Dynamic Role Switching Scheme With Joint Trajectory and Power Control for Multi-UAV Cooperative Secure Communication

Due to the high flexibility and mobility, unmanned aerial vehicles (UAVs) can be deployed as aerial relays touring to serve ground users (GUs), especially when the ground base station is temporally damaged. However, the broadcasting nature of wireless channels makes such communication vulnerable to be wiretapped by malicious eavesdropping users (EUs). Besides the collecting offloading data for legitimate GUs, UAVs are also expected to be friendly jammers, i.e., generating artificial noise (AN) to deteriorate the wiretapping of EUs. With this in mind, a novel role switching scheme (RSS) is proposed in the paper to guarantee the secure communication by the cooperation of multiple UAVs, where each UAV is allowed to switch its role as a collector or a jammer autonomously to explore a wider trajectory space. It's worthy to be noticed that the joint optimization for the trajectory of UAVs and the transmission power of GUs and UAVs with role switching scheme is a non-convex mixed integer non-linear programming (MINLP) problem. Since the relaxation of binary variables will lead the solution dropping into local minimum, a deep reinforcement learning (DRL) combined successive convex approximate (SCA) algorithm is further designed to maximize the achievable secrecy rate (ASR) of GUs. Numerical results illustrate that compared with the role fixed scheme (RFS) and relaxation based SCA approaches, the proposed DRL-SCA algorithm endows UAVs the capacity to fly close enough to target users (both GUs and EUs) with less moving distance which brings better ASR and less energy consumption.