Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Wireless Communications & Mobile Computing - Cognitive Radio, Software Defined Radio And Adaptive Wireless Systems
Dynamic spectrum assignment in multicell OFDMA networks enabling a secondary spectrum usage
Wireless Communications & Mobile Computing - Cognitive Radio and Advanced Spectrum Management
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency
IEEE Communications Magazine
Self-organization in communication networks: principles and design paradigms
IEEE Communications Magazine
Transmit power adaptation for multiuser OFDM systems
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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This paper proposes a Self-organized Spectrum Assignment strategy in the context of next generation multicell Orthogonal Frequency Division Multiple Access networks. The proposed strategy is able to dynamically find spectrum assignments per cell depending on the spatial distribution of the users over the scenario, opening new spectrum access opportunities for secondary spectrum usage. Reinforcement Learning methodology has been employed to implement the strategy, which compared with other fixed and dynamic spectrum assignment strategies shows the best tradeoff between spectral efficiency and Quality-of-Service while releases spectrum in large geographical areas.