Artificial Intelligence for Satellite Communication and Non-Terrestrial Networks: A Survey

no code implementations • 25 Apr 2023 • G. Fontanesi, F. Ortíz, E. Lagunas, V. Monzon Baeza, M. Á. Vázquez, J. A. Vásquez-Peralvo, M. Minardi, H. N. Vu, P. J. Honnaiah, C. Lacoste, Y. Drif, T. S. Abdu, G. Eappen, J. Rehman, L. M. Garcés-Socorrás, W. A. Martins, P. Henarejos, H. Al-Hraishawi, J. C. Merlano Duncan, T. X. Vu, S. Chatzinotas

We first present a comprehensive list of use cases, the relative challenges and the main AI tools capable of addressing those challenges.

NB-IoT via LEO satellites: An efficient resource allocation strategy for uplink data transmission

no code implementations • 2 Jul 2021 • O. Kodheli, N. Maturo, S. Chatzinotas, S. Andrenacci, F. Zimmer

Scheduling at the same radio frame users that overcome a certain distance would violate the differential Doppler limit supported by the NB-IoT standard.

Scheduling

Random Access Procedure over Non-Terrestrial Networks: From Theory to Practice

no code implementations • 29 Jun 2021 • O. Kodheli, A. Astro, J. Querol, M. Gholamian, S. Kumar, N. Maturo, S. Chatzinotas

The laboratory test-bed built in this work, not only enables us to validate various solutions, but also plays a crucial role in identifying novel challenges not previously treated in the literature.

Deep Channel Learning For Large Intelligent Surfaces Aided mm-Wave Massive MIMO Systems

1 code implementation • 29 Jan 2020 • Ahmet M. Elbir, A Papazafeiropoulos, P. Kourtessis, S. Chatzinotas

This letter presents the first work introducing a deep learning (DL) framework for channel estimation in large intelligent surface (LIS) assisted massive MIMO (multiple-input multiple-output) systems.