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Open Access

Modeling and Simulation of Packet Delivery Rate in LTE-V Network Based on Markov Chain

Department of Automation, Tsinghua University, Beijing 100084, China
Beijing Nebula Link Technology Co. Ltd., Beijing 100080, China.
School of Airport Engineering and Transportation Management, Civil Aviation Flight University of China, Guanghan 618300, China.
Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
Tsinghua-Berkeley Shenzhen Institute (TBSI), Shenzhen 518055, China
Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China.
China Unicom Network Technology Research Institute, Beijing 100091, China.
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Abstract

As one of the most promising communication technologies for vehicular networks, LTE-V has the advantages of wide coverage and a high transmission rate. 3GPP released the technical specification of LTE-V in March 2017, launching a spate of related research and industrialization. In this paper, we propose a communication model based on Markov process to evaluate the reliability of LTE-V. We derived the Packet Delivery Rate (PDR) of LTE-V based on the model. Moreover, we use Poisson process to model the distribution of vehicles on a highway, then combine the communication model with the vehicles’ distribution to derive the PDR under this scenario. To verify the correctness of the proposed model, we established a simulation program on the MATLAB platform. By comparing the simulation results and the mathematical results, we found that simulation results are a very good fit for the model.

Keywords

Vehicle-to-everything (V2X)LTE-Vvehicle infrastructure cooperation systempacket delivery rate

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Tsinghua Science and Technology
Volume 25 Issue 3,
June 2020
Pages 357-367
DOI: 10.26599/TST.2018.9010142
Cite this article:
Shi M, Tang Y, Zhang X, et al. Modeling and Simulation of Packet Delivery Rate in LTE-V Network Based on Markov Chain. Tsinghua Science and Technology, 2020, 25(3): 357-367. https://doi.org/10.26599/TST.2018.9010142

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Received: 31 October 2018
Revised: 29 November 2018
Accepted: 11 December 2018
Published: 07 October 2019
© The author(s) 2020

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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