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An application of reinforcement learning for efficient spectrum usage in next-generation mobile cellular networks

Autor
Bernardo, F.; Agusti, R.; Perez-Romero, J.; Sallent, J.
Tipus d'activitat
Article en revista
Revista
IEEE transactions on systems man and cybernetics Part C-applications and reviews
Data de publicació
2010-07
Volum
40
Número
4
Pàgina inicial
477
Pàgina final
484
DOI
https://doi.org/10.1109/TSMCC.2010.2041230 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/8321 Obrir en finestra nova
URL
http://ieeexplorepreview.ieee.org/xpl/freeabs_all.jsp?arnumber=5415613&abstractAccess=no&userType= Obrir en finestra nova
Resum
This paper proposes reinforcement learning as a foundational stone of a framework for efficient spectrum usage in the context of nextgeneration mobile cellular networks. The objective of the framework is to efficiently use the spectrum in a cellular orthogonal frequency-division multiple access network while unnecessary spectrum is released for secondary spectrum usage within a private commons spectrum accessmodel. Numerical results show that the proposed framework obtains the best performance c...
Citació
Bernardo, F. [et al.]. An application of reinforcement learning for efficient spectrum usage in next-generation mobile cellular networks. "IEEE transactions on systems man and cybernetics Part C-applications and reviews", Juliol 2010, vol. 40, núm. 4, p. 477-484.
Grup de recerca
CCABA - Centre de Comunicacions Avançades de Banda Ampla
GRCM - Grup de Recerca en Comunicacions Mòbils

Participants

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