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

## TL;DR

This paper introduces a new geometry-based stochastic MIMO channel model for V2V communication at intersections, based on extensive measurements and advanced ray tracing, improving the accuracy of wireless channel simulations in urban scenarios.

## Contribution

The paper extends existing V2V channel models by incorporating obstructions, higher order interactions, and an angular gain function, validated with real-world measurements at intersections.

## Key findings

- Model accurately predicts channel gain, Doppler, and delay spread.
- Path coherence distance estimated at 0-2 meters.
- Validated across multiple intersection scenarios.

## Abstract

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