGIN).A deep learning-based cognitive UAV relay selection strategy is proposed,and the secure outage performance of the primary user under dual-RIS,RIS and dual-RIS hybrid channels is analyzed.Simulation results show that the deep learning-based relay selection strategy can achieve higher system security performance compared to random relay selection.
作者
李世豪
李震
薛鹏
李美玲
李世兴
LI Shihao;LI Zhen;XUE Peng;LI Meiling;LI Shixing(College of Electronic Information Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China;5G Technology and Application Innovation Center for National Defense in Shanxi,Taiyuan 030024,China;North Automation Control Technology Institute,Taiyuan 030006,China)
出处
《火力与指挥控制》
北大核心
2025年第8期106-113,共8页
Fire Control & Command Control
基金
山西省科技创新人才团队专项计划(202304051001035)
山西省国防5G技术与应用创新中心项目
山西省科技成果转化引导专项(202204021301055)
山西省专利转化专项计划项目(202302003)
山西省留学回国人员科研基金资助项目(2021-133)。
