Joint Trajectory and Power Control Design for UAV Anti-Jamming Communication Network

Recently, unmanned aerial vehicles (UAVs) have been used in wireless communication network due to the advantages of low cost, high mobility and effective deployment. However, complex environment, fading effect and the openness of wireless channel limit the quality of wireless communications, making the communication system vulnerable to jamming attack. In this paper, an anti-jamming UAV communication scheme is developed, in which a UAV is deployed to transmit data to multiple ground user devices under jamming environment. We consider the UAV as a mobile base station, which flies within a target area with several jamming sources in it, and keeps providing wireless communication service from the air via air-to-ground downlink. In addition, we assume that the UAV has limited energy capacity. By applying a deep reinforcement learning based algorithm, the UAV learns from the scheme and spontaneously determines an optimal anti-jamming communication policy that jointly controls the trajectory and power of the UAV. Simulation results shows that the proposed scheme can improve energy efficiency while maintaining a relatively high level of signal-to-interference-plus-noise ratio (SINR) in data transmission tasks.