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Automatic Recognition of Digital Modulation Types using Wavelet Transformation  

Park, Cheol-Sun (Agency for Defense Development)
Nah, Sun-Phil (Agency for Defense Development)
Yang, Jong-Won (Agency for Defense Development)
Choi, Jun-Ho (Agency for Defense Development)
Publication Information
Journal of the Institute of Electronics Engineers of Korea TC / v.45, no.4, 2008 , pp. 22-30 More about this Journal
Abstract
In this paper, we deal with modulation classification method using WT capable of classifying incident digital signals without a priori information. These key features should have good properties of sensitive with modulation types and insensitive with SNR variation. The 4 key features for modulation recognition are selected using WT coefficients, which have the property of insentive to the changing of noise. The numerical simulations for classifying 8 digital modulation types using these features are peformed. The numerical simulations of the 3 types (i.e. DTC, MDC, and SVMC) of modulation classifiers are performed the investigation of classification accuracy and execution time to design the modulation classification module in software radio. The simulation result indicated that the execution time of MDC and DTC was best and MDC and SVMC showed good classification performance.
Keywords
Wavelet Transformation; Modulation Classification; Decision Tree; Minimum Distance; Support Vector Machine;
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