PERFORMANCE IMPROVEMENT OF INTELLIGENT WEATHER SYSTEM

Prediction of channel characteristics can be of immense value in improving the quality of signals in high frequency satellite systems. Atmospheric properties like rain, snow, gaseous, cloud, fog, scintillation can have a distorting effect on signal fidelity of Ku and Ka bands, thus resulting in excessive digital transmission error. This loss of signal is commonly referred to as signal attenuation. Signal attenuation impacts the QoS in wireless and satellite networks. Accurately predicting channel attenuation due to atmospheric conditions can enable mitigation planning by adaptively selecting appropriate modulation, coding, transmitted power level, transmission rate and configured frame size. The aim of this paper is to estimate different attenuations using predicted signal-weather correlated database in collaboration with ITU-R propagation models combined with interpolation methods, gateway, and ground terminal characteristics. An intelligent decision support system is used for accurately calculating the attenuations. In this project we are calculating rain attenuation. The fuzzy logic is added into the system. The fuzzy system will determine the ambiguous signal during the attenuation performed.