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Título del libro: 2020 10th Advanced Satellite Multimedia Systems Conference And The 16th Signal Processing For Space Communications Workshop, Asms/spsc 2020
Título del capítulo: Supervised Machine Learning for Power and Bandwidth Management in VHTS Systems

Autores UNAM:
SALVADOR LANDEROS AYALA;
Autores externos:

Idioma:

Año de publicación:
2020
Palabras clave:

Multimedia signal processing; Multimedia systems; Satellites; Supervised learning; Bandwidth management; Classification algorithm; Flexible payloads; High throughput; Resource management; Service area; Supervised machine learning; Traffic demands; Learning systems


Resumen:

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. © 2020 IEEE.


Entidades citadas de la UNAM: