Survey of application of machine learning in wireless channel modeling

Liu LIU; Jianhua ZHANG; Yuanyuan FAN; Li YU; Jiachi ZHANG

doi:10.11959/j.issn.1000-436x.2021001

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Survey of application of machine learning in wireless channel modeling

Comprehensive Reviews | 更新时间：2024-06-05

- Survey of application of machine learning in wireless channel modeling
- Journal on Communications Vol. 42, Issue 2, Pages: 134-153(2021)
- 作者机构：
  
  1. 北京交通大学电子信息工程学院，北京 100044
  2. 北京邮电大学网络与交换技术国家重点实验室，北京 100876
- 作者简介：
- 基金信息：
  
  The National Key Research and Development Program of China(2018YFB1801101);The National Science Fund for Distinguished Young Scholars of China(61925102);The Beijing Natural Science Foundation-Haidian Original Innova-tion Joint Fund Project(L172030);Key Program of National Natural Science Foundation of China(61931001)
- DOI：10.11959/j.issn.1000-436x.2021001
  CLC： TN929.5
- Online First：2021-02，
  
  Published：25 February 2021
- 稿件说明：
移动端阅览
Liu LIU, Jianhua ZHANG, Yuanyuan FAN, et al. Survey of application of machine learning in wireless channel modeling[J]. Journal on Communications, 2021, 42(2): 134-153.
DOI：

Liu LIU, Jianhua ZHANG, Yuanyuan FAN, et al. Survey of application of machine learning in wireless channel modeling[J]. Journal on Communications, 2021, 42(2): 134-153. DOI： 10.11959/j.issn.1000-436x.2021001.

摘要

信道建模是设计无线通信系统的基础，传统的信道建模方法无法自动学习特定类型信道的规律，特别是在针对特殊应用场景，如物联网、毫米波通信、车联网等，存在一定的局限性。此外，机器学习具有有效处理大数据、创建模型的能力，基于此，探讨了机器学习如何与信道建模进行有机融合，分别从信道多径分簇、参数估计、模型的构造及信道的场景识别展开了讨论，对当前该领域的重要研究成果进行了阐述，并对未来发展提出了展望。

Abstract

Channel characterization is primary to the design of the wireless communication system.The conventional channel characterization method cannot learn the law of certain types of channels by itself

which limits its application in several special scenarios

such as Internet of things

millimeter wave communication and Internet of vehicles.Machine learning was able to process the big data and establish the model.Based on this

the cooperation between the machine learning and channel characterization was investigated.The channel multipath clustering

parameter estimation

model construction and wireless channel scene recognition were discussed

and recent significant research results in this field were provided.Finally

the future direction of the machine learning in wireless channel modeling was proposed.

关键词

Keywords

references

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Hebei Key Laboratory of Space-Air-Ground Intelligent Communication, University of Science and Technology Beijing

School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications

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