Artificial Intelligence for Satellite Communication: A Survey
Gianluca Fontanesi, Flor Ortíz, Eva Lagunas, Luis Manuel Garcés-Socarrás, Víctor Monzón Baeza, Miguel Ángel Vázquez, Juan A. Vásquez-Peralvo, Mario Minardi, Vu Nguyen Ha, Puneeth Jubba Honnaiah, Clèment Lacoste, Youssouf Drif, Liz Martínez Marrero, Saed Daoud, Tedros Salih Abdu, Geoffrey Eappen, Junaid ur Rehman, Wallace A. Martins, Pol Henarejos, Hayder Al-Hraishawi, Juan Carlos Merlano Duncán, Thang X. Vu, Symeon Chatzinotas
Abstract
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.