电讯技术2025，Vol.65Issue(4)：518-524,7.DOI:10.20079/j.issn.1001-893x.240116003
基于时空卷积网络的通信信号调制识别
Modulation Recognition of Communication Signals Based on Spatiotemporal Convolutional Network
摘要
Abstract
For the problems that modulation recognition methods based on deep learning do not utilize the original signal sequence information,the recognition rate is low,and the number of parameters is large,a modulation recognition algorithm based on Spatiotemporal Convolutional Network(SCN)is proposed.In order to prevent the loss of signal sequence information,the network first extracts the temporal features of the signal,and then extracts the spatial features of the signal.The temporal features are extracted using the Temporal Convolutional Network(TCN)structure.Two-Dimensional Convolution Neural Network(2D-CNN)is used to extract spatial features.In the final classification,Global Average Pooling(GAP)is used to replace the Flatten layer.Due to the application of causal expansion convolution and GAP in TCN,the simultaneous parameters of high recognition rate are greatly reduced.Compared with that of the traditional CNN2,ResNet,DenseNet,CLDNN and LSTM2,the IQ signal modulation recognition without preprocessing has the lowest number of parameters,and the average recognition accuracy is improved by 4.9%～16.5%.关键词
通信信号/调制识别/深度学习/时域特征/空间特征/全局平均池化Key words
communication signal/modulation recognition/deep learning/time domain characteristics/spatial characteristics/global average pooling分类
电子信息工程引用本文复制引用
陈发堂,刘泽,范子健..基于时空卷积网络的通信信号调制识别[J].电讯技术,2025,65(4):518-524,7.基金项目
重庆市自然科学基金创新发展联合基金(中国星网)(CSTB2023NSCQ-LZX0114) （中国星网）
