现代电子技术2024，Vol.47Issue(15)：47-52,6.DOI:10.16652/j.issn.1004-373x.2024.15.008
基于循环谱的去模糊调制识别算法
Deblurring modulation recognition algorithm based on cyclic spectrum
摘要
Abstract
In view of the low recognition rate of current modulation recognition algorithms at low signal-to-noise ratio(SNR)and its performance degradation of cyclic spectrum applications due to the spectrum similarity of some signals,a deblurring modulation recognition algorithm based on 2D cyclic spectrum grayscale is proposed.A 2D cyclic spectral grayscale template library is constructed for the signals with similar spectral features.And then,the input signals are streamed into two parts by spectral matching with the template library,including spectrum-similar signals and spectrum-distinguishable signals.A differentiated recognition method is proposed on the basis of signal streaming.For the spectrum-distinguishable signals,a convolutional neural network(CNN)based on 2D cyclic spectrum grayscale(CSG-Net)is constructed to complete the recognition.For the spectrum-similar signals,the recognition is completed with the help of multi-channel learning deep neural network(MCLDNN).The experimental results show that the advantages of different networks are integrated in the proposed algorithm,which improves the overall recognition performance of the network with a recognition rate close to 70%when the SNR is-10 dB.关键词
循环谱/深度学习/卷积神经网络/自动调制识别/低信噪比/去模糊调制Key words
cyclic spectrum/deep learning/CNN/automatic modulation recognition/low SNR/deblurring modulation分类
电子信息工程引用本文复制引用
陈杰豪,王江..基于循环谱的去模糊调制识别算法[J].现代电子技术,2024,47(15):47-52,6.基金项目
国家重点研发计划项目:物联网智能传感器系统集成与应用示范(2021YFB3202105) （2021YFB3202105）
中科院创新基金(CXJJ-23S037) （CXJJ-23S037）
