Statistical Characterization of WiFi White Space

This letter presents an analytical framework based on Markov modulated batch Poisson processes for stochastic modeling of WiFi temporal activity and its idle gaps, or white spaces. The proposed model takes into account the dynamic and bursty nature of WiFi traffic to mathematically characterize the duration and the frequency of occurrence of white spaces in unlicensed bands. Closed-form expressions as well as simple approximations are derived. Numerical results demonstrate the accuracy of the model, along with the plenitude of the spectral resources in an arbitrary WiFi network that may be exploited opportunistically, with minimum impact on WiFi activity.