5G城市轨道交通场景分类及信道建模

doi:10.11959/j.issn.1000-0801.2021243

Abstract

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.

Key words: intelligent rail traffic, 5G, urban rail traffic, scenario classification, channel modeling, radio propagation

CLC Number:

TN92

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.

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References 59

[1]	AI B , CHENG X , KüRNER T , ,et al. Challenges toward wireless communications for high-speed railway[J]. IEEE Transactions on Intelligent Transportation Systems, 2014,15(5): 2143-2158.
[2]	AI B , HE R S , ZHONG Z D ,et al. Radio wave propagation scene partitioning for high-speed rails[J]. International Journal of Antennas and Propagation, 2012: 1-7.
[3]	WANG C X , BIAN J , SUN J ,et al. A survey of 5G channel measurements and models[J]. IEEE Communications Surveys＆ Tutorials, 2018,20(4): 3142-3168.
[4]	WANG C X , GHAZAL A , AI B ,et al. Channel measurements and models for high-speed train communication systems:a survey[J]. IEEE Communications Surveys ＆ Tutorials, 2016,18(2): 974-987.
[5]	ZHANG J H , TANG P , YU L ,et al. Channel measurements and models for 6G:current status and future outlook[J]. Frontiers of Information Technology ＆ Electronic Engineering, 2020,21(1): 39-61.
[6]	ZHANG B , ZHONG Z D , HE R S ,et al. Measurement-based Markov modeling for multi-link channels in railway communication systems[J]. IEEE Transactions on Intelligent Transportation Systems, 2019,20(3): 985-999.
[7]	HE R S , ZHONG Z D , AI B ,et al. Measurements and analysis of propagation channels in high-speed railway viaducts[J]. IEEE Transactions on Wireless Communications, 2013,12(2): 794-805.
[8]	ZHANG B , ZHONG Z D , HE R S ,et al. Measurement-based multiple-scattering model of small-scale fading in high-speed railway cutting scenarios[J]. IEEE Antennas and Wireless Propagation Letters, 2017,16: 1427-1430.
[9]	LI J Z , AI B , HE R S ,et al. Cluster-based 3D channel modeling for massive MIMO in subway station environment[J]. IEEE Access, 2018,6: 6257-6272.
[10]	AI B , GUAN K , ZHONG Z D ,et al. Measurement and analysis of extra propagation loss of tunnel curve[J]. IEEE Transactions on Vehicular Technology, 2016,65(4): 1847-1858.
[11]	WANG J , LI R , WANG J ,et al. Artificial intelligence and wireless communications[J]. Frontiers of Information Technology ＆Electronic Engineering, 2020,21(10): 1413-1425.
[12]	LIU Y , WANG C X , HUANG J . Recent developments and future challenges in channel measurements and models for 5G and beyond high-speed train communication systems[J]. IEEE Communications Magazine, 2019,57(9): 50-56.
[13]	AI B , MOLISCH A F , RUPP M ,et al. 5G key technologies for smart railways[J]. Proceedings of the IEEE, 2020,108(6): 856-893.
[14]	HE R S , AI B , MOLISCH A F ,et al. Clustering enabled wireless channel modeling using big data algorithms[J]. IEEE Communications Magazine, 2018,56(5): 177-183.
[15]	HUANG C , MOLISCH A F , GENG Y L ,et al. Trajectory-joint clustering algorithm for time-varying channel modeling[J]. IEEE Transactions on Vehicular Technology, 2020,69(1): 1041-1045.
[16]	HUANG C , HE R S , ZHONG Z D ,et al. A power-angle-spectrum based clustering and tracking algorithm for time-varying radio channels[J]. IEEE Transactions on Vehicular Technology, 2019,68(1): 291-305.
[17]	HUANG C , MOLISCH A F , HE R S ,et al. Machine-learning-based data processing techniques for vehicle-to-vehicle channel modeling[J]. IEEE Communications Magazine, 2019,57(11): 109-115.
[18]	KURNIAWAN E , ZHIWEI L , SUN S M . Machine learning-based channel classification and its application to IEEE 802.11ad communications[C]// Proceedings of GLOBECOM 2017 - 2017 IEEE Global Communications Conference. Piscataway:IEEE Press, 2017: 1-6.
[19]	XIAO Z L , WEN H K , MARKHAM A ,et al. Non-line-of-sight identification and mitigation using received signal strength[J]. IEEE Transactions on Wireless Communications, 2015,14(3): 1689-1702.
[20]	VAN NGUYEN T , JEONG Y , SHIN H ,et al. Machine learning for wideband localization[J]. IEEE Journal on Selected Areas in Communications, 2015,33(7): 1357-1380.
[21]	HUANG C , MOLISCH A F , HE R S ,et al. Machine learning-enabled LOS/NLOS identification for MIMO systems in dynamic environments[J]. IEEE Transactions on Wireless Communications, 2020,19(6): 3643-3657.
