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International Journal of Antennas and Propagation
Volume 2017, Article ID 3098198, 12 pages
Research Article

Research on Spatial Channel Model for Vehicle-to-Vehicle Communication Channel in Roadside Scattering Environment

1Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai 200444, China
2Department of Electrical and Computer Engineering, University of Michigan-Dearborn, Dearborn, MI 48128, USA
3School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Correspondence should be addressed to Yong Fang; nc.ude.uhs.ffats@gnafy

Received 9 June 2017; Revised 2 September 2017; Accepted 19 September 2017; Published 22 October 2017

Academic Editor: Matteo Pastorino

Copyright © 2017 Xin Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In this paper, an extension of spatial channel model (SCM) for vehicle-to-vehicle (V2V) communication channel in roadside scattering environment is investigated for the first time theoretically and by simulations. Subsequently, to efficiently describe the roadside scattering environment and reflect the nonstationary properties of V2V channels, the proposed SCM V2V model divides the scattering objects into three categories of clusters according to the location of effective scatterers by introducing critical distance. We derive general expressions for the most important statistical properties of V2V channels, such as channel impulse response, power spectral density, angular power density, autocorrelation function, and Doppler spread of the proposed model. The impact of vehicle speed, traffic density, and angle of departure, angle of arrival, and other statistical performances on the V2V channel model is thoroughly discussed. Numerical simulation results are presented to validate the accuracy and effectiveness of the proposed model.