  The rapid development of unmanned aerial vehicle (UAV) technology provides
flexible communication services to terrestrial nodes. Energy efficiency is
crucial to the deployment of UAVs, especially rotary-wing UAVs whose propulsion
power is sensitive to the wind effect. In this paper, we first derive a
three-dimensional (3D) generalised propulsion energy consumption model (GPECM)
for rotary-wing UAVs under the consideration of stochastic wind modeling and 3D
force analysis. Based on the GPECM, we study a UAV-enabled downlink
communication system, where a rotary-wing UAV flies subject to stochastic wind
disturbance and provides communication services for ground users (GUs). We aim
to maximize the energy efficiency (EE) of the UAV by jointly optimizing the 3D
trajectory and user scheduling among the GUs based on the GPECM. We formulate
the problem as stochastic optimization, which is difficult to solve due to the
lack of real-time wind information. To address this issue, we propose an
offline-based online adaptive (OBOA) design with two phases, namely, an offline
phase and an online phase. In the offline phase, we average the wind effect on
the UAV by leveraging stochastic programming (SP) based on wind statistics;
then, in the online phase, we further optimize the instantaneous velocity to
adapt the real-time wind. Simulation results show that the optimized
trajectories of the UAV in both two phases can better adapt to the wind in
changing speed and direction, and achieves a higher EE compared with the
windless scheme. In particular, our proposed OBOA design can be applied in the
scenario with dramatic wind changes, and makes the UAV adjust its velocity
dynamically to achieve a better performance in terms of EE.
