Cyclic spectral features based modulation recognition

Author

Mingquan, Lu ; Xianci, Xiao ; Leming, Li

Author_Institution

Dept. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China

Volume

2

fYear

1996

fDate

5-7 May 1996

Firstpage

792

Abstract

Modulation recognition of an intercepted communication signal is a fundamental problem of electromagnetic signal monitoring task arising in many fields, such as electronic surveillance and broadcasting control. A cyclic spectral features based neural network modulation recognition method is proposed. Because of the use of cyclic spectral features and the application of neural network classifier, the proposed method can efficiently recognize almost all currently used modulation types. Some computer simulation results are also reported

Keywords

broadcasting; feature extraction; modulation; neural nets; spectral analysis; surveillance; broadcasting control; computer simulation results; cyclic spectral features; electromagnetic signal monitoring; electronic surveillance; intercepted communication signal; modulation recognition; neural network classifier; neural network modulation recognition method; Application software; Binary phase shift keying; Broadcasting; Classification algorithms; Communication system control; Computer simulation; Electromagnetic fields; Feature extraction; Frequency estimation; Monitoring; Neural networks; Phase modulation; Phase shift keying; Random sequences; Sampling methods; Spectral analysis; Surveillance;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Technology Proceedings, 1996. ICCT'96., 1996 International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-2916-3

Type

conf

DOI

10.1109/ICCT.1996.545000

Filename

545000