无线电工程2025，Vol.55Issue(3)：526-539,14.DOI:10.3969/j.issn.1003-3106.2025.03.009
基于深度学习的通信信号自动调制识别方法综述
Overview of Automatic Modulation Recognition Methods for Communication Signals Based on Deep Learning
陈昊 1郭文普 1巨西诺 2康凯 1施昊 1高绍原1
作者信息
- 1. 火箭军工程大学 作战保障学院,陕西 西安 710025
- 2. 中国人民解放军96852 部队,辽宁 沈阳 110033
- 折叠
摘要
Abstract
Automatic Modulation Recognition(AMR)is used to detect the modulation pattern of received signals and is a key prerequisite for subsequent information processing in communication systems.It is widely applied in various fields such as electronic warfare,spectrum control,and cognitive radio.In recent years,Deep Learning(DL)has experienced rapid development.The non-linear transformation of neurons and flexible concatenation methods of various neural networks make the network models have strong feature extraction capabilities,laying a solid foundation for the research of DL-AMR methods.Compared with the traditional AMR methods,the DL-AMR method has advantages in recognition accuracy and computational complexity.Based on this,the DL-AMR method is reviewed systematically from six aspects:overview of AMR,network model mechanism,AMR signal model,DL-AMR method,open source benchmark dataset,model evaluation indicators,and baseline model simulation experiment.The current research status is analyzed and summarized,the future research direction is prospected,which further promotes the progress of DL-AMR research.关键词
自动调制识别/深度学习/卷积神经网络/循环神经网络/混合神经网络Key words
AMR/DL/convolutional neural network/recurrent neural network/hybrid neural network分类
信息技术与安全科学引用本文复制引用
陈昊,郭文普,巨西诺,康凯,施昊,高绍原..基于深度学习的通信信号自动调制识别方法综述[J].无线电工程,2025,55(3):526-539,14.
