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Analytical Model and Performance Evaluation of Long-Term Evolution for Vehicle Safety Services

Publication ,  Journal Article
Li, W; Ma, X; Wu, J; Trivedi, KS; Huang, XL; Liu, Q
Published in: IEEE Transactions on Vehicular Technology
March 1, 2017

In a traffic jam or dense vehicle environment, vehicular ad hoc networks (VANETs) cannot meet the safety requirement due to serious packet collisions. The traditional cellular network solves packet collisions but suffers from long end-to-end delay. Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) overcomes both drawbacks; thus, it may be used, instead of VANETs, in some extreme environments. We use Markov models with dynamic scheduling and semipersistent scheduling (SPS) to evaluate how many idle resources of LTE can be provided for safety services and how safety applications impact LTE traditional users. Based on the analysis, we propose to reserve the idle radio resources in LTE for vehicular safety services (LTE-V). Additionally, we propose the weighted-fair-queuing (WFQ) algorithm to schedule beacons for safety services using the LTE reserved resources. Numerical results verify that the proposed mechanism can significantly improve the reliability of safety applications by borrowing limited LTE bandwidth. We also build an NS3 simulation platform to verify the effectiveness of the proposed Markov models. Finally, the reliability of applications, including cooperation collision warning (CCW), slow vehicle indication (SVI), and rear-end collision warning (RCW), using dedicated short-range communication (DSRC) with LTE-V, are evaluated. The simulation results demonstrate that the stringent quality-of-service (QoS) requirement of the aforementioned three applications can be satisfied, even under heavy traffic.

Duke Scholars

Published In

IEEE Transactions on Vehicular Technology

DOI

ISSN

0018-9545

Publication Date

March 1, 2017

Volume

66

Issue

3

Start / End Page

1926 / 1939

Related Subject Headings

  • Automobile Design & Engineering
  • 46 Information and computing sciences
  • 40 Engineering
  • 10 Technology
  • 09 Engineering
  • 08 Information and Computing Sciences
 

Citation

APA
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ICMJE
MLA
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Li, W., Ma, X., Wu, J., Trivedi, K. S., Huang, X. L., & Liu, Q. (2017). Analytical Model and Performance Evaluation of Long-Term Evolution for Vehicle Safety Services. IEEE Transactions on Vehicular Technology, 66(3), 1926–1939. https://doi.org/10.1109/TVT.2016.2580571
Li, W., X. Ma, J. Wu, K. S. Trivedi, X. L. Huang, and Q. Liu. “Analytical Model and Performance Evaluation of Long-Term Evolution for Vehicle Safety Services.” IEEE Transactions on Vehicular Technology 66, no. 3 (March 1, 2017): 1926–39. https://doi.org/10.1109/TVT.2016.2580571.
Li W, Ma X, Wu J, Trivedi KS, Huang XL, Liu Q. Analytical Model and Performance Evaluation of Long-Term Evolution for Vehicle Safety Services. IEEE Transactions on Vehicular Technology. 2017 Mar 1;66(3):1926–39.
Li, W., et al. “Analytical Model and Performance Evaluation of Long-Term Evolution for Vehicle Safety Services.” IEEE Transactions on Vehicular Technology, vol. 66, no. 3, Mar. 2017, pp. 1926–39. Scopus, doi:10.1109/TVT.2016.2580571.
Li W, Ma X, Wu J, Trivedi KS, Huang XL, Liu Q. Analytical Model and Performance Evaluation of Long-Term Evolution for Vehicle Safety Services. IEEE Transactions on Vehicular Technology. 2017 Mar 1;66(3):1926–1939.

Published In

IEEE Transactions on Vehicular Technology

DOI

ISSN

0018-9545

Publication Date

March 1, 2017

Volume

66

Issue

3

Start / End Page

1926 / 1939

Related Subject Headings

  • Automobile Design & Engineering
  • 46 Information and computing sciences
  • 40 Engineering
  • 10 Technology
  • 09 Engineering
  • 08 Information and Computing Sciences