TY - JOUR
T1 - Towards the Application of Neuromorphic Computing to Satellite Communications
AU - Ortiz, Flor
AU - Lagunas, Eva
AU - Martins, Wallace
AU - Dinh, Thinh
AU - Skatchkovsky, Nicolas
AU - Simeone, Osvaldo
AU - Rajendran, Bipin
AU - Navarro, Tomas
AU - Chatzinotas, Symeon
N1 - Funding Information:
This work has been supported by the European Space Agency (ESA) funded under Contract No. 4000137378/22/UK/ND - The Application of Neuromorphic Processors to Satcom Applications. Please note that the views of the authors of this paper do not necessarily reflect the views of ESA.
Publisher Copyright:
© 2022 Proceedings of the Design Society. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Artificial intelligence (AI) has recently received significant attention as a key enabler for future 5G-and-beyond terrestrial wireless networks. The applications of AI to satellite communications is also gaining momentum to realize a more autonomous operation with reduced requirements in terms of human intervention. The adoption of AI for satellite communications will set new requirements on computing processors, which will need to support large workloads as efficiently as possible under harsh environmental conditions. In this context, neuromorphic processing (NP) is emerging as a bio-inspired solution to address pattern recognition tasks involving multiple, possibly unstructured, temporal signals and/or requiring continual learning. The key merits of the technology are energy efficiency and capacity for on-device adaptation. In this paper, we highlight potential use cases and applications of NP to satellite communications. We also explore major technical challenges for the implementation of space-based NP focusing on the available NP chipsets.
AB - Artificial intelligence (AI) has recently received significant attention as a key enabler for future 5G-and-beyond terrestrial wireless networks. The applications of AI to satellite communications is also gaining momentum to realize a more autonomous operation with reduced requirements in terms of human intervention. The adoption of AI for satellite communications will set new requirements on computing processors, which will need to support large workloads as efficiently as possible under harsh environmental conditions. In this context, neuromorphic processing (NP) is emerging as a bio-inspired solution to address pattern recognition tasks involving multiple, possibly unstructured, temporal signals and/or requiring continual learning. The key merits of the technology are energy efficiency and capacity for on-device adaptation. In this paper, we highlight potential use cases and applications of NP to satellite communications. We also explore major technical challenges for the implementation of space-based NP focusing on the available NP chipsets.
KW - ARTIFICIAL INTELLIGENCE
KW - NEUROMORPHIC COMPUTING
KW - ONBOARD PROCESS
KW - SATELLITE COMMUNICATIONS
KW - SPIKING NEURAL NETWORK
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U2 - 10.1049/icp.2023.1367
DO - 10.1049/icp.2023.1367
M3 - Conference article
AN - SCOPUS:85149031255
SN - 2732-4494
VL - 2022
SP - 91
EP - 97
JO - IET Conference Proceedings
JF - IET Conference Proceedings
IS - 29
T2 - 39th International Communications Satellite Systems Conference, ICSSC 2022
Y2 - 18 October 2022 through 21 October 2022
ER -