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Distributed Machine Learning for UAV Swarms: Computing, Sensing, and Semantics

delete2024-03-01
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OA
AI
Y
Yahao Ding *
杨朝晖 cover
杨朝晖 (Zhaohui Yang)
Q
Quoc‐Viet Pham
Y
Ye Hu
张
张朝阳 (Zhaoyang Zhang)
M
Mohammad Shikh‐Bahaei
DOI:10.1109/JIOT.2023.3341307delete
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Abstract

Abstract

En 中文
The unmanned aerial vehicle (UAV) swarms have shown great potential to serve next-generation communication networks with their extraordinary flexibility, affordability, and the ability to collaboratively and autonomously provide Line-of-Sight (LoS) services. However, autonomous collaboration under wireless dynamics is challenging. Distributed learning (DL) provides a chance for the UAV swarms to operate intelligently under sophisticated dynamics, such that they can be applied to wireless communication service scenarios, as well as applications including multidirectional remote surveillance, and target tracking. In this survey, we first introduce several popular DL frameworks that are capable of managing a UAV swarm, these include federated learning (FL), multiagent reinforcement learning (MARL), distributed inference (DI), and split learning (SL). We also present a comprehensive overview of how these DL frameworks manage UAV swarms in regard to trajectory design, power control, wireless resource allocation, user assignment, perception, and satellite-drone integration. Then, we present several state-of-the-art applications of UAV swarms in wireless communication systems, such as reconfigurable intelligent surfaces (RISs), virtual reality (VR), and semantic communications (SemComs), and discuss the problems and challenges that DL-enabled UAV swarms can solve in these applications. Finally, we describe open problems of using DL in UAV swarms and future research directions of DL-enabled UAV swarms. In summary, this survey provides a concise survey of various DL applications for UAV swarms in extensive scenarios.
Keywords:
Distributed inference (DI)
distributed learning (DL) satellite communications
semantic communications
split learning (SL)
unmanned aerial vehicle (UAV) swarms

Journal

IEEE Internet of Things Journal cover
IEEE Internet of Things Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W

Organization

T
Trinity College Dublin
Scholars:
2.4W
Papers: 1.9W
Citations: 2.7W
U
university of london
Scholars:
21.5W
Papers: 19.7W
Citations: 305
U
university of miami
Scholars:
3.4W
Papers: 2.6W
Citations: 32
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Cited Papers

Cited Papers

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PREAI
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PREAI
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UAV Swarm-Enabled Aerial Reconfigurable Intelligent Surface (SARIS)
err2021-10-01
err39
PREAI
errShang, Bodong; Shafin, Rubayet; Liu, Lingjia
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A Survey on Machine-Learning Techniques for UAV-Based Communications
errSENSORS
IF3.5
err2019-11-26
err204
errOAAI
errBithas, Petros S.; Michailidis, Emmanouel T.; Nomikos, Nikolaos; Vouyioukas, Demosthenes; Kanatas, Athanasios G.
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Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing
err2019-08-01
err1.2K
errOAAI
errZhou, Zhi; Chen, Xu; Li, En; Zeng, Liekang; Luo, Ke; Zhang, Junshan
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