Paper Info
Title
Digital Modulation identification model using wavelet transform and statistical parameters
Abstract
A generalized modulation identification scheme is developed and presented. With the help of this scheme, the automatic modulation classification and recognition of wireless communication signals with a priori unknown parameters are possible effectively. The special features of the procedure are the possibility to adapt it dynamically to nearly all modulation types, and the capability to identify. The developed scheme based on wavelet transform and statistical parameters has been used to identify Mary PSK, M-ary QAM, GMSK, and M-ary FSK modulations. The simulated results show that the correct modulation identification is possible to a lower bound of 5 dB. The identification percentage has been analyzed based on the confusion matrix. When SNR is above 5 dB, the probability of detection of the proposed system is more than 0.968. The performance of the proposed scheme has been compared with existing methods and found it will identify all digital modulation schemes with low SNR.
Year
DOI
Venue
2008
10.1155/2008/175236
Journal Comp. Netw. and Communic.
Keywords
Field
DocType
digital modulation identification model,generalized modulation identification scheme,developed scheme,digital modulation scheme,modulation type,proposed scheme,correct modulation identification,m-ary fsk modulation,m-ary qam,identification percentage,statistical parameter,automatic modulation classification,communications,and,networks,wavelet transform
Quadrature amplitude modulation,Identification scheme,Confusion matrix,Frequency-shift keying,Computer science,Minimum-shift keying,QAM,Algorithm,Speech recognition,Modulation,Wavelet transform
Journal
Volume
Citations 
PageRank 
2008,
5
0.59
References 
Authors
3
2
Name
Order
Citations
PageRank
P. Prakasam1208.92
M. Madheswaran210215.57