现代电子技术2026，Vol.49Issue(7)：12-18,7.DOI:10.16652/j.issn.1004-373x.2026.07.003
基于自适应空间通道收缩网络的自动调制识别算法
Automatic modulation recognition algorithm based on adaptive space channel shrinkage network
高绍原 1郭文普 1康凯 1施昊1
作者信息
- 1. 火箭军工程大学 作战保障学院,陕西 西安 710025
- 折叠
摘要
Abstract
In view of the insufficient feature learning in automatic modulation recognition(AMR)algorithm at low signal-to-noise ratio(SNR),this paper proposes an AMR algorithm based on adaptive space channel shrinkage network.The algorithm is mainly composed of adaptive space channel shrinkage(ASCS)module,multi-scale convolution(MC)module,residual module and multi-head attention(MHA)module.The ASCS module is used to extract features in the spatial and channel dimensions,and the improved soft threshold function is used to shrink the features to reduce noise features and retain useful features,so as to improve the feature processing ability of the network.Comprehensive analysis of experimental results show that the improved soft threshold function can process the features better.The average recognition accuracy of the proposed AMR algorithm is 62.94%on the public dataset RML2016.10a,and 64.79%on RML2016.10b.In comparison with the existing AMR algorithm,the proposed algorithm can achieve higher accuracy.In conclusion,it provides an effective method for feature learning at low SNR.关键词
自动调制识别/收缩网络/阈值处理/通道特征/空间特征/深度学习Key words
AMR/shrinkage network/threshold processing/channel feature/spatial feature/deep learning分类
信息技术与安全科学引用本文复制引用
高绍原,郭文普,康凯,施昊..基于自适应空间通道收缩网络的自动调制识别算法[J].现代电子技术,2026,49(7):12-18,7.
