A Novel Non-WSSUS Statistical Model of Vehicle-Vehicle Radio Channel for the 5-GHz Band

  • Tao HeEmail author
  • Ye Jin
  • Weiting Fu
  • Mingshuang Lian
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 262)


In recent years, with the dramatic development in intelligent transportation systems (ITS), vehicle-vehicle (V2V) radio channel models have drawn much attention. With the analysis of the preceding statistical models of V2V channel, it is obvious that the critical works in developing statistical channel models focus on two aspects, the modeling of the time-variant properties and the modeling of the severe multipath fading. In this paper, we discuss an innovative method to model the fading dispersive channels that do not satisfy the assumption of wide-sense stationary uncorrelated scattering (WSSUS). And the Weibull distribution is integrated to mimic the severe multipath fading of V2V radio channel. Moreover, based on the tapped-delay like (TDL) model, the non-WSSUS channel impulse response (CIR) function has been formulated. There are several statistical properties characterized to evaluate the performance of the proposed model, such as, Power delay profile (PDP), Temporal autocorrelation function (ACF), Local scattering function (LSF) and Power spectrum density (PSD). The simulation results demonstrate that the proposed model has a good performance in the characterization of the non-WSSUS V2V radio channel. Hence, the channel model presented will be beneficial in future V2V communications systems.


V2V radio channel models Non-stationary Correlated scattering Weibull fading Statistical model 


  1. 1.
    Borhani, A., Stuber, G.L., Patzold, M.: A random trajectory approach for the development of nonstationary channel models capturing different scales of fading. IEEE Trans. Veh. Technol. 66(1), 2–14 (2017)CrossRefGoogle Scholar
  2. 2.
    Jiang, D., Delgrossi, L.: EEE 802.11p: Towards an International Standard for Wireless Access in Vehicular Environments, pp. 2036–2040 (2008)Google Scholar
  3. 3.
    Dahech, W., Patzold, M., Gutierrez, C.A., Youssef, N.: A non-stationary mobile-to-mobile channel model allowing for velocity and trajectory variations of the mobile stations. IEEE Trans. Wirel. Commun. 16(3), 1987–2000 (2017)CrossRefGoogle Scholar
  4. 4.
    Patzold, M., Gutierrez, C.A., Youssef, N.: On the consistency of non-stationary multipath fading channels with respect to the average doppler shift and the doppler spread. In: Wireless Communications and Networking Conference (WCNC), pp. 1– 6.D. San Francisco, USA (2017)Google Scholar
  5. 5.
    Wang, C., Cheng, X., Laurenson, D.: Vehicle-to-Vehicle Channel Modeling and Measurements: Recent Advances and Future Challenges. pp. 96–103 (2009)Google Scholar
  6. 6.
    Ghazal, A., Yuan, Y., Wang, C-X., Zhang, Y., Yao, Q., Zhou, H., Duan, W.: A non-stationary IMT-advanced MIMO channel model for high-mobility wireless communication systems. IEEE Trans. Wirel. Commun. 16(4) (2017)CrossRefGoogle Scholar
  7. 7.
    IEEE Computer Society.: Standard for wireless local area networks providing wireless communications while in vehicular environment. IEEE P802.11p/D2.01 (2007)Google Scholar
  8. 8.
    Acosta-Marum, G., Ingram, M.A.: Six time- and frequency- selective empirical channel models for vehicular wireless LANs. IEEE Veh. Technol. Mag. 2(4), 4–11 (2007)CrossRefGoogle Scholar
  9. 9.
    Chen, B., Zhong, Z., Ai, B.: Stationarity intervals of time-variant channel in high speed railway scenario. China Commun. 9(8), 64–70 (2012)Google Scholar
  10. 10.
    Sen, I., Matolak, D.W.: Vehicle–vehicle channel models for the 5-GHz band. IEEE Trans. Intell. Transp. Syst. 9(2), 235–245 (2008)CrossRefGoogle Scholar
  11. 11.
    Matz, G.: On non-WSSUS wireless fading channels. IEEE Trans. Wireless Commun. 4(5), 2465–2478 (2005)CrossRefGoogle Scholar
  12. 12.
    Zajic, A.G., Stuber, G.L.: Space-time correlated mobile-to-mobile channels: modelling and simulation. IEEE Trans. Veh. Technol. 57(2), 715–726 (2008)CrossRefGoogle Scholar
  13. 13.
    Sen, I., Matolak, D.W.: Vehicle-vehicle channel models for the 5-GHz band. IEEE Trans. Intell. Transp. Syst. 9(2), 235–245 (2008)CrossRefGoogle Scholar
  14. 14.
    Matolak., Sen, I., Xiong, W.: Channel modeling for V2V communications. In: Proceedings of the V2VCOM Workshop, San Jose (2006)Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.Peking UniversityHaidian District, BeijingPeople’s Republic of China
  2. 2.China University of GeosciencesHaidian District, BeijingPeople’s Republic of China

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