基于主动诱导机制的中继通信智能抗干扰方法

Intelligent anti⁃jamming relay communication method based on active induction mechanism

抗干扰作为无线通信领域的重要研究方向,近年来受到了越来越多的关注。聚焦对抗环境下的多跳无线通信场景,文中针对跟踪干扰条件下的中继通信抗干扰问题,考虑到通信方与干扰方之间的对抗特性,构建了基于主动诱导机制的斯坦伯格博弈模型,其中用户作为领导者,利用先发制人的优势,选择诱导中继主动吸引干扰攻击,而干扰机作为跟随者。在此基础上,提出了基于Q学习和随机自动学习机的双阶段分层学习中继选择算法。仿真表明,相较于无诱导中继条件的多用户随机自动学习机算法,文中算法能够使用户的平均满意度提高20%以上。

Anti⁃jamming is an important and interesting topic in wireless communication filed.has attracted more and more attentions in recent years.Focusing on the multi⁃hop wireless communication scenario in the adversarial environment,a relay selection optimization problem in anti⁃jamming relay communication networks is studied.Considering the confrontation characteristics between users and jammers,a Stackelberg game with a two⁃stage relay selection deception mechanism is proposed,in which users acted as leaders,take advantages of pre⁃emption so to select a deceptive relay firstly to actively attract jammer attacks,and the jammer acted as a follower.On this basis,a two⁃stage hierarchical learning relay selection algorithm based on Q learning and random stochastic learning is proposed.Simulation results show that compared with the multi⁃user random automatic learning machine algorithm without the induced relay condition,the algorithm can increase the average user satisfaction by more than 20%.