Artificial Intelligence Satellite Telecommunication Testbed using Commercial Off-The-Shelf Chipsets

January 1, 2024·
Luis Manuel GARCES SOCARRAS
,
Amirhossein Nik
,
Flor de Guadalupe ORTIZ GOMEZ
,
Juan Andres VASQUEZ-PERALVO
,
Jorge Luis GONZALEZ RIOS
,
Mouhamad CHEHAITLY
,
Marcele OLIVEIRA KUHFUSS DE MENDONÇA
,
Eva Lagunas
,
Jan Thoemel
,
Sumit Kumar
,
Jorge Querol
· 1 min read
Abstract
The Artificial Intelligence Satellite Telecommunications Testbed (AISTT), part of the ESA project SPAICE, is focused on the transformation of the satellite payload by using artificial intelligence (AI) and machine learning (ML) methodologies over available commercial off-the-shelf (COTS) AI-capable chips for onboard processing. The objectives include validating artificial intelligence-driven SATCOM scenarios such as interference detection, spectrum sharing, radio resource management, decoding, and beamforming. The study highlights hardware selection and payload architecture. Preliminary results show that ML models significantly improve signal quality, spectral efficiency, and throughput compared to conventional payload. Moreover, the testbed aims to evaluate the performance and the use of AI-capable COTS chips in onboard SATCOM contexts.
Type
Publication
AI in and for Space (ESA SPAICE 2024)
publication

Abstract & Overview

The Artificial Intelligence Satellite Telecommunications Testbed (AISTT), part of the ESA project SPAICE, is focused on the transformation of the satellite payload by using artificial intelligence (AI) and machine learning (ML) methodologies over available commercial off-the-shelf (COTS) AI-capable chips for onboard processing. The objectives include validating artificial intelligence-driven SATCOM scenarios such as interference detection, spectrum sharing, radio resource management, decoding, and beamforming. The study highlights hardware selection and payload architecture. Preliminary results show that ML models significantly improve signal quality, spectral efficiency, and throughput compared to conventional payload. Moreover, the testbed aims to evaluate the performance and the use of AI-capable COTS chips in onboard SATCOM contexts.

Publication Metadata

  • Authors: Luis Manuel GARCES SOCARRAS, Amirhossein Nik, Flor de Guadalupe ORTIZ GOMEZ, Juan Andres VASQUEZ-PERALVO, Jorge Luis GONZALEZ RIOS, Mouhamad CHEHAITLY, Marcele OLIVEIRA KUHFUSS DE MENDONÇA, Eva Lagunas, Jan Thoemel, Sumit Kumar, Jorge Querol
  • Venue: AI in and for Space (ESA SPAICE 2024) (2024)
  • Research Areas: Satellite Communications, SDR & Experimental Testbeds
  • DOI: 10.5281/zenodo.13885550
  • Open Access Repository: ORBiLu – University of Luxembourg
Satellite Communications SDR & Experimental Testbeds