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Aerial Energy Orchestration for Heterogeneous UAV-Assisted Wireless Communications

Authors
Lakew, Demeke ShumeyeNa, WoongsooDao, Nhu-NgocCho, Sungrae
Issue Date
Jun-2022
Publisher
Institute of Electrical and Electronics Engineers Inc.
Keywords
Aerial energy sharing; Batteries; Internet of Things; MIMO communication; Solar energy; Trajectory; unmanned aerial vehicle (UAV)-assisted communications; Unmanned aerial vehicles; wireless charging; Wireless networks
Citation
IEEE Systems Journal, v.16, no.2, pp 2383 - 2384
Pages
2
Journal Title
IEEE Systems Journal
Volume
16
Number
2
Start Page
2383
End Page
2384
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/47519
DOI
10.1109/JSYST.2021.3075316
ISSN
1932-8184
1937-9234
Abstract
The integration of unmanned aerial vehicles (UAVs) into future-generation wireless networks is a promising strategy for complementing terrestrial communication infrastructures that will lead to capacity and coverage improvements. Unfortunately, the energy limitations of the existing off-the-shelf small-size UAVs are significant challenges, especially during long missions. In this article, first, we investigate the communication model of a heterogeneous UAV-assisted wireless network that consists of multiple energy-constrained battery-powered small-size UAVs (a.k.a. follower UAVs) and a large-size UAV (a.k.a. dispatcher UAV) with solar energy harvesting capability. Subsequently, we propose an aerial energy sharing algorithm to improve the lifetime of the system by orchestrating energy balancing among follower UAVs. In particular, the dispatcher UAV having large energy capacity owing to its battery size and solar energy harvesting capability shares its energy with follower UAVs using radio-frequency-based power transfer through beamforming. The proposed energy sharing algorithm considers the placement, available battery capacity, and mission execution time of the follower UAVs to decide the energy sharing points with optimum efficiency. Extensive simulations show that our proposed algorithm outperforms existing algorithms in terms of charging efficiency and energy balancing among UAVs. IEEE
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Cho, Sung Rae
소프트웨어대학 (소프트웨어학부)
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