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Título:	A novel framework for dynamic spectrum management in multiCell OFDMA networks based on reinforcement learning
Autor/a:	Bernardo Álvarez, Francisco; Agustí Comes, Ramon; Pérez Romero, Jordi; Sallent Roig, José Oriol
Otros autores:	Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. GRCM - Grup de Recerca en Comunicacions Mòbils
Abstract:	In this work the feasibility of Reinforcement Learning (RL) for Dynamic Spectrum Management (DSM) in the context of next generation multicell Orthogonal Frequency Division Multiple Access (OFDMA) networks is studied. An RL-based algorithm is proposed and it is shown that the proposed scheme is able to dynamically find spectrum assignments per cell depending on the spatial distribution of the users over the scenario. In addition the proposed scheme is compared with other fixed and dynamic spectrum strategies showing the best tradeoff between spectral efficiency and Quality-of-Service (QoS).
Materia(s):	-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació -Reinforcement learning -Signal theory (Telecommunication) -Quality of Service -Orthogonal frequency division multiplexing -Senyal, Teoria del (Telecomunicació)
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Tipo de documento:	Artículo - Versión publicada Objeto de conferencia
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