5G urban rail traffic scenario classification and channel modeling
Urban rail traffic is an important part of modern transportation infrastructure.As a new generation of mobile communication technology, 5G can provide high data rate and low latency wireless transmission, which helps to improve the efficiency and service quality of urban rail traffic system.Due to t...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2021-10-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2021243/ |
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| _version_ | 1841528876049629184 |
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| author | Ruisi HE Bo AI Zhangdui ZHONG Mi YANG Chen HUANG Zhangfeng MA Guiqi Sun Hang MI Chengyi ZHOU Ruifeng CHEN |
| author_facet | Ruisi HE Bo AI Zhangdui ZHONG Mi YANG Chen HUANG Zhangfeng MA Guiqi Sun Hang MI Chengyi ZHOU Ruifeng CHEN |
| author_sort | Ruisi HE |
| collection | DOAJ |
| description | Urban rail traffic is an important part of modern transportation infrastructure.As a new generation of mobile communication technology, 5G can provide high data rate and low latency wireless transmission, which helps to improve the efficiency and service quality of urban rail traffic system.Due to the complexity of urban rail traffic scenarios, accurate communication scenario classification, channel characterization and channel models are required to provide theoretical support for the design of urban rail traffic 5G communication systems.The classification of 5G urban rail traffic radio propagation scenarios to support channel measurements and modeling was proposed.Current status of urban rail traffic channel measurements and modeling was shown, and the current challenges were analyzed.The applications of artificial intelligence in channel feature extraction and channel modeling were discussed, and the 5G urban rail traffic channels by considering reconfigurable intelligent surface and unmanned aerial vehicle were analyzed.Finally, the research on 5G urban rail traffic channel modeling at millimeter wave frequency band was described. |
| format | Article |
| id | doaj-art-a0f047f5e99b40448d1babab863f594b |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2021-10-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-a0f047f5e99b40448d1babab863f594b2025-01-15T03:32:54ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012021-10-0137102116598155295G urban rail traffic scenario classification and channel modelingRuisi HEBo AIZhangdui ZHONGMi YANGChen HUANGZhangfeng MAGuiqi SunHang MIChengyi ZHOURuifeng CHENUrban rail traffic is an important part of modern transportation infrastructure.As a new generation of mobile communication technology, 5G can provide high data rate and low latency wireless transmission, which helps to improve the efficiency and service quality of urban rail traffic system.Due to the complexity of urban rail traffic scenarios, accurate communication scenario classification, channel characterization and channel models are required to provide theoretical support for the design of urban rail traffic 5G communication systems.The classification of 5G urban rail traffic radio propagation scenarios to support channel measurements and modeling was proposed.Current status of urban rail traffic channel measurements and modeling was shown, and the current challenges were analyzed.The applications of artificial intelligence in channel feature extraction and channel modeling were discussed, and the 5G urban rail traffic channels by considering reconfigurable intelligent surface and unmanned aerial vehicle were analyzed.Finally, the research on 5G urban rail traffic channel modeling at millimeter wave frequency band was described.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2021243/intelligent rail traffic5Gurban rail trafficscenario classificationchannel modelingradio propagation |
| spellingShingle | Ruisi HE Bo AI Zhangdui ZHONG Mi YANG Chen HUANG Zhangfeng MA Guiqi Sun Hang MI Chengyi ZHOU Ruifeng CHEN 5G urban rail traffic scenario classification and channel modeling Dianxin kexue intelligent rail traffic 5G urban rail traffic scenario classification channel modeling radio propagation |
| title | 5G urban rail traffic scenario classification and channel modeling |
| title_full | 5G urban rail traffic scenario classification and channel modeling |
| title_fullStr | 5G urban rail traffic scenario classification and channel modeling |
| title_full_unstemmed | 5G urban rail traffic scenario classification and channel modeling |
| title_short | 5G urban rail traffic scenario classification and channel modeling |
| title_sort | 5g urban rail traffic scenario classification and channel modeling |
| topic | intelligent rail traffic 5G urban rail traffic scenario classification channel modeling radio propagation |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2021243/ |
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