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.

关键词： automatic modulation recognition cyclic spectral features maximum likelihood filter neural network classifiers

作者: CHEN Xiaolong WANG Jiali SUN Lu

作者单位: School of Mechano-electronic Engineering, Xidian University, Xian,710071

会议类型: 国际会议

会议名称: 第七届国际测试技术研讨会

会议地点: 北京

会议语种:英文

在线出版日期: 2007-08-05（万方平台首次上网日期，不代表论文的发表时间）