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Advances in Communications-Based Train Control Systems by F. Richard Yu

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65
Chapter 4
Modeling of the
Wireless Channels in
Underground Tunnels for
Communications-Based
Train Control Systems
Hongwei Wang, F. RichardYu,Li Zhu,
and Tao Tang
Contents
4.1 Introduction .............................................................................................. 66
4.2 Real Field CBTC Channel Measurements .................................................67
4.2.1 Measurement Equipment ................................................................ 67
4.2.2 Measurement Scenario ....................................................................68
4.3 Finite-State Markov Chain Channel Model ...............................................69
4.3.1 FSMC Model ..................................................................................69
4.3.2 Determine the SNR-Level resholds of the FSMC Model ............72
4.3.3 Determine the Distribution of SNR ...............................................74
4.4 Real Field Measurement: Results and Discussions ......................................76
4.5 Conclusion .................................................................................................79
References ...........................................................................................................79
66 Advances in Communications-Based Train Control Systems
4.1 Introduction
Building a trainground wireless communication system for communications-
based train control (CBTC) is a challenging task. As urban rail transit systems are
mostly deployed in underground tunnels, there are a large amount of reections,
scattering, and barriers that severely aect the propagation performance of wireless
communications. Moreover, due to the available commercial o-the-shelf equip-
ment, wireless local area networks (WLANs) are often adopted as the main method
of trainground communications for CBTC systems. However, most of the cur-
rent IEEE 802.11 WLAN standards are not originally designed for the high-speed
environment in tunnels [1]. Furthermore, the fast movement of trains will cause
frequent handos between WLAN access points (APs), which can severely aect
the CBTC performance.
Modeling the channels of urban rail transit systems is very important to design
the wireless networks and evaluate the performance of CBTC systems. ere are
some previous works on radio wave propagation in urban rail transit systems.
Apath loss model of tunnel channels is given in [2], which describes the character-
istics of the large-scale fading. e authors of [3] present the propagation charac-
teristics based on real environment measurements in Madrid subway. A two-layer
multistate Markov model is presented in [4] for modeling a 1.8 GHz channel in
urban Taipei city. Based on the Winner II physical layer channel model parameters,
the authors of [5] propose a channel model for high-speed railway.
Although some excellent works have been done on modeling channels, most
of them do not consider the unique characteristics of CBTC systems, such as high
mobility speed, deterministic moving direction, and accurate train location infor-
mation. In this chapter, we develop a nite-state Markov channel (FSMC) model
for tunnel channels in CBTC systems. FSMC models have been widely accepted in
the literature as an eective approach to characterize the correlation structure of the
fading process, including 1.8 GHz narrow-band channels [4], high-speed railway
channels [5], satellite channels [6], indoor channels [7], Rayleigh fading channels
[8], Rician fading channels [9], and Nakagami fading channels [10]. Using FSMC
models, a variety of analytical results of system performance can be derived, includ-
ing channel capacity [11], throughput [12], and packet error distribution [13].
To the best of our knowledge, FSMC models for tunnel channels in CBTC
systems have not been studied in previous works. erefore, there is a strong moti-
vation to develop an FSMC model for tunnel channels in CBTC systems. Some
distinct features of the proposed channel model are as follows:
e proposed FSMC model is based on real eld CBTC channel measure-
ments obtained from the business operating Beijing Subway Changping Line.
Unlike most existing channel models, which do not use train location infor-
mation, the proposed FSMC channel model takes train locations into account
to have a more accurate channel model.

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