  Unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) systems
offer significant advantages in coverage and deployment flexibility, but suffer
from endurance limitations due to the limited onboard energy. This paper
proposes to improve the energy efficiency of UAV-enabled WPT systems with
multiple ground sensors by utilizing reconfigurable intelligent surface (RIS).
Specifically, the total energy consumption of the UAV is minimized, while
meeting the energy requirement of each sensor. Firstly, we consider a
fly-hover-broadcast (FHB) protocol, in which the UAV radiates radio frequency
(RF) signals only at several hovering locations. The energy minimization
problem is formulated to jointly optimize the UAV's trajectory, hovering time
and the RIS's reflection coefficients. To solve this complex non-convex
problem, we propose an efficient algorithm. Specifically, the successive convex
approximation (SCA) framework is adopted to jointly optimize the UAV's
trajectory and hovering time, in which a minorization-maximization (MM)
algorithm that maximizes the minimum charged energy of all sensors is provided
to update the reflection coefficients. Then, we investigate the general
scenario in which the RF signals are radiated during the flight, aiming to
minimize the total energy consumption of the UAV by jointly optimizing the
UAV's trajectory, flight time and the RIS's reflection coefficients. By
applying the path discretization (PD) protocol, the optimization problem is
formulated with a finite number of variables. A high-quality solution for this
more challenging problem is obtained. Finally, our simulation results
demonstrate the effectiveness of the proposed algorithm and the benefits of RIS
in energy saving.
