基于深度学习的无线通信接收方法研究进展与趋势

doi:10.11959/j.issn.1000-0801.2022025

电信科学 ›› 2022, Vol. 38 ›› Issue (2): 1-17.doi: 10.11959/j.issn.1000-0801.2022025

• 综述 • 下一篇

基于深度学习的无线通信接收方法研究进展与趋势

李攀攀¹, 谢正霞², 乐光学¹, 刘鑫³

¹ 嘉兴学院信息科学与工程学院，浙江嘉兴 314001
² 嘉兴学院建筑工程学院，浙江嘉兴 314001
³ 大连理工大学信息与通信工程学院，辽宁大连 116024

修回日期:2022-02-04 出版日期:2022-02-20 发布日期:2022-02-01
作者简介:李攀攀（1983- ），男，博士，嘉兴学院讲师，主要研究方向为智能通信、深度学习、网络空间安全等
谢正霞（1982- ），女，嘉兴学院工程师，主要研究方向为智能通信、网络空间安全等
乐光学（1963- ），男，博士，嘉兴学院教授，主要研究方向为多云融合与协同服务、无线 mesh 网络与移动云计算、嵌入式系统等
刘鑫（1984- ），男，博士，大连理工大学副教授，主要研究方向为认知无线电、无人机通信和卫星通信等
基金资助:
国家自然科学基金资助项目(U19B2015);国家自然科学基金资助项目(U1833102)

Research progress and trends of deep learning based wireless communication receiving method

Panpan LI¹, Zhengxia XIE², Guangxue YUE¹, Xin LIU³

¹ College of Information Science and Technology, Jiaxing University, Jiaxing 314001, China
² College of Civil Engineering and Architecture, Jiaxing University, Jiaxing 314001, China
³ School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China

Revised:2022-02-04 Online:2022-02-20 Published:2022-02-01
Supported by:
The National Natural Science Foundation of China(U19B2015);The National Natural Science Foundation of China(U1833102)

摘要/Abstract

摘要：

随着无线通信应用边界的不断扩展，无线通信应用环境也日趋复杂多样，面临射频损伤、信道衰落、干扰和噪声等负面影响，给接收端恢复原始信息带来挑战。借鉴深度学习方法在计算机视觉、模式识别、自然语言处理等领域取得的研究成果，基于深度学习的无线通信接收技术受到学术界和产业界的广泛关注。首先阐述了国内外基于深度学习无线通信接收技术的研究现状；接着概述了信号大数据背景下无线通信接收所面临的技术挑战，并提出基于深度神经网络的无线通信智能接收参考架构；最后探讨了信号大数据背景下无线通信智能接收方法的发展趋势。为基于深度学习无线通信技术的研究和发展提供借鉴。

关键词: 无线通信, 信号大数据, 深度学习, 深度神经网络, 信号接收

Abstract:

With the continues expansion of the application boundary for wireless communications, the application environment of wireless communications is becoming increasingly complex and diverse, which faces negative impacts such as radio frequency (RF) damage, channel fading, interference and noise.It brings difficulties to recover the original information at the receiver.Drawing from the research results of deep learning methods in computer vision, pattern recognition, natural language processing and other fields, wireless communication reception technology based on deep learning has received wide attentions from both academia and industry.Firstly, the current research status of wireless communication reception technology based on deep learning at home and abroad was described.Secondly, the current technical challenges of wireless communication reception in the context of signal big data were outlined, and a reference architecture of intelligent wireless communication reception based on deep neural network was proposed.Finally, the development trend of intelligent wireless communication reception method in the context of signal big data was discussed.It is expected to provide reference for the research and development of wireless communication technology based on deep learning.

Key words: wireless communication, signal big data, deep learning, deep neural network, signal reception

中图分类号:

TN929.5

李攀攀, 谢正霞, 乐光学, 刘鑫. 基于深度学习的无线通信接收方法研究进展与趋势[J]. 电信科学, 2022, 38(2): 1-17.

Panpan LI, Zhengxia XIE, Guangxue YUE, Xin LIU. Research progress and trends of deep learning based wireless communication receiving method[J]. Telecommunications Science, 2022, 38(2): 1-17.

图/表 6

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基于深度学习的无线通信接收方法研究进展与趋势

Research progress and trends of deep learning based wireless communication receiving method

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