Statistical channel modelling of dynamic vehicular visible light communication system

被引:13
|
作者
Alsalami, Farah Mahdi [1 ]
Ahmad, Zahir [2 ]
Zvanovec, Stanislav [3 ]
Haigh, Paul Anthony [4 ]
Haas, Olivier C. L. [1 ]
Rajbhandari, Sujan [5 ]
机构
[1] Coventry Univ, Inst Future Transport & Cities, Coventry CV1 5FB, W Midlands, England
[2] Coventry Univ, Fac Engn Environm & Comp, Coventry CV1 5FB, W Midlands, England
[3] Czech Tech Univ, Dept Elect Field, Fac Elect Engn, Tech 2, Prague 16627, Czech Republic
[4] Newcastle Univ, Intelligent Sensing & Commun Grp, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England
[5] Huawei Technol Sweden AB, Gothenburg, Sweden
关键词
Vehicular communication; Visible Light Communication (VLC); Outdoor channel model; Statistical channel model;
D O I
10.1016/j.vehcom.2021.100339
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
This paper studies a statistical channel model for dynamic vehicular visible light communication systems. The proposed model considers the effect of variation in inter-vehicular spacing and the geometrical changes on path loss of the channel. The study also considers different weather conditions and vehicle mobility based on a realistic traffic flow model that considers traffic density during different times of the day. Monte Carlo simulation is used to examine the obtained statistical model for different transmission scenarios. In addition, the Kolmogorov-Smirnov test for the statistical model and Monte Carlo simulation has been performed to verify that they represent the same distribution. The results show that the channel statistical distribution varies with the traffic flow and inter-vehicular spacing, which changes at different times of the day. The results also show that the path loss values of the non-line-of-sight component are significantly larger than the path loss values of the line-of-sight component of the channel when a single reflector is considered. However, at rush hours, when inter-vehicle spacing becomes shorter, the path loss value of multiple reflections decreases significantly. (C) 2021 Elsevier Inc. All rights reserved.
引用
收藏
页数:12
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