DocumentCode :
3034899
Title :
Performance optimization of Automatic Modulation Classification for different signal and channel types
Author :
Sichelschmidt, S. ; Bruckmann, Dieter
Author_Institution :
Fac. of Electr., Inf. & Media Eng., Univ. of Wuppertal, Wuppertal, Germany
fYear :
2012
fDate :
11-16 Nov. 2012
Firstpage :
1
Lastpage :
4
Abstract :
The introduction of Cognitive Radio (CR) in mobile communication systems led to numerous opportunities to enhance spectral accessibility through Dynamic Spectrum Access (DSA). Automated Modulation Classification (AMC) confirms spectral white spaces and helps separating primary from secondary users. A significant number of different approaches have been presented and evaluated during the last years. Algorithms are generally developed and optimized for certain lengths of signal and transmission channels. The target for AMC optimization is to minimize the time interval required for classification and to make the system robust against different sources of distortion. The former coheres with the minimum signal length that is needed for the classifier to work, the latter can be simulated with different communication channel models. Therefore in this paper results are presented, which reflect the performance of AMC as a function of the signal length and for different modulation schemes and channel types.
Keywords :
cognitive radio; mobile communication; modulation; wireless channels; AMC optimization; automatic modulation classification; channel types; cognitive radio; communication channel models; dynamic spectrum access; mobile communication; performance optimization; signal types; Bandwidth; Classification algorithms; Cognitive radio; Interference; Modulation; Noise; White spaces;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Information Technology and Systems (ICWITS), 2012 IEEE International Conference on
Conference_Location :
Maui, HI
Print_ISBN :
978-1-4673-0947-9
Type :
conf
DOI :
10.1109/ICWITS.2012.6417709
Filename :
6417709
Link To Document :
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