Automatic digital modulation identification basing on decision method and cumulants

Author

Li, Ji ; He, Chen ; Chen, Jie

Author_Institution

Dept. of Electron. Eng., Shanghai Jiao Tong Univ., China

fYear

2005

fDate

28-30 May 2005

Firstpage

264

Lastpage

267

Abstract

Automatic modulation identification through digital signal processing has many applications in wireless communication systems. But most of signal classification methods can only recognize a few kinds of signals and they request SNR should be beyond 10 dB. Based on the method presented by Asoke K. Nandi and E. E. Azzouz, this paper adds some high-order cumulants, and uses the RBF neural network to classify 2ASK, 4ASK, 8ASK, 2PSK, 4PSK, 8PSK, 2FSK, 4FSK, 8FSK, 16QAM, 64QAM, these eleven kinds of digital modulated signals in low SNR to -5 dB. The simulation results indicate that this improved method can get good results.

Keywords

amplitude shift keying; frequency shift keying; higher order statistics; phase shift keying; quadrature amplitude modulation; radial basis function networks; radiocommunication; signal classification; 16QAM; 2ASK; 2FSK; 2PSK; 4ASK; 4FSK; 4PSK; 64QAM; 8ASK; 8FSK; 8PSK; RBF neural network; SNR; automatic digital modulation identification; decision method; digital modulated signals; digital signal processing; high-order cumulants; signal classification methods; wireless communication systems; Bandwidth; Digital modulation; Digital signal processing; Frequency; Helium; Neural networks; Quadrature amplitude modulation; Signal processing; Software radio; Wireless communication;

fLanguage

English

Publisher

ieee

Conference_Titel

VLSI Design and Video Technology, 2005. Proceedings of 2005 IEEE International Workshop on

Print_ISBN

0-7803-9005-9

Type

conf

DOI

10.1109/IWVDVT.2005.1504601

Filename

1504601