A V2I channel model based on Matérn hard-core Poisson cluster process

Wireless channel modeling plays a critical role in understanding, designing, and optimizing wireless communication systems, serving as an indispensable component in this field. To address the communication requirements in vehicle-to-everything (V2X) environments and investigate the impact of obstacle spatial distribution on channel fading characteristics, this paper proposes a novel stochastic scattering cluster generation algorithm. The algorithm integrates the Matérn hard-core point process and the Poisson cluster process to realistically emulate obstacles in V2X channels. Specifically, the spatial coordinates of scattering clusters are configured based on the spatial distribution of real-world obstacles, while the number of scatterers within each cluster is adaptively determined by the local obstacle density. Leveraging propagation graph theory, the simulation incorporates both line-of-sight (LOS) and single-bounce scattering paths. The channel impulse response (CIR) is utilized to derive key statistical metrics, including the power delay profile (PDP) and Doppler power spectrum density (DPSD). Furthermore, the cumulative distribution function (CDF) of the root mean square (RMS) delay spread under varying vehicular trajectories is analyzed. Additionally, the statistical properties of the Rician K-factor and the power angular spectrum (PAS) are characterized in detail. Simulation results demonstrate that the proposed model effectively captures the time-domain non-stationarity in vehicle-to-infrastructure (V2I) scenarios, offering valuable insights for the design and optimization of V2X communication systems.