  A Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) scheme
with simultaneous wireless information and power transfer (SWIPT) is proposed
in this paper. Unlike existing MEC-WPT schemes that disregard the downlink
period for returning computing results to the ground equipment (GEs), our
proposed scheme actively considers and capitalizes on this period. By
leveraging the SWIPT technique, the UAV can simultaneously transmit energy and
the computing results during the downlink period. In this scheme, our objective
is to maximize the remaining energy among all GEs by jointly optimizing
computing task scheduling, UAV transmit and receive beamforming, BS receive
beamforming, GEs' transmit power and power splitting ratio for information
decoding, time scheduling, and UAV trajectory. We propose an alternating
optimization algorithm that utilizes the semidefinite relaxation (SDR),
singular value decomposition (SVD), and fractional programming (FP) methods to
effectively solve the nonconvex problem. Numerous experiments validate the
effectiveness of the proposed scheme.
