基于时域卷积神经网络的光通信信号噪声抑制技术

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中文摘要：随着光通信技术的广泛应用,传输速率越来越高,对光信号质量的要求越来越高.同时,随着速率的提升,信号噪声带来的问题日益突出,影响系统的性能.文章提出了一种基于时域卷积神经网络(Time-domain Convolutional Neural Network,TCNN)的光通信信号噪声抑制技术.通过信号采集、数据清洗和标准化对光通信信号进行数据预处理,构建和训练TCNN模型以提取特征并抑制噪声.实验结果表明,该技术能有效提升信号的信噪比,显著改善信号质量.

外文标题：Optical Communication Signal Noise Suppression Technology Based on Time-domain Convolutional Neural Network

外文摘要：With the wide application of optical communication technology,the transmission rate is getting higher and higher,and the requirements for optical signal quality are getting higher and higher.At the same time,with the increase of the speed,the problems caused by signal noise are increasingly prominent,which affects the performance of the system.In this paper,an optical communication signal noise suppression technology based on Time-domain Convolutional Neural Network(TCNN)is proposed.Through signal acquisition,data cleaning and standardization,the optical communication signal is preprocessed,and the TCNN model is constructed and trained to extract features and suppress noise.The experimental results show that this technology can effectively improve the signal-to-noise ratio and signal quality.

外文关键词：

optical communicationTime-domain Convolutional Neural Network(TCNN)noise suppressionsignal preprocessing

作者：

刘玉鹏

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作者单位：

中兴通讯股份有限公司,江苏南京 211000

关键词：

光通信时域卷积神经网络(TCNN) 噪声抑制信号预处理

出版年：

2024

DOI：