UAV-Enabled Relaying and Edge Computing: Hybrid Network Optimization

This paper exploits an Unmanned Aerial Vehicle assisted Mobile Edge Computing (UAV-MEC) system to meet the computation demand of User Equipments (UEs). However, in conventional UAV-MEC architecture, a UAV is dedicated only to one single service, which will inevitably limit overall system performance. To address the above issue of the conventional UAV-MEC architecture, we propose a hybrid UAV-MEC model. In this model, a UAV is treated as an agent to provide either relay or computing services. Moreover, we propose an MEC Multiple Agent UAV Trajectory and User Association Policy Gradient (MEC-MAUTUA-PG) algorithm to optimize offloading strategies of the UEs as well as the trajectory design of UAV. We show the superiority of the proposed algorithm in terms of delay and the safety of trajectory design of UAV in the environment.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2025-03-24
DOI
https://doi.org/10.1109/tvt.2025.3549366
Citations
2
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
9.99

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

UAV-Enabled Relaying and Edge Computing: Hybrid Network Optimization

Dong In Kim, Chuanhuang Li, Bo Ma, Shaohan Feng et al.
2 citations
IEEE Transactions on Vehicular Technology
UAV Applications and Optimization
9.99
article

UAV-Enabled Relaying and Edge Computing: Hybrid Network Optimization

Dong In Kim, Chuanhuang Li, Bo Ma, Shaohan Feng, Dusit Niyato, Jiawei Ye
article en
2 citations

Abstract

This paper exploits an Unmanned Aerial Vehicle assisted Mobile Edge Computing (UAV-MEC) system to meet the computation demand of User Equipments (UEs). However, in conventional UAV-MEC architecture, a UAV is dedicated only to one single service, which will inevitably limit overall system performance. To address the above issue of the conventional UAV-MEC architecture, we propose a hybrid UAV-MEC model. In this model, a UAV is treated as an agent to provide either relay or computing services. Moreover, we propose an MEC Multiple Agent UAV Trajectory and User Association Policy Gradient (MEC-MAUTUA-PG) algorithm to optimize offloading strategies of the UEs as well as the trajectory design of UAV. We show the superiority of the proposed algorithm in terms of delay and the safety of trajectory design of UAV in the environment.

IEEE Transactions on Vehicular TechnologyVol. 74(7)
Nanyang Technological University (SG), Zhejiang Gongshang University (CN), Sungkyunkwan University (KR)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 3%
UAV Applications and Optimization
9.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

UAV-Enabled Relaying and Edge Computing: Hybrid Network Optimization — Dong In Kim, Chuanhuang Li, et al. · IEEE Transactions on Vehicular Technology (2025) | TGRS Research Map | TGRS