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5G城市轨道交通场景分类及信道建模
引用本文:何睿斯,艾渤,钟章队,杨汨,黄晨,马张枫,孙桂琪,米航,周承毅,陈瑞凤.5G城市轨道交通场景分类及信道建模[J].电信科学,2021,37(10):102-116.
作者姓名:何睿斯  艾渤  钟章队  杨汨  黄晨  马张枫  孙桂琪  米航  周承毅  陈瑞凤
作者单位:北京交通大学轨道交通控制与安全国家重点实验室,北京 100044;中国铁道科学研究院集团有限公司电子计算技术研究所,北京 100081
基金项目:国家重点研发计划项目(2020YFB1806903);国家自然科学基金资助项目(61922012);国家自然科学基金资助项目(62001519)
摘    要:城市轨道交通是现代化交通基础设施的重要组成部分,5G作为新一代移动通信技术,可提供高速率、低时延的无线数据传输,有助于提升城市轨道交通的运行效率和服务质量。由于城市轨道交通场景的复杂性,需要针对性的通信场景分类、信道特性分析和精准的信道模型为城市轨道交通5G通信系统的设计提供理论支撑。基于此,提出了5G城市轨道交通电波传播场景的分类,以支撑典型场景下的信道测试与建模工作,同时阐述了城市轨道交通场景信道测量和建模的现状,并分析了当前面临的主要挑战。结合5G通信智能化特点,讨论了人工智能在信道特征提取和信道建模方面的应用前景与可行思路,并深入分析了基于可重构智能面和无人飞行器辅助的5G城市轨道交通信道建模研究现状和发展前景。最后,阐述了毫米波频段下5G城市轨道交通信道建模的研究。

关 键 词:智能轨道交通  5G  城市轨道交通  场景分类  信道建模  电波传播

5G urban rail traffic scenario classification and channel modeling
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[J].Telecommunications Science,2021,37(10):102-116.
Authors:Ruisi HE  Bo AI  Zhangdui ZHONG  Mi YANG  Chen HUANG  Zhangfeng MA  Guiqi Sun  Hang MI  Chengyi ZHOU  Ruifeng CHEN
Affiliation:1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China;2. Institute of Computing Technology, China Academy of Railway Sciences Co., Ltd., Beijing 100081, China
Abstract: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.
Keywords:intelligent rail traffic  5G  urban rail traffic  scenario classification  channel modeling  radio propagation  
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