Gaussian Random Fields as a Model for Spatially Correlated Log-Normal Fading

Slow fading or shadowing on a wireless channel is commonly modeled by stochastically independent, log-normally distributed random variables. However, as slow fading is caused by buildings and large size obstacles, spatial correlations occur. In this paper, Gaussian random fields are used as a model for correlated slow fading in urban environments. An exponential correlation function is employed. The according parameters are estimated from path gain predictions by an accurate ray-optical propagation algorithm, named CORLA. Furthermore, a multidimensional model is suggested to describe correlated shadowing of the path gains from different base stations to a single receiver.