  This work considers unmanned aerial vehicle (UAV) networks for collecting
data covertly from ground users. The full-duplex UAV intends to gather critical
information from a scheduled user (SU) through wireless communication and
generate artificial noise (AN) with random transmit power in order to ensure a
negligible probability of the SU's transmission being detected by the
unscheduled users (USUs). To enhance the system performance, we jointly design
the UAV's trajectory and its maximum AN transmit power together with the user
scheduling strategy subject to practical constraints, e.g., a covertness
constraint, which is explicitly determined by analyzing each USU's detection
performance, and a binary constraint induced by user scheduling. The formulated
design problem is a mixed-integer non-convex optimization problem, which is
challenging to solve directly, but tackled by our developed penalty successive
convex approximation (P-SCA) scheme. An efficient UAV trajectory initialization
is also presented based on the Successive Hover-and-Fly (SHAF) trajectory,
which also serves as a benchmark scheme. Our examination shows the developed
P-SCA scheme significantly outperforms the benchmark scheme in terms of
achieving a higher max-min average transmission rate from all the SUs to the
UAV.
