UAV Relay-Assisted Emergency Communications in IoT Networks: Resource Allocation and Trajectory Optimization

Unmanned aerial vehicle (UAV) communication has emerged as a prominent technology for emergency communications (e.g., natural disaster) in Internet of Things (IoT) networks to enhance the ability of disaster prediction, damage assessment, and rescue operations promptly. In this paper, a UAV is deployed as a flying base station (BS) to collect data from time-constrained IoT devices and then transfer the data to a ground gateway (GW). In general, the latency constraint at IoT users and the limited storage capacity of UAV highly hinder practical applications of UAV-assisted IoT networks. In this paper, full-duplex (FD) technique is adopted at the UAV to overcome these challenges. In addition, half-duplex (HD) scheme for UAV-based relaying is also considered to provide a comparative study between two modes (viz., FD and HD). Herein, a device is successfully served iff its data is collected by UAV and conveyed to GW within the flight time. In this context, we aim at maximizing the number of
served IoT devices by jointly optimizing bandwidth and power allocation, as well as the UAV trajectory,
while satisfying the requested timeout (RT) requirement of each device and the UAV’s limited storage
capacity. The formulated optimization problem is troublesome to solve due to its non-convexity and
combinatorial nature. Toward appealing applications, we first relax binary variables into continuous
values and transform the original problem into a more computationally tractable form. By leveraging
inner approximation framework, we derive newly approximated functions for non-convex parts and then
develop a simple yet efficient iterative algorithm for its solutions. Next, we attempt to maximize the total throughput subject to the number of served IoT devices. Finally, numerical results show that the proposed algorithms significantly outperform benchmark approaches in terms of the number of served IoT devices and the amount of collected data.