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Vehicle-to-vehicle (V2V) communications have received a lot of attention as it can significantly improve efficiency and safety of road traffic. In general, V2V scenarios have some special features such as high mobility of transceivers, low antenna height, and small communication ranges, which significantly affect the propagation characteristics. Therefore, an accurate channel model is required to characterize V2V propagation channel. However, some important features of V2V channels have not been well characterized, for example, most existing V2V channel models tend to only consider the distribution of multipath components (MPCs) in a horizontal dimension, whereas ignoring vertical dimension, which is inconsistent with the distribution of MPCs in the actual channel. Moreover, the dynamic clusters of MPCs have not been well modeled in the existing V2V models. Therefore, in order to better model the V2V channel, a cluster-based three-dimensional (3D) channel model is proposed in this paper, which is based on the measurements conducted at 5.9 GHz in urban and suburban scenarios. In the proposed model, the distribution of MPCs clusters in both horizontal and vertical dimensions is considered. The space-alternating generalized expectation-maximization algorithm is used to extract MPCs, and the clustering and tracking algorithms are used to identify and track the clusters of dynamic MPCs. In the proposed model, all MPC clusters are divided into two categories: global-clusters and scatterer-clusters, and the distribution of the two clusters are characterized by a series of inter- and intra-cluster parameters. It is found that both the azimuth spread and the elevation spread follow the lognormal distribution. In addition, the power of MPCs within a cluster has the truncated-Gaussian distribution, whereas the angle of MPCs within a cluster has the Laplacian distribution. Finally, the accuracy of the model is verified by comparing the measurements and simulations.
Yang et al. (Thu,) studied this question.