Predictions of cloud attenuation models for uplink and downlink margins at ku, ka and v bands in tropical regions

Abstract

Abstract To achieve effective wireless transmission margin and larger bandwidth at lower cost, hydrometeor models roles are of primary importance. The almost perpetual existence of clouds in tropical climates makes cloud models all the more fundamental. Details of four years station spectrum analyzer data, five years climatological data and fifty – eight years radiosonde data used in this research were earlier published. The radiosonde data was used to obtain existing primary cloud models’ predicted cloud attenuation cumulative distributions for the station and it was also used to deduce the new algorithm’s parameters for the station. The every minute measured and logged station cloud attenuation data using spectrum analyzer was used to deduce the station cloud attenuation cumulative distribution for comparison with that of other existing cloud models. The simulation program was run to generate the new cloud attenuation algorithm’s parameters, which defines the cloud attenuation model for the station. Thus the new model only fundamentally requires station radiosonde data. The cloud cover data and all others are needed only for graphical comparisons and corroboration. Thus the new tropical cloud attenuation algorithm can be used to develop the cloud attenuation model for any station climatic zone by using the methodology earlier published. Collected spectrum analyzer data, climatological data and acquired radiosonde data were used to compute projected attenuation values for each cloud attenuation model at propagation signal frequencies between 12 GHz to 50 GHz. The predicted values were extracted and analysed statistically. With respect to frequency, the new cloud attenuation model’s cumulative distribution proportionally averaged the characteristics of the cumulative distributions deduced from the station radiosonde data and that of the spectrum analyzer data as shown by the graphical figures. The results show that convergence of the range of predicted attenuation values by each of the cloud models increases directly with frequency.