A Dynamic Wideband Directional Channel Model for Vehicle-to-Vehicle Communications

Vehicle-to-vehicle (V2V) communications have received a lot of attention due to their numerous applications in traffic safety. The design, testing, and improvement of the V2V system hinge critically on the understanding of the propagation channels. An important feature of the V2V channel is the time...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) 2015-12, Vol.62 (12), p.7870-7882
Main Authors: Ruisi He, Renaudin, Olivier, Kolmonen, Veli-Matti, Haneda, Katsuyuki, Zhangdui Zhong, Bo Ai, Oestges, Claude
Format: Article
Language:English
Subjects:
Accuracy
Antenna arrays
Azimuth
Channel models
Computational modeling
Delays
dynamic model
Indexes
MPC lifetime
Vehicle dynamics
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Summary:Vehicle-to-vehicle (V2V) communications have received a lot of attention due to their numerous applications in traffic safety. The design, testing, and improvement of the V2V system hinge critically on the understanding of the propagation channels. An important feature of the V2V channel is the time variance. To statistically model the time-variant V2V channels, a dynamic wideband directional channel model is proposed in this paper, based on measurements conducted at 5.3 GHz in suburban, urban, and underground parking environments. The model incorporates both angular and delay domain properties and the dynamic evolution of multipath components (MPCs). The correlation matrix distance is used to determine the size of local wide-sense stationary (WSS) region. Within each WSS time window, MPCs are extracted using the Bartlett beamformer. A multipath distance-based tracking algorithm is used to identify the "birth" and "death" of such paths over different stationarity regions, and the lifetime of MPC is modeled with a truncated Gaussian distribution. Distributions for the number of multipaths and their positions are statistically modeled. Within each path lifetime, the initial power is found to depend on the excess delay, and a linear polynomial function is used to model the variations within the lifetime. In addition, a Nakagami distribution is suggested to describe the fading behavior. Finally, the model implementation is validated by comparison of second-order statistics between measurements and simulations.
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2015.2459376