Coverage optimization for UAV-aided Internet of Things with partial channel knowledge

Due to the high maneuverability of unmanned aerial vehicles (UAVs), they have been widely deployed to boost the performance of Internet of Things (IoT). In this paper, to promote the coverage performance of UAV-aided IoT communications, we maximize the minimum average rate of the IoT devices by jointly optimizing the resource allocation strategy and the UAV altitude. Particularly, to depict the practical propagation environment, we take the composite channel model including both the small-scale and the large-scale channel fading into account. Due to the difficulty in acquiring the random small-scale channel fading, we assume that only the large-scale channel sate information (CSI) is available. On this basis, we formulate an optimization problem, which is not convex and challenging to solve. Then, an efficient iterative algorithm is proposed using block coordinate descent and successive convex optimization tools. Finally, simulation results are presented to demonstrate the significant performance gain of the proposed scheme over existing ones