Reference : Onboard Processing in Satellite Communications Using AI Accelerators
Scientific journals : Article
Engineering, computing & technology : Electrical & electronics engineering
Security, Reliability and Trust
http://hdl.handle.net/10993/54478
Onboard Processing in Satellite Communications Using AI Accelerators
English
Ortiz Gomez, Flor de Guadalupe mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Monzon Baeza, Victor mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Garces Socarras, Luis Manuel mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Vasquez-Peralvo, Juan Andres mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Gonzalez Rios, Jorge Luis mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Fontanesi, Gianluca mailto [Nokia]
Lagunas, Eva mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Querol, Jorge mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Chatzinotas, Symeon mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
13-Jan-2023
Aerospace
MDPI
10
2
On-Board Systems Design for Aerospace Vehicles
Yes
International
2226-4310
Basel
Switzerland
[en] satellite communications ; artificial intelligence ; onboard process
[en] Satellite communication (SatCom) systems operations centers currently require high human intervention, which leads to increased operational expenditure (OPEX) and implicit latency in human action that causes degradation in the quality of service (QoS). Consequently, new SatCom systems leverage artificial intelligence and machine learning (AI/ML) to provide higher levels of autonomy and control. Onboard processing for advanced AI/ML algorithms, especially deep learning algorithms, requires an improvement of several magnitudes in computing power compared to what is available with legacy, radiation-tolerant, space-grade processors in space vehicles today. The next generation of onboard AI/ML space processors will likely include a diverse landscape of heterogeneous systems. This manuscript identifies the key requirements for onboard AI/ML processing, defines a reference architecture, evaluates different use case scenarios, and assesses the hardware landscape for current and next-generation space AI processors.
University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >
European Space Agency - ESA ; Fonds National de la Recherche - FnR
SmartSpace and SPAICE
Researchers ; Professionals ; Students ; General public
http://hdl.handle.net/10993/54478
10.3390/aerospace10020101
https://www.mdpi.com/2226-4310/10/2/101
FnR ; FNR16193290 > Eva Lagunas > SmartSpace > Leveraging Artificial Intelligence To Empower The Next Generation Of Satellite Communications > 01/04/2022 > 31/03/2025 > 2021

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