Title
Distributed spectrum management based on reinforcement learning
Abstract
Abstract—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,spec- tral 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. Index Terms—Spectrum Management, Reinforcement Learn- ing, Cognitive Radio, Self-organization, Autonomic Systems, OFDMA.
Year
DOI
Venue
2009
10.1109/CROWNCOM.2009.5189161
Hannover
Keywords
Field
DocType
ofdm modulation,cellular radio,frequency division multiple access,learning (artificial intelligence),quality of service,radio access networks,radio spectrum management,spectral analysis,telecommunication computing,telecommunication network management,cellular radio access network management,distributed spectrum management,fixed frequency planning schemes,machine learning,multicell ofdma radio access network,quality-of-service,reinforcement learning,spectral efficiency,autonomic systems,cognitive radio,ofdma,self-organization,spectrum management,cognitive radio network,interference,signal to noise ratio,throughput,learning artificial intelligence,bandwidth,planning,downlink,radio access network,self organization,spectrum
Spectrum management,Computer science,Computer network,Bandwidth (signal processing),Spectral efficiency,Frequency-division multiple access,Radio access network,Access network,Reinforcement learning,Cognitive radio
Conference
ISBN
Citations 
PageRank 
978-1-4244-3424-4
4
0.41
References 
Authors
6
4
Name
Order
Citations
PageRank
Francisco Bernardo1636.67
Ramon Agust240.41
Jordi Pérez-Romero3184.13
Oriol Sallent4726.14