Survey of application of machine learning in wireless channel modeling
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...
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Format: | Article |
Language: | zho |
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Editorial Department of Journal on Communications
2021-02-01
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Series: | Tongxin xuebao |
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Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021001/ |
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author | Liu LIU Jianhua ZHANG Yuanyuan FAN Li YU Jiachi ZHANG |
author_facet | Liu LIU Jianhua ZHANG Yuanyuan FAN Li YU Jiachi ZHANG |
author_sort | Liu LIU |
collection | DOAJ |
description | 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. |
format | Article |
id | doaj-art-645bbb503e7c42cd964356da14c94649 |
institution | Kabale University |
issn | 1000-436X |
language | zho |
publishDate | 2021-02-01 |
publisher | Editorial Department of Journal on Communications |
record_format | Article |
series | Tongxin xuebao |
spelling | doaj-art-645bbb503e7c42cd964356da14c946492025-01-14T07:21:41ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2021-02-014213415359740404Survey of application of machine learning in wireless channel modelingLiu LIUJianhua ZHANGYuanyuan FANLi YUJiachi ZHANGChannel 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.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021001/channel modelingmachine learningneural networkclusteringchannel classification |
spellingShingle | Liu LIU Jianhua ZHANG Yuanyuan FAN Li YU Jiachi ZHANG Survey of application of machine learning in wireless channel modeling Tongxin xuebao channel modeling machine learning neural network clustering channel classification |
title | Survey of application of machine learning in wireless channel modeling |
title_full | Survey of application of machine learning in wireless channel modeling |
title_fullStr | Survey of application of machine learning in wireless channel modeling |
title_full_unstemmed | Survey of application of machine learning in wireless channel modeling |
title_short | Survey of application of machine learning in wireless channel modeling |
title_sort | survey of application of machine learning in wireless channel modeling |
topic | channel modeling machine learning neural network clustering channel classification |
url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021001/ |
work_keys_str_mv | AT liuliu surveyofapplicationofmachinelearninginwirelesschannelmodeling AT jianhuazhang surveyofapplicationofmachinelearninginwirelesschannelmodeling AT yuanyuanfan surveyofapplicationofmachinelearninginwirelesschannelmodeling AT liyu surveyofapplicationofmachinelearninginwirelesschannelmodeling AT jiachizhang surveyofapplicationofmachinelearninginwirelesschannelmodeling |