Joint Trajectory Design and Resource Allocation for UAV-assisted Jamming NOMA Cognitive UAV Networks

Abstract

The exploitation of non-orthogonal multiple access (NOMA) for the cognitive unmanned aerial vehicle (UAV) networks is promising to tackle the spectrum scarcity problem. However, the openness characteristic of the spectrum in the cognitive UAV networks makes the private information vulnerable to be eavesdropped. In this paper, a downlink UAV-assisted jamming cognitive UAV network with NOMA is studied to tackle this issue. In order to improve the secure performance of the networks, the trajectories and transmit power of the cognitive UAV and the jamming UAV are jointly optimized to maximize the average security rate of the secondary users. An alternative algorithm that employs the successive convex approximation (SCA) method is proposed to solve the challenging non-convex optimization problem. Furthermore, the simulation results show that the proposed scheme can significantly improve the system secure performance.