Geometry-based stochastic modeling and estimation of vehicle to vehicle channels

In this paper, a geometry-based stochastic channel model (GSCM) for vehicle-to-vehicle (V2V) wireless communication is developed. The channel model reveals that the channel representation in delay-Doppler domain can be divided into four regions. In each region, the V2V channel can be modeled using a hybrid sparse/diffuse (HSD) model. Prior art on hybrid channel estimation for linear time-invariant channels is extended to the time-varying case. Furthermore, the effects of pulse shape leakage are explicitly determined and compensated. Simulation results shows that exploiting the V2V channel properties in the delay-Doppler domain, yields significantly improved channel estimates over unstructured approaches (more than 10dB gain in SNR).