无人机网络中基于分层博弈的干扰对抗频谱接入优化

Hierarchical game based spectrum access optimization for anti-jamming in UAV network

针对无人机通信网络中的干扰对抗问题,提出了一种基于分层博弈的自适应频谱接入优化机制。考虑到无人机网络节点的动态特性,将干扰器视为分层博弈领导者,无人机用户视为分层博弈跟随者,不同层级间博弈参与者具有不同的效应函数,采用斯坦伯格均衡分析所构建的博弈并证明了均衡解的存在性和唯一性。在此基础上设计一种分层信道选择学习算法来求解博弈的均衡解,并分析其收敛性能。仿真表明,所提算法能使网络节点智能地调整信道选择策略,从而获得良好的吞吐量性能。

For the anti-jamming spectrum access optimization problem in unmanned aerial vehicle(UAV)communication networks,considering the complex and diverse malicious jamming from jammers,a Bayesian Stackelberg game was proposed to formulate the competitive relations between UAV users and jammers.Specifically,jammers acted as the leader,whereas users acted as followers of the proposed game.Based on their different utility functions,the jammer and users independently and selfishly selected their optimal strategies and obtained the optimal channels selection.Due to the NP-hard nature,it was challenging to obtain the Stackelberg Equilibrium of the proposed game.To this end,a hierarchical learning framework was formulated,and a hierarchical channel selection-learning algorithm was proposed.Simulations demonstrate that with the proposed hierarchical learning algorithm,UAV nodes can adjust their channel selection and obtain superior performance.