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

Author
Bernardo, F.; Agusti, R.; Perez-Romero, J.; Sallent, J.
Type of activity
Journal article
Journal
IEEE transactions on systems man and cybernetics Part C-applications and reviews
Date of publication
2010-07
Volume
40
Number
4
First page
477
Last page
484
DOI
https://doi.org/10.1109/TSMCC.2010.2041230 Open in new window
Repository
http://hdl.handle.net/2117/8321 Open in new window
URL
http://ieeexplorepreview.ieee.org/xpl/freeabs_all.jsp?arnumber=5415613&abstractAccess=no&userType= Open in new window
Abstract
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...
Citation
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.
Group of research
CCABA - Advanced Broadband Communications Center
GRCM - Mobile Communication Reserach Group

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