Browsing by Author "Akinyemi, M. I."

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    Global Transmission Margins Determination and Cloud Attenuation Models at Satellite Bands
    (Scientific Research, New Technologies and Applications Vol. 7, 2024) Adewusi, O. M.; Ometan, O. O.; Akinwumi, S. A.; Omotosho, T. V.; Akinyemi, M. I.
    Considering the fact that various dimensions of disturbances occur in the atmospheric layers randomly, which often have consequential footprints on the troposphere where mankind naturally lives, there is an obvious need for periodic determination of effective transmission margins consistently for most geographic locations on Earth. The need for the achievement of an effective wireless transmission margin and larger bandwidth at a relatively lower cost precipitates the importance of hydrometeor models’ roles in satellite transmissions. Also, the almost perpetual existence of clouds in tropical climates makes cloud models all the more fundamental. Details of four years of station spectrum analyzer data, five years of climatological data and fifty – eight years of radiosonde data used in this research at tropical test station - Ota, southwest Nigeria - were earlier published. At the station, total cloud attenuation data were measured and logged every minute using the spectrum analyzer. The large data was used to deduce the station cloud attenuation cumulative distribution, which was used to derive the station's new cloud attenuation algorithm. This cumulative distribution was compared with the station cloud attenuation cumulative distribution of each of the other existing cloud models. The radiosonde data was used to derive each existing cloud model’s predicted cloud attenuation cumulative distribution respectively for the tropical station. These sets of distributions were used to deduce the station's new cloud attenuation algorithm’s parameters through a written and published simulation program, which defined the cloud attenuation model for the station. Thus, the generation of any new station cloud attenuation model only fundamentally requires the station’s radiosonde data. The integrity of the radiosonde data renders cloud cover data and all others for a station only for graphical comparisons and corroboration. Thus, the new cloud attenuation algorithm can be used to develop the cloud attenuation model for any geographic location by using the methodology reviewed above and whose details were earlier published. Subsequently, the 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. Spectrally, the station's new cloud attenuation model’s cumulative distribution proportionally averaged the other model’s characteristic cumulative distributions 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. Hence, global hydrometeor transmission margins for any set of locations can be determined through the explained method, at an effective frequency.