摘要
物理层安全是解决信息安全的有效技术。论文针对含有无人机窃听者的系统安全问题,采用无人机辅助的方式发射人工噪声,即空中人工噪声发射机,提升系统安全性能。通过推导保密中断概率的闭合表达式衡量系统的安全性能,为了有效应对无人机窃听者的快速移动变化,提出基于Q-learning的空中人工噪声发射机轨迹优化算法,以达到在无人机窃听者移动情况下系统保密性能最优。仿真结果表明,所提算法能快速收敛,并且空中人工噪声发射机能够跟踪窃听者移动来确定自身最佳位置,对窃听信道实施有效干扰,从而保证系统保密中断概率最小。
Physical layer security is effective to solve the problem of communication security.Aiming at the system security problem with unmanned aerial vehicle(UAV)eavesdroppers,this paper uses UAV aided way to transmit artificial noise,that is,air artificial noise transmitter,the system security performance is improved.The security performance of the system is measured by deriving the closed expression of security output probability,in order to effectively deal with the mobility of UAV eavesdroppers,a trajectory optimization algorithm of air artificial noise transmitter based on Q-learning is proposed to achieve the optimal security performance of the system when UAV eavesdroppers move.The results show that the proposed algorithm converges quickly.More⁃over,the air artificial noise transmitter can track the eavesdropper's movement to determine its best position,and the eavesdropper channel is effectively jammed,so as to ensure the minimum secrecy output probability.
作者
谭蓉俊
TAN Rongjun(Kunming Shipborne Equipment Research&Test Center,Kunming 650216)
出处
《舰船电子工程》
2022年第4期79-85,共7页
Ship Electronic Engineering
