导频污染下的智能反射面辅助无人机传输方法  

IRS-Assisted UAV Transmission with Pilot Pollution

作　　者：马增起 罗屹洁 周浩 王润升 胡宏达 王嘉琦 MA Zengqi;LUO Yijie;ZHOU Hao;WANG Runsheng;HU Hongda;WANG Jiaqi(Army Engineering University of PLA,Nanjing Jiangsu 210007,China)

机构地区：[1]中国人民解放军陆军工程大学,江苏南京210007

出　　处：《通信技术》2023年第9期1036-1042,共7页Communications Technology

摘　　要：被动窃听或主动干扰会给空地通信网络带来严重的安全威胁。智能反射面因其可以智能调控电磁环境,能够有效对抗这类恶意攻击者。在导频污染下,研究通过智能反射面辅助来提升空地通信网络的物理层安全性能具有现实意义。在斯坦伯格博弈、机器学习和分层优化理论与方法的指导下,利用多天线发射机的主动波束成型、智能反射表面的被动波束成型等手段,削弱了主动窃听者导频干扰带来的影响,提升了空地通信网络的传输安全性。Passive eavesdropping or active jamming could pose a serious security threat to air-ground communication networks.Due to the ability of programming electromagnetic environment intelligently,it is available for IRS(Intelligent Reflecting Surface)to defeat such malicious attackers.It is of practical significance to study the improvement of physical layer security performance of air-ground communication networks through IRS assistance with pilot pollution.Based on Stackelberg game,machine learning and hierarchical optimization theories and methods,this paper employs active beamforming of multi-antenna transmitters and passive beamforming of IRS to weaken the impact of pilot interference brought by active eavesdroppers,and improve the transmission security of air-ground communication networks.

关 键 词：导频污染 智能反射面 无人机通信 机器学习 

分 类 号：TN929.5[电子电信—通信与信息系统]