A novel analytical model for service delay in IEEE 802.11 networks

Abstract

In this paper, we present a novel analytical model for the service delay in IEEE 802.11 networks. This model is capable of closely tracking service delay's behavior in real wireless local area networks. We find a compact closed-form expression for the probability-generating function (PGF) of service delay using which all higher-order moments are achievable. We begin with finding the service-delay PGF; then we determine the probability density (mass) function of the delay metric by taking the inverse $z$-transform using numerical methods. At last, by comparing the first two statistical moments of this PGF with the mean delay and standard deviation from simulation results, the accuracy of the proposed analytical model is proved.