Automatic Modulation Recognition for MFSK Using Modified Covariance Method
Abstract
This paper presents modulation classification method capable of classifying
MFSK digital signals without a priori information using modified covariance
method. This method using for calculation features for FSK modulation
should have a good properties of sensitive with FSK modulation index and
insensitive with signal to noise ratio SNR variation. The numerical
simulations and investigation of the performance by the support vectors
machine one against all (SVM-OAA) as a classifier for classifying 6 digitally
modulated signals which gives probability of correction classification up to
85.85 at SNR=-15dB.
MFSK digital signals without a priori information using modified covariance
method. This method using for calculation features for FSK modulation
should have a good properties of sensitive with FSK modulation index and
insensitive with signal to noise ratio SNR variation. The numerical
simulations and investigation of the performance by the support vectors
machine one against all (SVM-OAA) as a classifier for classifying 6 digitally
modulated signals which gives probability of correction classification up to
85.85 at SNR=-15dB.
Keywords
modulation recognition,support vector machine,FSK modulation
Full Text:
PDFDOI: http://doi.org/10.11591/ijece.v5i3.pp429-435
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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).