  This paper proposes a time-efficient mechanism to decrease the on-line
computing time of solving the joint unmanned aerial vehicle base station
(UAV-BS) deployment and user/sensor association (UDUA) problem aiming at
maximizing the downlink sum transmission throughput. The joint UDUA problem is
decoupled into two sub-problems: one is the user association sub-problem, which
gets the optimal matching strategy between aerial and ground nodes for certain
UAV-BS positions; and the other is the UAV-BS deployment sub-problem trying to
find the best position combination of the UAV-BSs that make the solution of the
first sub-problem optimal among all the possible position combinations of the
UAV-BSs. In the proposed mechanism, we transform the user association
sub-problem into an equivalent bipartite matching problem and solve it using
the Kuhn-Munkres algorithm. For the UAV-BS deployment sub-problem, we
theoretically prove that adopting the best UAV-BS deployment strategy of a
previous user distribution for each new user distribution will introduce little
performance decline compared with the new user distribution's ground true best
strategy if the two user distributions are similar enough. Based on our
mathematical analyses, the similarity level between user distributions is well
defined and becomes the key to solve the second sub-problem. Numerical results
indicate that the proposed UDUA mechanism can achieve near-optimal system
performance in terms of average downlink sum transmission throughput and
failure rate with enormously reduced computing time compared with benchmark
approaches.
