基于深度学习的通信信号调制识别系统设计  

Design of a Communication Signal Modulation Recognition System Based on Deep Learning

作　　者：李震伟 LI Zhenwei(Laizhou Longtai Thermal Power Co.,Ltd.,Laizhou 261400,China)

机构地区：[1]莱州龙泰热电有限公司,山东莱州261400

出　　处：《通信电源技术》2024年第12期37-39,共3页Telecom Power Technology

摘　　要：文章设计一种基于深度学习的通信信号调制识别系统,旨在克服传统调制识别方法在复杂电磁环境下的局限性。系统具有信号预处理、特征提取、调制分类以及后处理决策4个模块,采用卷积神经网络(Convolutional Neural Networks,CNN)进行特征提取,结合支持向量机(Support Vector Machine,SVM)进行分类。实验结果表明,系统在多种信道条件下,尤其在复杂信道和低信噪比(Signal Noise Ratio,SNR)情况下,表现出较高的识别准确率。文章的研究成果验证了深度学习技术在通信信号处理中的应用价值,为无线通信和电子对抗领域提供了新的技术手段。The article designs a deep learning-based communication signal modulation recognition system,aiming to overcome the limitations of traditional modulation recognition methods in complex electromagnetic environments.The system has four modules:signal preprocessing,feature extraction,modulation classification and post-processing decision.ConvolutionalNeural Networks(CNN)are used for feature extraction,and Support Vector Machine(SVM)is used for feature extraction.The experimental results show that the system exhibits high recognition accuracy under a variety of channel conditions,especially under complex channels and low Signal Noise Ratio(SNR).The research results of the article validate the value of deep learning techniques in communication signal processing,and provide new technical means for the field of wireless communication and electronic countermeasures.

关 键 词：通信信号 调制识别 深度学习 

分 类 号：TN911.3[电子电信—通信与信息系统] TP18[电子电信—信息与通信工程]