Paper Info
Title
Intelligent Decision Making System for Digital Modulation Scheme Classification in Software Radio Using Wavelet Transform and Higher Order Statistical Moments
Abstract
This paper proposes a neural network (NN) based intelligent decision making system for digital modulation classification using wavelet transform, histogram peak and higher order statistical moments. The decision making system is developed to classify the modulation schemes buried in additive white Gaussian noise and channel interference utilizing NN classifier. The performance is verified and validated for M-ary PSK, M-ary FSK, M-ary QAM and GMSK modulation schemes by examining the receiver operating characteristics, confusion matrix and probability of correct identification for various signal-to-noise ratios (SNR) and also for various decision parameters. The performance of the proposed system also has been compared with existing methods and found that this method can be considered as reliable classification method for Digital Modulation Scheme with lower SNR upto 驴 5 dB.
Year
DOI
Venue
2009
10.1007/s11277-008-9621-z
Wireless Personal Communications
Keywords
Field
DocType
Software radio,Receiver operating characteristics,Feature extraction,Statistical Moments,Wavelet transform,Confusion matrix
Confusion matrix,Software-defined radio,Computer science,Minimum-shift keying,Real-time computing,Artificial intelligence,Wavelet transform,Quadrature amplitude modulation,Pattern recognition,Frequency-shift keying,QAM,Speech recognition,Additive white Gaussian noise
Journal
Volume
Issue
ISSN
50
4
0929-6212
Citations 
PageRank 
References 
4
0.45
6
Authors
2
Name
Order
Citations
PageRank
P. Prakasam1208.92
M. Madheswaran210215.57