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Títol: Distributed spectrum management based on reinforcement learning
Autor: Bernardo Álvarez, Francisco
Agustí Comes, Ramon
Pérez Romero, Jordi
Sallent Roig, José Oriol
Altres autors/autores: Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. GRCM - Grup de Recerca en Comunicacions Mòbils
Matèries: Àrees temàtiques de la UPC::Enginyeria electrònica i telecomunicacions
Signal theory (Telecommunication)
Autonomic systems
Senyal, Teoria del (Telecomunicació)
Tipus de document: Conference report
Descripció: This paper presents a novel distributed framework to decide the spectrum assignment in a primary cellular radio access network. The distributed nature of the framework allows each cell to autonomously decide (by means of machine learning procedures) the best frequencies to use in order to maximize spectral efficiency, preserve quality-of-service, and generate spectrum gaps, so that secondary cognitive radio networks can improve overall spectrum usage. The proposed distributed framework has been validated over a downlink multicell OFDMA radio access network, showing comparable performance results with respect to its centralized counterpart and superior performance with respect to fixed frequency planning schemes.
Postprint (published version)
Altres identificadors i accés: Bernardo, F. [et al.]. Distributed spectrum management based on reinforcement learning. A: International Conference on Cognitive Radio Oriented Wireless Networks and Communications. "4th International Conference on Cognitive Radio Oriented Wireless Networks and Communications". Hannover: 2009, p. 1-6.
978-1-4244-3423-7
http://hdl.handle.net/2117/8900
10.1109/CROWNCOM.2009.5189161
Disponible al dipòsit:E-prints UPC
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