Artificial Intelligence for Satellite Communication: A Survey

Artificial Intelligence; Machine Learning; Non-terrestrial Networks; Satellite Communication; Artificial intelligence learning; Different layers; Growing demand; Machine learning technology; Machine-learning; Non-terrestrial network; Performance efficiency; Satellite communications; Satellite communications system; Terrestrial networks; Electrical and Electronic Engineering

Résumé :

[en] This paper provides a comprehensive survey on the application and development of Artificial Intelligence (AI) and Machine Learning (ML) in satellite communication (SATCOM). It explores the increasing integration of AI/ML technologies in SATCOM systems, highlighting their potential to enhance performance, efficiency, and adaptability in response to growing demands for connectivity and data processing. The survey categorizes various use cases across different layers of satellite networks, detailing conventional solutions and the advantages of employing AI/ML techniques. It discusses the challenges associated with onboard processing, including hardware constraints, radiation tolerance, and the need for efficient resource management. Furthermore, the document examines the role of neuromorphic computing and COTS (Commercial Off-The-Shelf) devices in facilitating AI applications in space environments. Finally, we discuss the long-term developments of AI in the SATCOM sector and potential research directions. Overall, the survey emphasizes the transformative impact of AI/ML on the future of SATCOM, paving the way for innovative solutions in next-generation satellite networks.

Disciplines :

Sciences informatiques

Auteur, co-auteur :

Fontanesi, Gianluca ; Interdisciplinary Centre for Security, Reliability, and Trust (SnT), Luxembourg ; Nokia Bell Labs, Stuttgart, Germany

ORTIZ GOMEZ, Flor de Guadalupe ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom

LAGUNAS, Eva ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom ; Interdisciplinary Centre for Security, Reliability, and Trust (SnT), Luxembourg

GARCES SOCARRAS, Luis Manuel ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom

Baeza, Victor Monzon ; Interdisciplinary Centre for Security, Reliability, and Trust (SnT), Luxembourg

Vazquez, Miguel Angel ; Centre Tecnologic de les Telecommunicacions de Catalunya, Barcelona, Spain

VASQUEZ-PERALVO, Juan Andres ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom ; Interdisciplinary Centre for Security, Reliability, and Trust (SnT), Luxembourg

Minardi, Mario ; Interdisciplinary Centre for Security, Reliability, and Trust (SnT), Luxembourg

HA, Vu Nguyen ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom

Honnaiah, Puneeth Jubba ; Interdisciplinary Centre for Security, Reliability, and Trust (SnT), Luxembourg

Plus d'auteurs (13 en +)

Co-auteurs externes :

yes

Langue du document :

Anglais

Titre :

Artificial Intelligence for Satellite Communication: A Survey

Date de publication/diffusion :

13 février 2025

Titre du périodique :

IEEE Communications Surveys and Tutorials

eISSN :

1553-877X

Maison d'édition :

Institute of Electrical and Electronics Engineers Inc.

Pagination :

1-1

Peer reviewed :

Peer reviewed vérifié par ORBi

URL complémentaire :

http://xplorestaging.ieee.org/ielx8/9739/5451756/10886927.pdf?arnumber=10886927

Organisme subsidiant :

Luxembourg National Research Fund
project SOFIA
Catalan government
HORIZON.1.2 Marie Curie Actions Programme

Disponible sur ORBilu :

depuis le 12 juillet 2025

Statistiques

Nombre de vues

181 (dont 7 Unilu)

Nombre de téléchargements

1500 (dont 12 Unilu)

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citations Scopus^®
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citations OpenAlex

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