TY  - INPR
A1  - Hu, X
A1  - Wen, P
A1  - Xiao, H
A1  - Wang, W
A1  - Wong, KK
KW  - Mobile edge computing (MEC)
KW  -  simultaneous
wireless information and power transfer (SWIPT)
KW  -  unmanned
aerial vehicle (UAV)
JF  - IEEE Transactions on Vehicular Technology
UR  - https://doi.org/10.1109/tvt.2025.3530426
PB  - Institute of Electrical and Electronics Engineers (IEEE)
SN  - 0018-9545
N2  - 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 assistant 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 non-convex problem. Numerous experiments validate the effectiveness of the proposed scheme.
ID  - discovery10204644
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
AV  - public
SP  - 1
Y1  - 2025/01/01/
EP  - 6
TI  - Maximizing Energy Charging for UAV-Assisted MEC Systems With SWIPT
ER  -