Intelligent Weather Aware Scheme for Satellite Systems

Rain, snow, gaseous, cloud, fog, scintillation and other atmospheric properties 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. A three dimensional relationship is proposed among these attenuations with respect to propagation angle and rainfall rate [l]-[8]. The outcome is key factor in diagnosing, adjusting and improving satellite signal power, modulation and coding schemes, monitored and controlled altogether by a powerful and efficient intelligent-based attenuation countermeasure system. These results will lead to an enhanced back propagation-learning algorithm that is used to iteratively tune the IS with returned SNR values to activate the weighted Modulation/Codepoint to its optimal values, depending on actual or predicted weather conditions, configuration settings and tolerance/safety margins for SLA commitment.