Automatic digital modulation recognition using spectral and statistical features with multi-layer perceptrons

Author

Wong, M.L.D. ; Nandi, A.K.

Author_Institution

Dept. of Electr. Eng. & Electron., Liverpool Univ., UK

Volume

2

fYear

2001

fDate

2001

Firstpage

390

Abstract

Automatic recognition of digitally modulated signals has seen increasing demand nowadays. The use of ANNs for this purpose has been popular since the late 90´s. We propose an MLP recogniser implementation with better generalisation as well as an addition of a new statistical cumulant based features set for recognising ten different modulation types. Simulations show satisfactory results even with low SNR value, e.g. 98% success rate at 0 dB SNR

Keywords

amplitude shift keying; feature extraction; frequency shift keying; higher order statistics; multilayer perceptrons; quadrature amplitude modulation; spectral analysis; telecommunication computing; ANN; ASK; BPSK; FSK; MLP recogniser implementation; PSK; QAM; QPSK; SNR; amplitude shift keying; artificial neural network; automatic digital modulation recognition; automatic recognition; digitally modulated signals; feature extraction; frequency shift keying; multilayer perceptrons; phase shift keying; quadrature amplitude modulation; spectral features; statistical cumulant; statistical features; Artificial neural networks; Counting circuits; Demodulation; Digital communication; Digital modulation; Digital signal processing; Frequency shift keying; Pattern recognition; Signal processing; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and its Applications, Sixth International, Symposium on. 2001

Conference_Location

Kuala Lumpur

Print_ISBN

0-7803-6703-0

Type

conf

DOI

10.1109/ISSPA.2001.950162

Filename

950162