Computer Science ›› 2023, Vol. 50 ›› Issue (6A): 220600179-5.doi: 10.11896/jsjkx.220600179

• Network & Communication • Previous Articles     Next Articles

Study on Performance of Wireless Train Communication Network Based on Wi-Fi 6

YANG Shaolong, ZHU Guosheng, PANG Xinglong, LI Xiuyuan, PAN Deng   

  1. School of Computer and Information Engineering,Huhei University,Wuhan 430062,China
  • Online:2023-06-10 Published:2023-06-12
  • About author:YANG Shaolong,born in 1998,postgraduate.His main research interersts include network traffic analysis and communication network. ZHU Guosheng,born in 1972,Ph.D,professor.His main research interests include next-generation Internet and software-defined network.

Abstract: The normal operation of modern trains is inseparable from the cooperation of mechanical and electronic systems,especially the train control and management system(TCMS) plays a key role in it.TCMS-related applications and services run on the train communication network(TCN),which is wired and often redundant,resulting in a large number of wired links interconnection,making network deployment and maintenance difficulties,and poor flexibility.This paper proposes a Wi-Fi 6-based train wireless communication networking scheme,which applies Wi-Fi 6 technology to the vehicle-level ECN network.The work includes the design of network architecture,the selection of communication data and the experimental verification in simulation environment.Experimental results show that the proposed Wi-Fi 6-based train communication QoS in terms of delay,jitter and packet loss rate meets the IEC 61375-3-4 standard,and have advantages over long term evolution(LTE).

Key words: Wi-Fi 6, Train communication network, Wireless communication, Real-time

CLC Number: 

  • TP393
[1]MA L C,ZHONG C C,CAO Y,et al.Research on train communication network based on switched Ethernet[J].Computers in Railways XIV:Railway Engineering Design and Optimization,2014,135(109).
[2]IEC/TC9.IEC 61375-1:2012 Electronic railway equipment-Traincommunication network(TCN)-Part 1:General architecture[S].Geneva:International Electrotechnical Commission(IEC),2012.
[3]FENG J,LU X,YANGW,et al.Survey of development and application of train communication network[C]//Proceedings of the 2015 International Conference on Electrical and Information Technologies for Rail Transportation.Springer,Berlin,Heidelberg,2016:843-854.
[4]HÄRRI J,ARRIOLA A,ALJAMA P,et al.Wireless Technologies for the Next-Generation Train Control and Monitoring System[C]//2019 IEEE 2nd 5G World Forum(5GWF).IEEE,2019:179-184.
[5]MIN C,JINHAO Z.The Application of Wi-Fi 6 Technology in Underground Mine[C]//IOP Conference Series:Earth and Environmental Science.IOP Publishing,012153.
[6]SERRANO P,SALVADOR P,MANCUSO V,et al.Experimenting with commodity 802.11 hardware:Overview and future directions[J].IEEE Communications Surveys & Tutorials,2015,17(2):671-699.
[7]KHOROV E,KIRYANOV A,LYAKHOVA,et al.A tutorialon IEEE 802.11 ax high efficiency WLANs[J].IEEE Communications Surveys & Tutorials,2018,21(1):197-216.
[8]BANERJI S,CHOWDHURY R S.On IEEE 802.11:wirelessLAN technology[J].arXiv:1307.2661,2013.
[9]LUDICKE D,LEHNER A.Train communication networks and prospects[J].IEEE Communications Magazine,2019,57(9):39-43.
[10]AI B,GUAN K,RUPPM,et al.Future railway services-oriented mobile communications network[J].IEEE Communications Magazine,2015,53(10):78-85.
[11]GARCÍA-LOYGORRI J M,GOIKOETXEA J,ECHEVE-RRÍA E,et al.The wireless train communication network:Roll2Rail vision[J].IEEE Vehicular Technology Magazine,2018,13(3):135-143.
[12]ALJAMA P,ARRIOLA A,MARTÍNEZ I,et al.Applicability of 5G Technology for a Wireless Train Backbone[C]//2021 15th European Conference on Antennas and Propagation(EuCAP).IEEE,2021:1-5.
[13]REKIK M,GRANSART C,BERBINEAU M.Cyber-physicalsecurity risk assessment for train control and monitoring systems[C]//2018 IEEE Conference on Communications and Network Security(CNS).IEEE,2018:1-9.
[14]IEC/TC9.IEC 61375-2-5:2014 Electronic railway equipment-Train communication network(TCN)-Part 2-5:Ethernet train backbone[S].Geneva:International Electrotechnical Commission(IEC),2014.
[15]LIU Y,TONG K F,QIUX,et al.Wireless mesh networks in IoT networks[C]//2017 International Workshop on Electromagnetics:Applications and Student Innovation Competition.IEEE,2017:183-185.
[16]IEC/TC9.IEC 61375-3-4:2014 Electronic railway equipment - Train communication network(TCN)-Part 3-4:Ethernet Consist Network(ECN)[S].Geneva:International Electrotechnical Commission(IEC),2014.
[17]WANG T,WANG L D,ZHOU J Q,et al.Research on Real-time Performance of Train Communication Network Based on the Switched Ethernet Technology[J].Journal of the China Railway Society,2015,37(4):39-45.
[18]GARCÍA-LOYGORRI J M,VAL I,ARRIOLA A,et al.Channel model and interference evaluation for a wireless train backbone[J].IEEE Access,2019,7:115518-115527.
[19]MURUGANATHAN S D,LIN X,MÄÄTTÄNEN H L,et al.An overview of 3GPP release-15 study on enhanced LTE support for connected drones[J].IEEE Communications Standards Magazine,2021,5(4):140-146.
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