Joint Resource Allocation and UAV Trajectory Optimization for Space–Air–Ground Internet of Remote Things Networks

Abstract

Given the limited transmission power of smart devices in Internet of Remote Things (IoRT), unmanned aerial vehicle (UAV) aided space-air-ground (SAG) networks become a beneficial remedy for uplink data transmission in IoRT networks. In this article, we propose a SAG–IoRT framework, where drones act as relays to upload the data from smart devices to low earth orbit satellites. Considering the large number of smart devices, we maximize the system capacity by jointly optimizing smart devices connection scheduling, power control, and UAV trajectory, where the joint optimization is a nonconvex optimization problem. The formulated problem is a mixed integer nonconvex optimization problem, which is challenging to solve directly. Hence, an efficient iterative algorithm is proposed for solving the above-mentioned nonconvex optimization problem by applying variable substitution, successive convex optimization techniques, and the block coordinate decent algorithm. In particular, we alternately iterate smart device connection scheduling, power control, and UAV trajectory design to obtain the maximum system capacity. Numerical simulation results show that our proposed algorithm substantially improves the system capacity in comparison to the static UAV scheme, and achieves a gain of at least 22.3% in terms of the capacity against dynamic UAV scheme with a circular trajectory.