Estimation of the Number of Competing Stations Applied with Central Difference Filter for an IEEE 802.11 Network

Abstract

The ubiquitous computing environments requires integration of a variety of current and future wired and wireless networking technologies to support seamless computing and communication environments for user applications. WLAN also need to be a part of a seamless communication infrastructure, as they can be used either as a wireless extension of wired networks or peer-to-peer networks. This paper proposes a new methodology to estimate the number of competing stations in an IEEE 802.11 network. Due to nonlinear nature of measurement model, an iterative nonlinear filtering algorithm, called the “Central Difference Filter” (CDF), is employed. The CDF can provide a better alternative to nonlinear filtering than the conventional extended Kalman filter (EKF) since it avoids errors associated with linearization. This approach shows both high accuracy as well as prompt reactivity to changes in the network occupancy status. Specially, our proposed algorithm is more improved performance in non saturated conditions than the EKF. Numerical results show that it provides a more viable means for estimation of the number of competing stations in IEEE 802.11 network than estimators based on the EKF.