[22]	YANG M , AI B , HE R S ,et al. Machine-learning-based scenario identification using channel characteristics in intelligent vehicular communications[J]. IEEE Transactions on Intelligent Transportation Systems, 2021,22(7): 3961-3974.
[23]	WU Q Q , ZHANG R . Towards smart and reconfigurable environment:intelligent reflecting surface aided wireless network[J]. IEEE Communications Magazine, 2020,58(1): 106-112.
[24]	LONG R Z , LIANG Y C , PEI Y Y ,et al. Active reconfigurable intelligent surface-aided wireless communications[J]. IEEE Transactions on Wireless Communications, 2021,20(8): 4962-4975.
[25]	JUNG M , SAAD W , DEBBAH M ,et al. On the optimality of reconfigurable intelligent surfaces (RISs):passive beamforming,modulation,and resource allocation[J]. IEEE Transactions on Wireless Communications, 2021,20(7): 4347-4363.
[26]	SHOJAEIFARD A , WONG K K , DI RENZO M ,et al. Massive MIMO-enabled full-duplex cellular networks[J]. IEEE Transactions on Communications, 2017,65(11): 4734-4750.
[27]	LIASKOS C , NIE S , TSIOLIARIDOU A ,et al. A new wireless communication paradigm through software-controlled metasurfaces[J]. IEEE Communications Magazine, 2018,56(9): 162-169.
[28]	YANG B , CAO X L , HUANG C W ,et al. Intelligent spectrum learning for wireless networks with reconfigurable intelligent surfaces[J]. IEEE Transactions on Vehicular Technology, 2021,70(4): 3920-3925.
[29]	HUANG C W , ZAPPONE A , ALEXANDROPOULOS G C ,et al. Reconfigurable intelligent surfaces for energy efficiency in wireless communication[J]. IEEE Transactions on Wireless Communications, 2019,18(8): 4157-4170.
[30]	TAHA A , ZHANG Y , MISMAR F B ,et al. Deep reinforcement learning for intelligent reflecting surfaces:towards standalone operation[C]// Proceedings of 2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). Piscataway:IEEE Press, 2020: 1-5.
[31]	TANG W K , CHEN M Z , CHEN X Y ,et al. Wireless communications with reconfigurable intelligent surface:path loss modeling and experimental measurement[J]. IEEE Transactions on Wireless Communications, 2021,20(1): 421-439.
[32]	BASAR E , YILDIRIM I , KILINC F . Indoor and outdoor physical channel modeling and efficient positioning for reconfigurable intelligent surfaces in mmWave bands[J]. IEEE Transactions on Communications, 3954,PP(99): 1.
[33]	HE R S , SCHNEIDER C , AI B ,et al. Propagation channels of 5G millimeter-wave vehicle-to-vehicle communications:recent advances and future challenges[J]. IEEE Vehicular Technology Magazine, 2020,15(1): 16-26.
[34]	DI RENZO M , ZAPPONE A , DEBBAH M ,et al. Smart radio environments empowered by reconfigurable intelligent surfaces:how it works,state of research,and the road ahead[J]. IEEE Journal on Selected Areas in Communications, 2020,38(11): 2450-2525.
[35]	RENZO M D , DEBBAH M , PHAN-HUY D T , ,et al. Smart radio environments empowered by reconfigurable AI meta-surfaces:an idea whose time has come[J]. EURASIP Journal on Wireless Communications and Networking,2019, 2019:129.
[36]	YOU C S , ZHENG B X , ZHANG R . Channel estimation and passive beamforming for intelligent reflecting surface:discrete phase shift and progressive refinement[J]. IEEE Journal on Selected Areas in Communications, 2020,38(11): 2604-2620.
[37]	ZHENG B X , ZHANG R . Intelligent reflecting surface-enhanced OFDM:channel estimation and reflection optimization[J]. IEEE Wireless Communications Letters, 2020,9(4): 518-522.
[38]	MATTHIESEN B , BJ?RNSON E , DE CARVALHO E ,et al. Intelligent reflecting surface operation under predictable receiver mobility:a continuous time propagation model[J]. IEEE Wireless Communications Letters, 2021,10(2): 216-220.
[39]	KHAWAJA W , GUVENC I , MATOLAK D W ,et al. A survey of air-to-ground propagation channel modeling for unmanned aerial vehicles[J]. IEEE Communications Surveys ＆ Tutorials, 2019,21(3): 2361-2391.
[40]	KHUWAJA A A , CHEN Y F , ZHAO N ,et al. A survey of channel modeling for UAV communications[J]. IEEE Communications Surveys ＆ Tutorials, 2018,20(4): 2804-2821.
[41]	CHENG X , LI Y R , WANG C X ,et al. A 3-D geometry-based stochastic model for unmanned aerial vehicle MIMO ricean fading channels[J]. IEEE Internet of Things Journal, 2020,7(9): 8674-8687.
