A Transfer Reinforcement Learning Approach for Capacity Sharing in Beyond 5G Networks

A Transfer Reinforcement Learning Approach for Capacity Sharing in Beyond 5G Networks

The use of Reinforcement Learning (RL) techniques has been widely addressed in the literature to cope with capacity sharing in 5G Radio Access Network (RAN) slicing. These algorithms consider a training process to learn an optimal capacity sharing decision-making policy, which is later applied to th...

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Detalles Bibliográficos
Autores principales: Irene Vilà, Jordi Pérez-Romero, Oriol Sallent
Formato: Artículo
Lenguaje:English
Publicado: MDPI AG 2024-11-01
Colección:Future Internet
Materias:
RAN slicing
capacity sharing
reinforcement learning
transfer learning
transfer reinforcement learning
Acceso en línea:https://www.mdpi.com/1999-5903/16/12/434

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https://www.mdpi.com/1999-5903/16/12/434

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