Descripción del proyecto
Una herramienta inteligente para los satélites
Una nueva generación de satélites totalmente flexibles se está haciendo con el mercado espacial. A fin de controlar las cargas útiles flexibles de los satélites y sus equivalentes tradicionales configurables, el proyecto financiado con fondos europeos ATRIA creará una herramienta genérica e inteligente llamada AI-PCS. Las técnicas de inteligencia artificial (IA, o AI por sus siglas en inglés) dotarán a la herramienta de la inteligencia necesaria para decidir de manera autónoma la configuración óptima de los recursos satelitales disponibles para las solicitudes de servicios a demanda. El procesador digital transparente constituirá el núcleo de estas cargas útiles digitales, a las que proporcionará nuevas capacidades dentro de los paradigmas de red de la última revolución 5G, que no se habrían podido lograr con cargas útiles analógicas tradicionales, como el ancho de banda adaptativo y la asignación de energía, y flexibilidad en conectividad y cobertura.
Objetivo
A new generation of completely flexible satellites in terms of mission definition is currently appearing in the space segment as a response to the 5G revolution, resulting in an unprecedented integration of the satellite services with the terrestrial deployments. In this context, the Digital Transparent Processor (DTP) is aimed to constitute the core of these digital payload, providing them with new capabilities unthinkable to achieve with the traditional analogue ones, such as adaptive bandwidth (BW) and power allocation, or flexibility in the connectivity and coverage.
As a consequence, the flexibility offered by these kind of satellites leads to the increased complexity in their management. Then, the optimum reconfiguration of these complex payloads to fulfil the users requirements is no longer an achievable task for a payload engineer due to the real-time constraints and the number of possibilities. To solve this, these satellites require new and intelligent tools capable of optimally allocating the satellite resources, while monitoring the interferences in such a dynamic scenario.
In this point, Artificial Intelligence/Machine Learning (AI/ML) algorithms appear to substitute the operator decisions and manual operations while configuring the payloads. In atria project, these algorithms will compose an AI/ML module in a Payload optimization Control System (AI-PCS). The algorithms are to be trained with both real data sets of former manual operations and synthetic data. Also, the algorithms will receive information from external services to provide them with inputs regarding meteorology, traffic, availability, etc. in order to achieve the optimum decisions.
AI-PCS is to be validated using both a flexible payload emulator and real satellite environments. AI-PCS is aimed to be a generic tool, transparent to the payload, providing the satcom operators with added value and turning it into a cost-effective solution for the future of the ground segment.
Ámbito científico
- natural sciencesearth and related environmental sciencesatmospheric sciencesmeteorology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationstelecommunications networksmobile network5G
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcontrol systems
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Palabras clave
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SPACE-2020
Régimen de financiación
RIA - Research and Innovation actionCoordinador
28760 Tres Cantos
España