An endurance and transmission balancing scheme for solar-powered UAV-aided charging data collection in IoT networks

Solar-powered unmanned aerial vehicle (S-UAV) effectively alleviates the energy limitations of traditional UAV, providing greater degrees of freedom for energy allocation in S-UAV-aided charging-enabled data collection. However, the endurance of the S-UAV, ground device endurance, and data transmission performance are three crucial metrics for ensuring the completion of data collection. Optimizing one may not necessarily lead to satisfactory performance in the others. In this paper, we focus on balancing the endurance of S-UAV and ground devices, along with data transmission, to achieve a robust data collection. We propose a novel S-UAV utility to describe the energy consuming and harvesting of S-UAV and devices, and data collection volume from devices. Next, we maximize the proposed S-UAV utility function, via jointly optimizing 3D trajectory, velocity and device scheduling. To tackle the proposed mixed-integer non-convex maximization, we apply the block coordinate descent, slack variable substitution and successive convex approximation techniques to obtain a sub-optimal solution that converges in polynomial time. Numerical results demonstrate the proposed scheme achieves an effective balance among the endurance of the S-UAV, ground devices, and data transmission, outperforming state-of-the-art schemes. In the case of 120 s, it achieves an increase of 25.84% in average data collection volume and a 390.11% enhancement in device residual energy, while only sacrificing 3.28% of the S-UAV’s residual energy.