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

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

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 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.

Details

Authors
Organisations
External organisations
  • Halmstad University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Communication Systems
Original languageEnglish
Title of host publication2018 IEEE 87th Vehicular Technology Conference, VTC Spring 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
Volume2018-June
ISBN (Electronic)9781538663554
Publication statusPublished - 2018 Jul 20
Publication categoryResearch
Peer-reviewedYes
Event87th IEEE Vehicular Technology Conference, VTC Spring 2018 - Porto, Portugal
Duration: 2018 Jun 32018 Jun 6

Publication series

NameVehicular Technology Conference
ISSN (Electronic)2577-2465

Conference

Conference87th IEEE Vehicular Technology Conference, VTC Spring 2018
CountryPortugal
CityPorto
Period2018/06/032018/06/06