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Joint Trajectory and Passive Beamforming Optimization in IRS-UAV Enhanced Anti-Jamming Communication Networks 被引量:7

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摘要 This paper investigates the anti-jamming communication scenario where an intelligent reflecting surface(IRS)is mounted on the unmanned aerial vehicle(UAV)to resist the malicious jamming attacks.Different from existing works,we consider the dynamic deployment of IRS-UAV in the environment of the mobile user and unknown jammer.Therefore,a joint trajectory and passive beamforming optimization approach is proposed in the IRS-UAV enhanced networks.In detail,the optimization problem is firstly formulated into a Markov decision process(MDP).Then,a dueling double deep Q networks multi-step learning algorithm is proposed to tackle the complex and coupling decision-making problem.Finally,simulation results show that the proposed scheme can significantly improve the anti-jamming communication performance of the mobile user.
出处 《China Communications》 SCIE CSCD 2022年第5期191-205,共15页 中国通信(英文版)
基金 This work was supported in part by the National Natural Science Foundation of China(No.61971474,No.61771488) in part by the Beijing Nova Program under Grant Z201100006820121 in part by China Postdoctoral Science Foundation Funded Project under Grant 2019T120071.
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