Joint Trajectory and Resource Optimization for UAV-Enabled Relaying Systems

Unmanned aerial vehicles (UAVs) have attracted attentions due to their mobility and high possibility of the line of sight (LoS) channel. We can fully use these two properties by carefully optimizing the UAVs' trajectories and cooperating with some facilities. A UAV working as a mobile relay now attracts many interests due to its low cost and reliable performance. In this paper, we study a relaying system, where a UAV works as an aerial mobile relay to help some ground base stations send information to ground users periodically by using time division multiple access (TDMA). We aim to maximize the minimum average user rate through solving a non-convex and information causality constraints involved problem by jointly optimizing the UAV trajectory, nodes scheduling, and power allocation to ensure the fairness among all users. Finally, we propose an efficient iterative algorithm to solve a derived mixed-integer non-convex optimization problem to achieve this target by using block coordinate descent (BCD) and successive convex approximation (SCA) methods and prove the convergence of our algorithm. Simulations show the effectiveness of our proposed algorithm, some useful trade-offs and insights about the structure of our optimized trajectory, and the influence of two widely used trajectory initialization methods.