Joint Trajectory, Power Profile and Harvested Energy Management in Cooperative UAVs

Unmanned Aerial Vehicles (UAVs) have been a subject of research for cooperative communication for quite some time. To achieve the highest possible data rates, UAVs must be positioned optimally. For this cooperative communication to be most effective (maximizing data rates), the UAVs' positions and trajectories are critically important. Additionally, the limited onboard power supply, which depletes rapidly, becomes a decisive factor when burdened with transmission loads. In this research, UAV-assisted cooperative communication is explored, with a focus on moving UAVs rather than stationary ones. The objective is to maximize data rates through optimal trajectory planning, from the UAVs' initial positions to their final destinations, and through efficient utilization of onboard power resources. In this scenario, the UAVs harvest energy from the power received from the source and use it for further communication. A Mixed Integer Non-Linear Problem (MINLP) mathematical model is formulated to address these issues. Additionally, an efficient e-optimal algorithm is proposed, based on the mesh adaptive direct search method. This algorithm adaptively minimizes the search space of the problem using exploration and exploitation techniques to solve the non-convex MINLP model. The performance of the proposed algorithm is validated through Monte Carlo simulation.