Distributed spectrum management based on reinforcement learning
Tipo de documentoTexto en actas de congreso
Fecha de publicación2009
Condiciones de accesoAcceso abierto
Proyecto de la Comisión EuropeaE3 - End-to-End Efficiency (E3) (EC-FP7-216248)
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.
CitaciónBernardo, 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.