  In this letter, we study a wireless communication system with a fixed-wing
unmanned aerial vehicle (UAV) employed to collect information from a group of
ground nodes (GNs). Our objective is to maximize the UAV's energy efficiency
(EE), which is defined as the achievable rate among all GNs per unit propulsion
energy consumption of the UAV. To efficiently solve this problem with
continuous-time functions, we propose a new method based on receding horizon
optimization (RHO), which significantly reduces the computational complexity
compared to the conventional time discretization method. Specifically, we
sequentially solve the EE maximization problem over a moving time-window of
finite duration, for each of which the number of optimization variables is
greatly reduced. Simulation results are provided to show the effectiveness of
the proposed method.
