Artificial intelligence for satellite communication and non-terrestrial networks: A survey

G Fontanesi, F Ortíz, E Lagunas, VM Baeza… - arXiv preprint arXiv …, 2023 - arxiv.org
This paper surveys the application and development of Artificial Intelligence (AI) in Satellite
Communication (SatCom) and Non-Terrestrial Networks (NTN). We first present a …

Machine Learning and Deep Learning powered satellite communications: Enabling technologies, applications, open challenges, and future research directions

A Bhattacharyya, SM Nambiar, R Ojha… - … Journal of Satellite …, 2023 - Wiley Online Library
The recent wave of creating an interconnected world through satellites has renewed interest
in satellite communications. Private and government‐funded space agencies are making …

Machine learning for radio resource management in multibeam GEO satellite systems

FG Ortiz-Gomez, L Lei, E Lagunas, R Martinez… - Electronics, 2022 - mdpi.com
Satellite communications (SatComs) systems are facing a massive increase in traffic
demand. However, this increase is not uniform across the service area due to the uneven …

Precoding for high throughput satellite communication systems: A survey

M Khammassi, A Kammoun… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
With the expanding demand for high data rates and extensive coverage, high throughput
satellite (HTS) communication systems are emerging as a key technology for future …

Unsupervised learning for user scheduling in multibeam precoded geo satellite systems

F Ortiz, E Lagunas, S Chatzinotas - 2022 joint European …, 2022 - ieeexplore.ieee.org
Future generation SatCom multibeam architectures will extensively exploit full-frequency
reuse schemes together with interference management techniques, such as precoding, to …

An auction approach to aircraft bandwidth scheduling in non-terrestrial networks

X Li, K Mo, Y Hou, Z Li, H Xu, CJ Xue - Computer Networks, 2024 - Elsevier
Internet Service has witnessed only limited deployment on commercial flights, where
network infrastructure is lacking and subscription fees are high. It is natural to design an …

Harnessing Supervised Learning for Adaptive Beamforming in Multibeam Satellite Systems

F Ortiz, JA Vasquez-Peralvo, J Querol… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
In today's ever-connected world, the demand for fast and widespread connectivity is
insatiable, making multibeam satellite systems an indispensable pillar of modern …

Flexible Payload Configuration for Satellites using Machine Learning

MOK Mendonça, FG Ortiz-Gomez… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
Satellite communications, essential for modern connectivity, extend access to maritime,
aeronautical, and remote areas where terrestrial networks are unfeasible. Current GEO …

Learning to Optimize Satellite Flexible Payloads

MÁ Vázquez, P Henarejos… - 2022 30th European …, 2022 - ieeexplore.ieee.org
This paper proposes an optimization technique for satellite systems with flexible payloads.
Unlike current satellites whose per-beam capacity is fixed, forthcoming payloads will have …

[PDF][PDF] A review of the applications of artificial intelligence in improving the performance of integrated space-air and ground networks

P Hajipour, R Karimzadeh Baee, H Zarrabi… - Journal of Space …, 2023 - jsstpub.com
According to the technical specifications of the future generations of telecommunication,
which should provide new services, the use of hybrid networks space-air-ground is …