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

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.