Title :
A Modulation Type Recognition Method Using Wavelet Support Vector Machines
Author :
Liu, Hai-Yuan ; Sun, Jian-Cheng
Author_Institution :
Coll. of Inf. Tech. Sci., Nankai niversity, Tianjing, China
Abstract :
Soft defined radio is again the research issue because of cognitive radio, Modulation type recognition (MTR) is the key issue of the soft defined radio, in this paper, a new MTR method based on the wavelet support vector machine (WSVM) has been proposed, we derive the WSVM kernel function and utilize it to classify the modulation type, the results show when the SNR threshold for the modulation scheme classifier is approximately 10 dB. The correct recognizing rate exceeds 91%. It is shows that this method is better than the tradition method.
Keywords :
cognitive radio; modulation; pattern classification; signal classification; software radio; support vector machines; telecommunication computing; wavelet transforms; SNR threshold; Soft defined radio; WSVM kernel function; cognitive radio; modulation scheme classifier; modulation type recognition; wavelet support vector machine; Arithmetic; Cognitive radio; Educational institutions; Finance; Kernel; Lagrangian functions; Neural networks; Support vector machine classification; Support vector machines; Training data;
Conference_Titel :
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4129-7
Electronic_ISBN :
978-1-4244-4131-0
DOI :
10.1109/CISP.2009.5301396
