Solar-Aware Trajectory Optimization for UAV-Aide IoT Network

Abstract

This paper investigates a solar-aware trajectory optimization for unmanned aerial vehicles (UAVs) deployed in Internet of Things (IoT) networks for environmental monitoring. We develop a comprehensive energy consumption model that integrates aerodynamic flight dynamics with solar energy harvesting under realistic conditions. Building on this model, we formulate a trajectory optimization problem that considers UAV flight path, velocity, and energy dynamics to maximize reliable data collection and transmission throughput. The problem is inherently non-convex due to probabilistic constraints, energy harvesting non-linearities, and mobility restrictions. To overcome these challenges, we propose a successive convex approximation framework that reformulates the problem into tractable convex subproblems, which are solved iteratively with guaranteed convergence. Simulation results across diverse IoT deployment scenarios demonstrate that the proposed design substantially enhances UAV endurance, energy efficiency, and data throughput compared to benchmark approaches. The results show that solar-powered UAV communications are effective for large-scale IoT networks and contribute to more sustainable, reliable airborne sensing systems.