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...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology Vol. 74; no. 7; pp. 11644 - 11649
Main Authors: Ma, Bo, Ye, Jiawei, Feng, Shaohan, Li, Chuanhuang, Niyato, Dusit, Kim, Dong In
Format: Journal Article
Language:English
Published: New York IEEE 01.07.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Autonomous aerial vehicles
Cloud computing
Computational modeling
Computer architecture
deep deterministic policy gradient algorithm (DDPG)
Edge computing
Mobile computing
Multi-access edge computing
Optimization
Relaying
Relays
Servers
System performance
Trajectory
trajectory design
Unmanned aerial vehicle assisted mobile edge computing
Unmanned aerial vehicles
ISSN:0018-9545, 1939-9359
Online Access:Get full text
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Summary: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.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2025.3549366