A Stochastic Model for Non-Stationary Outdoor K-Factor Variation

A dense urban cellular environment contains many different locations where a line-of-sight or specular signal component from the base station is present. The small scale fading at these locations is best characterized using the Ricean distribution. However, the K-factor of that distribution will vary from one location to the next. This paper presents a statistical model for dense urban vehicular non-stationary Ricean fading where K- factor changes gradually due to movement through changing surroundings. Using analysis of empirical radio channel measurements, a model is developed to represent K-factor variation as a stochastic process. An auto-regressive (AR) model is used to ensure the autocorrelation of the simulated K-factor process matches the empirical data. The model is verified by using it to simulate a non-stationary Ricean small scale fading envelope and comparing it to the fading envelope seen in the measurements.