NAES: A Natural Adaptive Exponential Smoothing for Channel Prediction in WLANs

Abstract

The advent of wireless networks has increased the demand for research greatly. 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 (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 received signal strength (RSS) and the link quality. A comparison with the results obtained by the Trigg and Leach (1967)(TL) method shows that NAES outperforms TL method.