DocumentCode :
1941429
Title :
Neural Networks Mode Classification based on Frequency Distribution Features
Author :
Cattoni, Andrea F. ; Ottonello, Marina ; Raffetto, Mirco ; Regazzoni, Carlo S.
Author_Institution :
Department of Biophysical and Electronic Engineering (DIBE), University of Genova, Genova, Italy, Email: cattoni@dibe.unige.it
fYear :
2007
fDate :
1-3 Aug. 2007
Firstpage :
251
Lastpage :
257
Abstract :
The growing number of new emerging wireless standards is creating regulatory problems in allocating the unlicensed frequencies. A possible solution for increasing the frequency re-usage within the framework of info-mobility cellular systems is the joint exploitation of Smart Antennas and Cognitive Radio. In the paper a Mode Identification algorithm, based on frequency distribution features and multiple neural network classifiers, for a Cognitive Base Transceiver Station is presented. Simulated results, obtained in a simplified framework, will prove the effectiveness of the proposed approach.
Keywords :
Chromium; Cognitive radio; FCC; Frequency; Multiaccess communication; Neural networks; Radio spectrum management; Radiofrequency identification; Transceivers; Vehicle dynamics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Radio Oriented Wireless Networks and Communications, 2007. CrownCom 2007. 2nd International Conference on
Conference_Location :
Orlando, FL, USA
Print_ISBN :
978-1-4244-0814-6
Electronic_ISBN :
978-1-4244-0815-3
Type :
conf
DOI :
10.1109/CROWNCOM.2007.4549806
Filename :
4549806
Link To Document :
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