Title :
Recognition of digital modulation signals based on high order cumulants and support vector machines
Author :
Wang, Lan-Xun ; Ren, Yu-jing
Author_Institution :
Coll. of Electron. & Inf. Eng., Hebei Univ., Baoding, China
Abstract :
The paper presents a new algorithm of digital modulation signals based on high order cumulants (HOC) and support vector machines (SVM). The parameters which are picked up from the signals´ fourth order and sixth order cumulants are used as the classification feature vectors. Using SVM based on binary tree as classifiers, recognition of the 2ASK, 4ASK, QPSK, 2FSK and 4FSK signals is efficient. The computer simulation results justify that the success rate is over 97.5% at SNR = 10 dB.
Keywords :
amplitude shift keying; frequency shift keying; higher order statistics; quadrature phase shift keying; signal classification; support vector machines; tree data structures; ASK; FSK; HOC; QPSK; SVM; binary tree; classification feature vector; digital modulation signal recognition; high order cumulant; support vector machine; Communication system control; Computer science; Crawlers; Digital modulation; Frequency; Functional analysis; Search engines; Support vector machines; Technology management; Web pages; Binary tree; High order cumulants; Modulation identification; Support vector machines;
Conference_Titel :
Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-4247-8
DOI :
10.1109/CCCM.2009.5267733
