MQAM modulation scheme recognition using Hilbert transform;

Automatic digital modulation classification algorithm based on novel combined feature vector

A new method of modulation classification for digital communication signals,using normalized fourth-order cumulants as characteristics and a covering algorithm for constructing neural networks as a classifier,is proposed.

Noises and fading channel are very important factors affecting the success rate of modulation classification in practical situation.

Study on efficient adaptive clustering algorithm based modulation identification;

Method of modulation identification for digital communication signals;

A blind equalization based algorithm of modulation identification in multipath channel enviroments;

Algorithm for modulation recognition in a time-variant multipath channel environment;

The application of support vector machine to digital signal modulation recognition system;

Hierarchical digital modulation recognition using support vector machines;