Joint Trajectory and Resource Optimization for UAV-Assisted SWIPT Systems: A Comparative Study of Linear and Nonlinear Energy Harvesting Models

This study considers an unmanned aerial vehicle (UAV)-assisted simultaneous wireless information and power transfer (SWIPT) system in which the UAV broadcasts wireless signals to ground nodes (GNs) that receive information and harvest energy simultaneously using a policy of power splitting (PS) or time switching (TS). While taking into account the throughput and fairness of GNs, we investigate a joint optimization of the trajectory, transmit power of the UAV, and the energy harvesting (EH) ratio of the GNs to maximize the sum of the logarithmic average throughput of the GNs while ensuring the average harvested energy requirement for each GN in terms of both linear and nonlinear EH models. We employ a successive convex approximation method to address the nonconvex nature of this problem, which stems from incorporating a nonlinear EH model. This approach allows us to approximate the problem as convex for each control parameter. Thereafter, we propose a respective iterative algorithm based on the block coordinate descent method to identify the optimal solution for each convex problem under each PS or TS policy. Extensive simulations confirm that the proposed method improves average throughput and fairness index while satisfying the EH constraint by effectively optimizing the three control parameters, thereby achieving a near-optimal performance that is superior to existing baseline methods. Our results also reveal significant differences in the UAV trajectory and resource allocation patterns between linear and nonlinear EH models under the PS and TS policies. Furthermore, we explore the practical aspects of EH by comparing both EH models, such as the limitations of the linear EH model in satisfying the EH requirement in real-world SWIPT environments. The findings underscore the importance of considering nonlinear EH models in practical UAV-assisted SWIPT environments.