DocumentCode :
2942420
Title :
Learning and Adaptation in Cognitive Radios Using Neural Networks
Author :
Baldo, N. ; Zorzi, M.
Author_Institution :
Padova Univ., Padova
fYear :
2008
fDate :
10-12 Jan. 2008
Firstpage :
998
Lastpage :
1003
Abstract :
The estimation of the communication performance achievable with respect to environmental factors and configuration parameters plays a key role in the optimization process performed by a Cognitive Radio according to the original definition by Mitola [1]. In this paper we propose the use of Multilayered Feedforward Neural Networks as an effective technique for real-time characterization of the communication performance which is based on measurements carried out by the device and therefore offers some interesting learning capabilities.
Keywords :
cognitive radio; environmental factors; feedforward neural nets; learning systems; cognitive radio; communication performance estimation; configuration parameter; environmental factor; learning capability; multilayered feedforward neural network; Chromium; Cognition; Cognitive radio; Environmental factors; Error analysis; Feedforward neural networks; Multi-layer neural network; Neural networks; Phase measurement; Throughput;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Communications and Networking Conference, 2008. CCNC 2008. 5th IEEE
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-1456-7
Electronic_ISBN :
978-1-4244-1457-4
Type :
conf
DOI :
10.1109/ccnc08.2007.229
Filename :
4446527
Link To Document :
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