无人机网络中基于分层博弈的干扰对抗频谱接入优化

doi:10.11959/j.issn.1000-436x.2020114

Abstract

Abstract:

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.

Key words: unmanned aerial vehicle network, anti-jamming, spectrum access, hierarchical game, reinforcement learning

CLC Number:

TN92

Chaoqiong FAN,Chenglin ZHAO,Bin LI. Hierarchical game based spectrum access optimization for anti-jamming in UAV network[J]. Journal on Communications, 2020, 41(6): 26-33.

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References 20

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