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

Volume

4

fYear

2009

fDate

8-9 Aug. 2009

Firstpage

271

Lastpage

274

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on

Conference_Location

Sanya

Print_ISBN

978-1-4244-4247-8

Type

conf

DOI

10.1109/CCCM.2009.5267733

Filename

5267733