NAES: Natural Adaptive Exponential Smoothing Algorithm for WLAN Channel Prediction in Mobile Environment

Abstract

The advent of wireless networks has increased the demand for research. Context-aware applications must adapt to the environment in which they are inserted, and, for this, information on both device's hardware and the characteristics of the environment is crucial. In this work, we propose a method - called natural adaptive exponential smoothing algorithm (NAES) - to describe and forecast, in real time, the channel behavior of IEEE 802.11 WLAN networks. The NAES method uses a variation of the exponential smoothing technique to compute the channel quality indicators, namely the signal strength and the link quality. A comparison with the results obtained by other linear prediction methods shows that NAES outperforms them.