Statistical Model of Path Loss for Railway 5G Marshalling Yard Scenario

doi:10.12142/ZTECOM.202303015

ZTE Communications ›› 2023, Vol. 21 ›› Issue (3): 117-122.DOI: 10.12142/ZTECOM.202303015

• Research Papers • Previous Articles

Statistical Model of Path Loss for Railway 5G Marshalling Yard Scenario

DING Jianwen¹, LIU Yao¹(), LIAO Hongjian¹, SUN Bin¹, WANG Wei²

^1.Beijing Jiaotong University, Beijing 100044, China
^2.ZTE Corporation, Shenzhen 518057, China

Received:2022-10-25 Online:2023-09-21 Published:2023-09-21
About author:DING Jianwen received his MS and PhD degrees from Beijing Jiaotong University, China in 2005 and 2019, respectively. He is currently a professor of National Research Center of Railway Safety Assessment, Beijing Jiaotong University. He received the first prize of progress in science and technology of the Chinese Railway Society. His research interests are broadband mobile communications, dedicated mobile communication system for railway, and safety communication technology for train control system.|LIU YAO (21120095@bjtu.edu.cn) received her BE degree in communication engineering from Lanzhou Jiaotong University, 2021, China. She is currently working toward a master’s degree with the State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, China. Her research interests include wireless communications and 5G-R.|LIAO Hongjian received his BE degree in communication engineering from Beijing Jiaotong University, China in 2020. He is currently working toward a master’s degree with the State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, China. His research interests include wireless communications and 5G-R.|SUN Bin received his BS degree in electronic engineering and MS degree in electronic engineering from Beijing Jiaotong University, China in 2004 and 2007, respectively. From 2007 to 2015, he was a R&D manager with BeiJing LiuJie Technology Co., Ltd. He is currently an assistant researcher with National Research Center of Railway Safety Assessment, Beijing Jiaotong University. His main research interest is the interconnection and interworking of core network for dedicated railway mobile communication system.|WANG Wei is the LTE-R technical director and a railway wireless communication system expert of ZTE Corporation, with rich experience of the GSM-R system design. He has a deep understanding of GSM-R and LTE-R and has undertaken several major railway-related projects on wireless communication systems.
Supported by:
the Fundamental Research Funds for the Central Universities(2022JBXT001);NSFC(62171021);the Project of China State Railway Group(P2021G012);ZTE Industry?University?Institute Cooperation Funds(I21L00220)

Abstract

Abstract:

The railway mobile communication system is undergoing a smooth transition from the Global System for Mobile Communications-Railway (GSM-R) to the Railway 5G. In this paper, an empirical path loss model based on a large amount of measured data is established to predict the path loss in the Railway 5G marshalling yard scenario. According to the different characteristics of base station directional antennas, the antenna gain is verified. Then we propose the position of the breakpoint in the antenna propagation area, and based on the breakpoint segmentation, a large-scale statistical model for marshalling yards is established.

Key words: 5G-R, marshalling yard, path loss prediction, statistical modeling

DING Jianwen, LIU Yao, LIAO Hongjian, SUN Bin, WANG Wei. Statistical Model of Path Loss for Railway 5G Marshalling Yard Scenario[J]. ZTE Communications, 2023, 21(3): 117-122.

Figures/Tables 9

Figure 1 2D schematic diagram of directional antenna system

Figure 2 Path loss of 150 cells of the marshalling station

Figure 3 Prediction error statistics of marshalling yard Area A

Figure 4 Fitting two-path model for path loss in marshalling station Area A

Table 1 Correction factors of Hata model in different scenarios

Scenario	Correction Factor $? Δ_{1}$	Correction Factor $? Δ_{2}$
Urban area	-20.47	-1.82
Suburbs	$5.74 l g h_{t} - 30.42$	-6.72
Rural	$6.43 l g h_{t} - 30.44$	-6.71
Viaduct	-21.42	-9.62
Cutting	-18.78	$51.34 l g h_{t} - 78.99$
Station	$34.29 l g h_{t} - 70.75$	-8.86

Table 1 Correction factors of Hata model in different scenarios

Scenario	Correction Factor $? Δ_{1}$	Correction Factor $? Δ_{2}$
Urban area	-20.47	-1.82
Suburbs	$5.74 l g h_{t} - 30.42$	-6.72
Rural	$6.43 l g h_{t} - 30.44$	-6.71
Viaduct	-21.42	-9.62
Cutting	-18.78	$51.34 l g h_{t} - 78.99$
Station	$34.29 l g h_{t} - 70.75$	-8.86

Table 2 Fitting measurement results

Cell Number	Path Loss $P L_{0}$	Path-Loss Exponent n	Correction Factor $Δ_{1}$	Correction Factor $Δ_{2}$
62	4.565 0	4.513 81	-134.29	10.16
63	7.949 0	4.347 35	-131.07	9.25
64	3.651 2	4.358 74	-136.12	8.37
143	-3.014 8	4.542 59	-141.86	10.64
150	-7.115 8	4.472 55	-145.97	9.95
151	-4.066 2	4.482 93	-142.92	10.05
156	-4.460 3	4.442 59	-143.31	9.64
184	-13.105 2	4.438 65	-151.96	9.44
185	0.043 9	4.447 31	-138.89	9.53

Table 2 Fitting measurement results

Cell Number	Path Loss $P L_{0}$	Path-Loss Exponent n	Correction Factor $Δ_{1}$	Correction Factor $Δ_{2}$
62	4.565 0	4.513 81	-134.29	10.16
63	7.949 0	4.347 35	-131.07	9.25
64	3.651 2	4.358 74	-136.12	8.37
143	-3.014 8	4.542 59	-141.86	10.64
150	-7.115 8	4.472 55	-145.97	9.95
151	-4.066 2	4.482 93	-142.92	10.05
156	-4.460 3	4.442 59	-143.31	9.64
184	-13.105 2	4.438 65	-151.96	9.44
185	0.043 9	4.447 31	-138.89	9.53

Figure 5 Results of correction factor?Δ1and LS regression fitting curve

Figure 6 Results of correction factor?Δ2and LS regression fitting curve

Figure 7 Accuracy comparison of different models based on validation data

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Statistical Model of Path Loss for Railway 5G Marshalling Yard Scenario

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