  In this letter, a novel framework to deliver critical spread out URLLC
services deploying unmanned aerial vehicles (UAVs) in an out-of-coverage area
is developed. To this end, the resource optimization problem, i.e., resource
blocks (RBs) and power allocation, and optimal UAV deployment strategy are
studied for UAV-assisted 5G networks to jointly maximize the average sum-rate
and minimize the transmit power of UAV while satisfying the URLLC requirements.
To cope with the sporadic URLLC traffic problem, an efficient online URLLC
traffic prediction model based on Gaussian Process Regression (GPR) is proposed
which derives optimal URLLC scheduling and transmit power strategy. The
formulated problem is revealed as a mixed-integer nonlinear programming
(MINLP), which is solved following the introduced successive minimization
algorithm. Finally, simulation results are provided to show our proposed
solution approach's efficiency.
