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EnglishIn the near future, Very High Throughput Satellite (VHTS) systems are expected to have a high increase in traffic demand. However, this increase will not be uniform over the service area and will be also dynamic. A solution to this problem is given by flexible payload architectures; however, they require that resource management is performed autonomously and with low latency. In this paper we propose the use of Supervised Machine Learning, in particular a Classification algorithm, to manage the resources available in flexible payload architectures. A use case is presented to demonstrate the effectiveness of the proposed approach and a discussion is made on all the challenges that are presented.
| Titolo: | Supervised Machine Learning for Power and Bandwidth Management in VHTS Systems | |
| Autore/i: | Ortiz Gomez, Flor G.; Tarchi, Daniele; Rodriguez-Osorio, Ramon Martinez; Vanelli Coralli, Alessandro; Salas-Natera, Miguel A.; Landeros-Ayala, Salvador | |
| Autore/i Unibo: | ||
| Anno: | 2020 | |
| Serie: | ||
| Titolo del libro: | 2020 10th Advanced Satellite Multimedia Systems Conference and the 16th Signal Processing for Space Communications Workshop (ASMS/SPSC) | |
| Pagina iniziale: | 1 | |
| Pagina finale: | 7 | |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1109/ASMS/SPSC48805.2020.9268790 | |
| Abstract: | In the near future, Very High Throughput Satellite (VHTS) systems are expected to have a high increase in traffic demand. However, this increase will not be uniform over the service area and will be also dynamic. A solution to this problem is given by flexible payload architectures; however, they require that resource management is performed autonomously and with low latency. In this paper we propose the use of Supervised Machine Learning, in particular a Classification algorithm, to manage the resources available in flexible payload architectures. A use case is presented to demonstrate the effectiveness of the proposed approach and a discussion is made on all the challenges that are presented. | |
| Data stato definitivo: | 8-gen-2021 | |
| Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |
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