Minimizing Wi-Fi Latency With Unlicensed LTE Opportunistic White-Space Utilization

Abstract

We develop an analytical framework to model the temporal characteristics of Wi-Fi channel statistics, particularly, the duration of white spaces resulting from idle periods in Wi-Fi traffic. We employ a bivariate Markov process that captures the underlying dynamics of Wi-Fi network in formulating group Poisson arrivals corresponding to aggregated Wi-Fi frames and determine the parameters of this Markov modulated batch Poisson process by matching the associated first-order traffic arrival statistics. While this model is drastically simpler than others such as BMAP, nevertheless, it provides remarkably similar accuracy in modeling the white spaces. The results from analytical models are corroborated with those of the simulation platform we developed in NS3. Next, we use this model to study the feasibility of exploiting Wi-Fi white spaces for unlicensed LTE (U-LTE) transmissions. We further propose an opportunistic coexistence algorithm that enables the U-LTE base station to dynamically estimate the duration of upcoming Wi-Fi white spaces and determine the U-LTE ON/OFF epochs. The proposed scheme demonstrates performance limits when the latency imposed on Wi-Fi activity is minimized, while U-LTE maximally utilizes the available spectral resources. A useful application of this model is when integrated with stochastic geometry to form a basis for optimal resource allocation in 5G small cells to guarantee network quality of service and low latency.