Brummer A, Gütlein M, Schäfer M, German R, Djanatliev A (2020)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2020
Publisher: IEEE
City/Town: Virtual Conference
Pages Range: 1--8
Conference Proceedings Title: Proceedings of the 12th IEEE Vehicular Networking Conference (VNC 2020)
Event location: Virtual Conference
ISBN: 978-1-7281-9221-5
DOI: 10.1109/VNC51378.2020.9318362
In this paper, we evaluate the n-ray ground interference model based on field experiments. The n-ray model is an extension of the popular two-ray interference model for three-dimensional Vehicular Ad Hoc Network (VANET) simulation. Using commodity hardware, we measure the path loss on nine selected test tracks and replay the scenarios simulatively to compare it to the simulated path loss resulting from the n-ray model. The simulation results are in good agreement with the measurements for the most parts in all nine cases, indicating that the n-ray ground interference model is able to capture the effect of ground reflections for arbitrary terrain shapes. The two-ray interference model fails to do so as it neglects elevation information. Moreover, the dependence of the results on the parameterization of the model as well as on the horizontal resolution of the underlying elevation dataset is investigated. In order to ensure that the n-ray model is only applied under Line of Sight (LOS) conditions, we further present a possible combination with our environmental diffraction model.
APA:
Brummer, A., Gütlein, M., Schäfer, M., German, R., & Djanatliev, A. (2020). Experimental Evaluation of the N-Ray Ground Interference Model. In Proceedings of the 12th IEEE Vehicular Networking Conference (VNC 2020) (pp. 1--8). Virtual Conference: Virtual Conference: IEEE.
MLA:
Brummer, Alexander, et al. "Experimental Evaluation of the N-Ray Ground Interference Model." Proceedings of the 12th IEEE Vehicular Networking Conference (VNC 2020), Virtual Conference Virtual Conference: IEEE, 2020. 1--8.
BibTeX: Download