Lei Ma, K. Guan, Dong Yan, Danping He, B. Ai, Junhyeong Kim, Heesang Chung
{"title":"实现22.6 GHz智能铁路机动性的高速铁路信道特性","authors":"Lei Ma, K. Guan, Dong Yan, Danping He, B. Ai, Junhyeong Kim, Heesang Chung","doi":"10.1109/WCNC45663.2020.9120474","DOIUrl":null,"url":null,"abstract":"The millimeter wave (mmWave) communication with large bandwidth is a key enabler for both the fifth-generation mobile communication system (5G) and smart rail mobility. Thus, in order to provide realistic channel fundamental, the wireless channel at 22.6 GHz is characterized for a typical high-speed railway (HSR) environment in this paper. After importing the three-dimensional environment model of a typical HSR scenario into a self-developed high-performance cloud-computing Ray-Tracing platform – CloudRT, extensive raytracing simulations are realized. Based on the results, the HSR channel characteristics are extracted and analyzed, considering the extra loss of various weather conditions. The results of this paper can help for the design and evaluation for the HSR communication systems enabling smart rail mobility.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Characterization for High-Speed Railway Channel enabling Smart Rail Mobility at 22.6 GHz\",\"authors\":\"Lei Ma, K. Guan, Dong Yan, Danping He, B. Ai, Junhyeong Kim, Heesang Chung\",\"doi\":\"10.1109/WCNC45663.2020.9120474\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The millimeter wave (mmWave) communication with large bandwidth is a key enabler for both the fifth-generation mobile communication system (5G) and smart rail mobility. Thus, in order to provide realistic channel fundamental, the wireless channel at 22.6 GHz is characterized for a typical high-speed railway (HSR) environment in this paper. After importing the three-dimensional environment model of a typical HSR scenario into a self-developed high-performance cloud-computing Ray-Tracing platform – CloudRT, extensive raytracing simulations are realized. Based on the results, the HSR channel characteristics are extracted and analyzed, considering the extra loss of various weather conditions. The results of this paper can help for the design and evaluation for the HSR communication systems enabling smart rail mobility.\",\"PeriodicalId\":415064,\"journal\":{\"name\":\"2020 IEEE Wireless Communications and Networking Conference (WCNC)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Wireless Communications and Networking Conference (WCNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCNC45663.2020.9120474\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNC45663.2020.9120474","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Characterization for High-Speed Railway Channel enabling Smart Rail Mobility at 22.6 GHz
The millimeter wave (mmWave) communication with large bandwidth is a key enabler for both the fifth-generation mobile communication system (5G) and smart rail mobility. Thus, in order to provide realistic channel fundamental, the wireless channel at 22.6 GHz is characterized for a typical high-speed railway (HSR) environment in this paper. After importing the three-dimensional environment model of a typical HSR scenario into a self-developed high-performance cloud-computing Ray-Tracing platform – CloudRT, extensive raytracing simulations are realized. Based on the results, the HSR channel characteristics are extracted and analyzed, considering the extra loss of various weather conditions. The results of this paper can help for the design and evaluation for the HSR communication systems enabling smart rail mobility.