An Automatic Modulation Recognition Method Based on Cyclic Spectral and Neural Network in Test and Measurement Technology

摘要

In this paper, a method is presented based on the cyclic spectral features and the neural network classifiers for performing automatic modulation recognition. The process of the automatic modulation recognition using the method is divided into three basic steps: cyclic spectrum analysis, feature extraction and neural network classifier. Some computer simulation results showing the performance of the method in this paper are improved. The method can efficiently recognize almost all currently used modulation types and the recognition accuracy rate is over 95% at the SNRs of 10 dB.