On the use of neural networks for flexible payload management in VHTS systems
Year: 2019
Type: conference-paper
Abstract: Very High Throughput Satellites (VHTS) surpass the capacity of traditional systems providing FSS and BSS (fixed and broadcasting satellite services, respectively) using multi-beam coverage. The objective of VHTS systems is to achieve a satellite capacity of 1 Terabit/s in the near future. These systems provide greater satellite capacity at a reduced cost per Gbps in orbit, but further optimization is needed to use the full capacity of the satellite over time as traffic demand is non-uniform and changing over time. In other words, VHTS systems require flexible payloads to meet changing traffic demands. This paper presents a solution for the automatic management of a flexible payload architecture using a Neural Network and considering resource allocation as a classification problem.
Source: Hispana
Authors: Flor Ortíz, Ramón Martínez Rodríguez‐Osorio, Miguel A. Salas‐Natera, Landeros-Ayala Salvador, Daniele Tarchi, Alessandro Vanelli‐Coralli
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Awards: G1185089041, G864758029
OpenAlex ID: W3121436391