K. Guan, B. Ai, Danping He, D. Matolak, Qi Wang, Z. Zhong, T. Kürner
{"title":"面向智能车辆通信的受阻车对车信道建模","authors":"K. Guan, B. Ai, Danping He, D. Matolak, Qi Wang, Z. Zhong, T. Kürner","doi":"10.1109/GLOBALSIP.2018.8646585","DOIUrl":null,"url":null,"abstract":"In this paper, we model obstructed vehicle-to-vehicle (V2V) channels for the 5-GHz band through measurement-validated ray-tracing (RT) simulations. To begin, we establish a realistic V2V RT simulator through integrating three key channel features: small-scale structures (e.g. lampposts, traffic signs), handled by their approximate radar cross sections; large-scale structures (such as buildings and ground), calibrating their electromagnetic and scattering parameters; and obstructing vehicle effects via V2V channel measurements. Then, based on extensive RT simulations, the target channels are characterized comprehensively. All the parameters are input into and verified by the 3GPP-like quasi deterministic radio channel generator (QuaDRiGa). By adding the obstructed V2V scenario into standard channel model families, this paper provides a foundation for evaluating intelligent vehicular communications in challenging conditions.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"OBSTRUCTED VEHICLE-TO-VEHICLE CHANNEL MODELING FOR INTELLIGENT VEHICULAR COMMUNICATIONS\",\"authors\":\"K. Guan, B. Ai, Danping He, D. Matolak, Qi Wang, Z. Zhong, T. Kürner\",\"doi\":\"10.1109/GLOBALSIP.2018.8646585\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we model obstructed vehicle-to-vehicle (V2V) channels for the 5-GHz band through measurement-validated ray-tracing (RT) simulations. To begin, we establish a realistic V2V RT simulator through integrating three key channel features: small-scale structures (e.g. lampposts, traffic signs), handled by their approximate radar cross sections; large-scale structures (such as buildings and ground), calibrating their electromagnetic and scattering parameters; and obstructing vehicle effects via V2V channel measurements. Then, based on extensive RT simulations, the target channels are characterized comprehensively. All the parameters are input into and verified by the 3GPP-like quasi deterministic radio channel generator (QuaDRiGa). By adding the obstructed V2V scenario into standard channel model families, this paper provides a foundation for evaluating intelligent vehicular communications in challenging conditions.\",\"PeriodicalId\":119131,\"journal\":{\"name\":\"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GLOBALSIP.2018.8646585\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLOBALSIP.2018.8646585","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
OBSTRUCTED VEHICLE-TO-VEHICLE CHANNEL MODELING FOR INTELLIGENT VEHICULAR COMMUNICATIONS
In this paper, we model obstructed vehicle-to-vehicle (V2V) channels for the 5-GHz band through measurement-validated ray-tracing (RT) simulations. To begin, we establish a realistic V2V RT simulator through integrating three key channel features: small-scale structures (e.g. lampposts, traffic signs), handled by their approximate radar cross sections; large-scale structures (such as buildings and ground), calibrating their electromagnetic and scattering parameters; and obstructing vehicle effects via V2V channel measurements. Then, based on extensive RT simulations, the target channels are characterized comprehensively. All the parameters are input into and verified by the 3GPP-like quasi deterministic radio channel generator (QuaDRiGa). By adding the obstructed V2V scenario into standard channel model families, this paper provides a foundation for evaluating intelligent vehicular communications in challenging conditions.