[42]	JIA H L , CHEN H , WANG S W ,et al. 3D non-stationary unmanned aerial vehicles＆apos; MIMO channel model[J]. IET Communications, 2019,13(18): 2941-2945.
[43]	JIANG H , ZHANG Z C , GUI G . Three-dimensional non-stationary wideband geometry-based UAV channel model for A2G communication environments[J]. IEEE Access, 2019,7: 26116-26122.
[44]	JIANG H , ZHANG Z C , WU L ,et al. Three-dimensional geometry-based UAV-MIMO channel modeling for A2G communication environments[J]. IEEE Communications Letters, 2018,22(7): 1438-1441.
[45]	JIA R B , LI Y R , CHENG X ,et al. 3D geometry-based UAV-MIMO channel modeling and simulation[J]. China Communications, 2018,15(12): 64-74.
[46]	MA Z F , AI B , HE R S ,et al. A wideband non-stationary air-to-air channel model for UAV communications[J]. IEEE Transactions on Vehicular Technology, 2020,69(2): 1214-1226.
[47]	MA Z F , AI B , HE R S ,et al. Impact of UAV rotation on MIMO channel characterization for air-to-ground communication systems[J]. IEEE Transactions on Vehicular Technology, 2020,69(11): 12418-12431.
[48]	CUI Y P , FANG X M , YAN L . Hybrid spatial modulation beamforming for mmWave railway communication systems[J]. IEEE Transactions on Vehicular Technology, 2016,65(12): 9597-9606.
[49]	HEMADEH I A , SATYANARAYANA K , EL-HAJJAR M , ,et al. Millimeter-wave communications:physical channel models,design considerations,antenna constructions,and link-budget[J]. IEEE Communications Surveys ＆ Tutorials, 2017,20(2): 870-913.
[50]	PFADLER A , BALLESTEROS C , ROMEU J ,et al. Hybrid massive MIMO for urban V2I:sub-6 GHz vs mmWave performance assessment[J]. IEEE Transactions on Vehicular Technology, 2020,69(5): 4652-4662.
[51]	YAN L , FANG X M , FANG Y G . Stable beamforming with low overhead for C/U-plane decoupled HSR wireless networks[J]. IEEE Transactions on Vehicular Technology, 2018,67(7): 6075-6086.
[52]	TARIQ M H , CHONDROULIS I , SKARTSILAS P ,et al. MmWave massive MIMO channel measurements for fixed wireless and smart city applications[C]// Proceedings of 2020 IEEE 31st Annual International Symposium on Personal,Indoor and Mobile Radio Communications. Piscataway:IEEE Press, 2020: 1-6.
[53]	HUANG J , WANG C X , FENG R ,et al. Multi-frequency mmWave massive MIMO channel measurements and characterization for 5G wireless communication systems[J]. IEEE Journal on Selected Areas in Communications, 2017,35(7): 1591-1605.
[54]	MORENO GARCIA-LOYGORRI J , BRISO C , ARNEDO I ,et al. Intra-train propagation between 26-40 GHz for 5G applications[C]// Proceedings of 12th European Conference on Antennas and Propagation (EuCAP 2018). Institution of Engineering and Technology, 2018.
[55]	NONAKA N , MURAOKA K , OKUYAMA T ,et al. 28 GHz-band experimental trial at 283 km/h using the shinkansen for 5G evolution[C]// Proceedings of 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring). Piscataway:IEEE Press, 2020: 1-5.
[56]	HE R S , AI B , WANG G P ,et al. High-speed railway communications:from GSM-R to LTE-R[J]. IEEE Vehicular Technology Magazine, 2016,11(3): 49-58.
[57]	LIU Y , WANG C X , LOPEZ C F ,et al. 3D non-stationary wideband tunnel channel models for 5G high-speed train wireless communications[J]. IEEE Transactions on Intelligent Transportation Systems, 2020,21(1): 259-272.
[58]	CHANG Y Y , FURUKAWA M , SUZUKI H ,et al. Propagation analysis with ray tracing method for high speed trains environment at 60 GHz[C]// Proceedings of 2015 IEEE 81st Vehicular Technology Conference (VTC Spring). Piscataway:IEEE Press, 2015: 1-5.
[59]	YANG M , AI B , HE R S ,et al. Machine-learning-based fast angle-of-arrival recognition for vehicular communications[J]. IEEE Transactions on Vehicular Technology, 2021,70(2): 1592-1605.

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场景种类	列车移动性	场景封闭性	信道多径密集程度	用户密度	LOS/NLOS	覆盖形式
高架桥-城区混合场景	高	开放	中等	中等	LOS	室外带状覆盖
路堑-城区混合场景	高	半封闭	高	中等	LOS/NLOS	室外带状覆盖
隧道场景	高	封闭	极高	中等	LOS/NLOS	封闭空间带状覆盖
地上车站场景	低	半封闭	高	高	LOS/NLOS	半封闭空间面状覆盖
地下车站场景	低	封闭	高	高	LOS/NLOS	封闭空间面状覆盖
地表城区场景	高	开放	中等	中等	LOS/NLOS	室外带状覆盖
空-地通信场景	高	开放	低	中等	LOS	室外带状覆盖
列车-列车场景	高	开放/封闭	中等/高/极高	中等	LOS/NLOS	室外带状覆盖

5G urban rail traffic scenario classification and channel modeling

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