  Unmanned aerial vehicle (UAV) communication has emerged as a prominent
technology for emergency communications (e.g., natural disaster) in the
Internet of Things (IoT) networks to enhance the ability of disaster
prediction, damage assessment, and rescue operations promptly. A UAV can be
deployed as a flying base station (BS) to collect data from time-constrained
IoT devices and then transfer it to a ground gateway (GW). In general, the
latency constraint at IoT devices and UAV's limited storage capacity highly
hinder practical applications of UAV-assisted IoT networks. In this paper,
{full-duplex (FD) radio} 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 considered to be successfully served iff its data is collected by the
UAV and conveyed to GW timely during flight time}. In this context, we aim to
maximize the number of served IoT devices by jointly optimizing bandwidth,
power allocation, and the UAV trajectory while satisfying each device's
requirement and the UAV's limited storage capacity. The formulated optimization
problem is troublesome to solve due to its non-convexity and combinatorial
nature. {Towards appealing applications, we first relax binary variables into
continuous ones 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 system
throughput.
