Joint trajectory and passive beamforming optimization in IRS-UAV enhanced anti-jamming communication networks

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.