基于深度学习的调制识别综述  

A survey of deep learning based modulation recognition

作　　者：孙姝君 彭盛亮[1] 姚育东 杨喜 SUN Shujun;PENG Shengliang;YAO Yudong;YANG Xi(College of Information Science and Engineering,Huaqiao University,Xiamen 361021,China;Department of Electrical and Computer Engineering,Stevens Institute of Technology,Hoboken NJ 07030,USA;College of Information Science and Engineering,Jishou University,Jishou 416000,China)

机构地区：[1]华侨大学信息科学与工程学院,福建厦门361021 [2]史蒂文斯理工学院电子与计算机工程系,美国新泽西州霍博肯07030 [3]吉首大学信息科学与工程学院,湖南吉首416000

出　　处：《电信科学》2021年第5期82-90,共9页Telecommunications Science

基　　金：国家自然科学基金资助项目(No.61861019);华侨大学中央高校基本科研业务费专项(No.ZQN-708)。

摘　　要：调制识别是通信系统的基础任务之一,在认知无线电、智能通信、无线电监管、电子对抗等领域均有着广泛的应用。近年来,基于深度学习的调制识别技术以其在特征提取和识别性能方面的优势,日益成为研究的焦点。系统地梳理了基于深度学习的调制识别技术,首先介绍了相关基础,随后详细阐述了其系统架构、数据预处理方式、深度神经网络结构、常用数据集以及评价指标,最后分析展望了该技术未来的发展方向。Modulation recognition is one of the fundamental tasks for communications systems,which can be widely applied in various fields,such as cognitive radio,intelligent communications,radio surveillance,electronic warfare,etc.In recent years,deep learning(DL)based modulation recognition has attracted great attention due to its superiority in feature extraction and recognition performance.The techniques of DL based modulation recognition were systematically summarized.Firstly,some knowledge relevant to DL based modulation recognition was introduced.Then,the system architecture,data pre-processing methods,deep neural network structures,prevalent datasets and performance metrics of DL based modulation recognition were illustrated.Finally,the future directions of DL based modulation recognition were also discussed.

关 键 词：深度学习 调制识别 数据预处理 深度神经网络 

分 类 号：TN929[电子电信—通信与信息系统]