Title :
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
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;
Conference_Titel :
Signal Processing and its Applications, Sixth International, Symposium on. 2001
Conference_Location :
Kuala Lumpur
Print_ISBN :
0-7803-6703-0
DOI :
10.1109/ISSPA.2001.950162
