Conference Paper

Digital modulation recognition using support vector machine classifier

Dept. of Electr. & Comput. Eng., George Washington Univ., DC, USA
DOI: 10.1109/ACSSC.2004.1399565 In proceeding of: Signals, Systems and Computers, 2004. Conference Record of the Thirty-Eighth Asilomar Conference on, Volume: 2
Source: IEEE Xplore

ABSTRACT We propose four features to classify amplitude shift keying with two levels and four levels, binary phase shift keying, quadrature phase keying, frequency shift keying with two carriers and four carriers. After that we present a new method of classification based on support vector machine (SVM) that uses the four proposed features. We study the performance of SVM classifier and compare it to the previous work done in the literature on the digital modulation classification problem.

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