An optimal frame size predictor for indoor wireless network

An optimal frame size predictor for an indoor wireless network is studied. A Kalman filter is employed in order to predict optimal frame size. The closed form of state transition equation and observation equations under indoor wireless channel are derived. For analyzing the proposed predictor, a revised wall attenuation factor (WAF) indoor wireless channel model is developed and discussed. Through simulation, it is shown that the proposed algorithm can substantially lower the estimation error by the order of 10². Moreover it is also easy to implement. In the context of optimal frame size prediction, the proposed prediction methodology can be applied to predict other state parameters like receiving power bit error rate etc., and is also applicable to outdoor wireless networks.