DocumentCode
3094766
Title
Algorithm of digital modulation recognition based on support vector machines
Author
Wang, Lan-Xun ; Ren, Yu-jing ; Zhang, Rui-hua
Author_Institution
Coll. of Electron. & Inf. Eng., Hebei Univ., Baoding, China
Volume
2
fYear
2009
fDate
12-15 July 2009
Firstpage
980
Lastpage
983
Abstract
A new algorithm based on high order cumulants (HOC) and support vector machines (SVM) for modulation and recognition of digital communication signals is proposed. The new method can identify six digital modulation signals: 2ASK, 4ASK, 8ASK, 4PSK, 8PSK and 16QAM digital signals using fourth and sixth order cumulants of the signals as vectors and SVM based on binary tree as classifiers. The method uses new class distance as rules of constructing binary tree, which separates the furthest class from others first, so that the method can maintain high generalization ability. The computer simulation results justify the method´s validity.
Keywords
amplitude shift keying; digital communication; generalisation (artificial intelligence); higher order statistics; phase shift keying; quadrature amplitude modulation; signal classification; support vector machines; trees (mathematics); 16QAM digital signal; 2ASK digital signal; 4ASK digital signal; 4PSK digital signal; 8ASK digital signal; 8PSK digital signal; binary tree; digital communication signal recognition; digital modulation recognition; generalization ability; high order cumulants; signal classification; support vector machines; Binary trees; Classification tree analysis; Cybernetics; Digital modulation; Gaussian noise; Machine learning; Machine learning algorithms; Signal processing; Support vector machine classification; Support vector machines; Binary tree; High order cumulants; Modulation identification; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location
Baoding
Print_ISBN
978-1-4244-3702-3
Electronic_ISBN
978-1-4244-3703-0
Type
conf
DOI
10.1109/ICMLC.2009.5212366
Filename
5212366
Link To Document