Joint Optimization of UAV Communication and Time-Constrained Pickup Missions

Unmanned aerial vehicles (UAVs) are increasingly expected to support both wireless communication and logistics missions, creating a need for integrated operation strategies that jointly manage data collection and physical item handling. This paper investigates a UAV system that simultaneously performs uplink communication with multiple ground nodes (GNs) while completing time-constrained item-pickup tasks. To enhance both throughput and fairness across GNs, we maximize the proportional fair spectral efficiency of GNs while ensuring that all items are collected within the required mission duration under payload and geographical constraints. The resulting formulation constitutes a mixed-integer nonconvex optimization problem involving binary pickup assignments, binary communication scheduling, and trajectory-dependent channel coupling, making direct global optimization intractable. To address this challenge, we develop an iterative convexification framework that integrates the successive convex approximation and the penalty convex–concave procedure within a block coordinate descent structure, enabling efficient joint optimization of trajectory, pickup timing/sequence, and GN scheduling. Simulation results validate that the proposed scheme dynamically shapes the UAV trajectory to improve channel conditions without violating the pickup deadline and compensates disadvantaged GNs through proportional fair scheduling. As a result, it consistently outperforms the baseline strategies under various system parameters.