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Geometry based channel models with cross- and autocorrelation for vehicular network simulations

Nelson, Christian LU ; Lyamin, Nikita; Vinel, Alexey; Gustafson, Carl LU and Tufvesson, Fredrik LU (2018) 87th IEEE Vehicular Technology Conference, VTC Spring 2018 In Vehicular Technology Conference 2018-June. p.1-5
Abstract

Realistic network simulations are necessary to assess the performance of any communication system. In this paper, we describe an implementation of a channel model for vehicle-to-vehicle (V2V) communication in the OMNeT++/Plexe simulation environment. The model is based on previous extensive measurements in a V2V multilink highway scenario and cover line-of-sight (LOS) as well as obstructed LOS (OLOS) scenarios, which occurs when one or more vehicles obstruct the LOS component. The implementation captures both the temporal autocorrelation and the joint multilink cross-correlation processes to achieve a realistic behavior. Preliminary results show that the implementation now generates stochastic large-scale fading with an autocorrelation... (More)

Realistic network simulations are necessary to assess the performance of any communication system. In this paper, we describe an implementation of a channel model for vehicle-to-vehicle (V2V) communication in the OMNeT++/Plexe simulation environment. The model is based on previous extensive measurements in a V2V multilink highway scenario and cover line-of-sight (LOS) as well as obstructed LOS (OLOS) scenarios, which occurs when one or more vehicles obstruct the LOS component. The implementation captures both the temporal autocorrelation and the joint multilink cross-correlation processes to achieve a realistic behavior. Preliminary results show that the implementation now generates stochastic large-scale fading with an autocorrelation function that agrees well with measured data. A representation of the cross-correlation process is now implemented through proper channel model selection since the geometry and location of objects are known in Plexe. We also show the impact of the suggested V2V physical layer (PHY) on the performance evaluation results observed at the facilities layer. As a metric, we use the data age, which is a measure how old the information about a vehicle is. When considering the autocorrelation in simulations, the experienced data-age increases. Examples show an increase of the 10% percentile data-age from 0.1s to 1.5s, which may affect the application performance significantly in critical situations.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2018 IEEE 87th Vehicular Technology Conference, VTC Spring 2018 - Proceedings
series title
Vehicular Technology Conference
volume
2018-June
pages
5 pages
publisher
Institute of Electrical and Electronics Engineers Inc.
conference name
87th IEEE Vehicular Technology Conference, VTC Spring 2018
conference location
Porto, Portugal
conference dates
2018-06-03 - 2018-06-06
external identifiers
  • scopus:85050983616
ISSN
2577-2465
ISBN
9781538663554
DOI
10.1109/VTCSpring.2018.8417740
language
English
LU publication?
yes
id
41b9899f-ab44-43fc-926d-f88d4b3e5a7b
date added to LUP
2018-08-21 10:59:50
date last changed
2018-11-21 21:41:11
@inproceedings{41b9899f-ab44-43fc-926d-f88d4b3e5a7b,
  abstract     = {<p>Realistic network simulations are necessary to assess the performance of any communication system. In this paper, we describe an implementation of a channel model for vehicle-to-vehicle (V2V) communication in the OMNeT++/Plexe simulation environment. The model is based on previous extensive measurements in a V2V multilink highway scenario and cover line-of-sight (LOS) as well as obstructed LOS (OLOS) scenarios, which occurs when one or more vehicles obstruct the LOS component. The implementation captures both the temporal autocorrelation and the joint multilink cross-correlation processes to achieve a realistic behavior. Preliminary results show that the implementation now generates stochastic large-scale fading with an autocorrelation function that agrees well with measured data. A representation of the cross-correlation process is now implemented through proper channel model selection since the geometry and location of objects are known in Plexe. We also show the impact of the suggested V2V physical layer (PHY) on the performance evaluation results observed at the facilities layer. As a metric, we use the data age, which is a measure how old the information about a vehicle is. When considering the autocorrelation in simulations, the experienced data-age increases. Examples show an increase of the 10% percentile data-age from 0.1s to 1.5s, which may affect the application performance significantly in critical situations.</p>},
  author       = {Nelson, Christian and Lyamin, Nikita and Vinel, Alexey and Gustafson, Carl and Tufvesson, Fredrik},
  booktitle    = {Vehicular Technology Conference},
  isbn         = {9781538663554},
  issn         = {2577-2465},
  language     = {eng},
  location     = {Porto, Portugal},
  month        = {07},
  pages        = {1--5},
  publisher    = {Institute of Electrical and Electronics Engineers Inc.},
  title        = {Geometry based channel models with cross- and autocorrelation for vehicular network simulations},
  url          = {http://dx.doi.org/10.1109/VTCSpring.2018.8417740},
  volume       = {2018-June},
  year         = {2018},
}