  In this paper, we use an aerial base station (aerial-BS) to enhance fairness
in a dynamic environment with user mobility. The problem of optimally placing
the aerial-BS is a non-deterministic polynomial-time hard (NP-hard) problem.
Moreover, the network topology is subject to continuous changes due to the user
mobility. These issues intensify the quest to develop an adaptive and fast
algorithm for 3D placement of the aerial-BS. To this end, we propose a method
based on reinforcement learning to achieve these goals. Simulation results show
that our method increases fairness among users in a reasonable computing time,
while the solution is comparatively close to the optimal solution obtained by
exhaustive search.
