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Vehicle-to-vehicle (V2V) wireless communications can improve traffic safetyat road intersections and enable congestion avoidance. However, detailedknowledge about the wireless propagation channel is needed for the developmentand realistic assessment of V2V communication systems. We present a novelgeometry-based stochastic MIMO channel model with support for frequencies inthe band of 5.2-6.2 GHz. The model is based on extensive high-resolutionmeasurements at different road intersections in the city of Berlin, Germany. Weextend existing models, by including the effects of various obstructions,higher order interactions, and by introducing an angular gain function for thescatterers. Scatterer locations have been identified and mapped to measuredmulti-path trajectories using a measurement-based ray tracing method and asubsequent RANSAC algorithm. The developed model is parameterized, and usingthe measured propagation paths that have been mapped to scatterer locations,model parameters are estimated. The time variant power fading of individualmulti-path components is found to be best modeled by a Gamma process with anexponential autocorrelation. The path coherence distance is estimated to be inthe range of 0-2 m. The model is also validated against measurement data,showing that the developed model accurately captures the behavior of themeasured channel gain, Doppler spread, and delay spread. This is also the casefor intersections that have not been used when estimating model parameters.

The COST IRACON Geometry-based Stochastic Channel Model for Vehicle-to-Vehicle Communication in Intersections