The dynamic weather condition is a major concern for optimum channel utilization in recent times, especially at higher frequencies with larger bandwidth for 5G applications. Over the years, rain-induced attenuation among the hydrometeors has been linked as the major cause of signal impairment especially at the frequency, f > 10 GHz. However, when f > 18 GHz, the significant impact of other hydrometeors; cloud/fog, and scintillation increases tremendously, especially for Low Earth Orbit, LEO satellites. LEO satellites find applications in fibre optics technology, scientific research, remote sensing, surveillance, meteorology, satellite imaging, and other applications. In this paper, the assessment of combined impairments based on 5-year (2012-2016) data has been carried out and a dynamic adaptive intelligent scheme (DAIS) has been adopted to achieve a good quality of service along the satellite channels operating at Ku-V band frequencies over five stations representing different climatic regions in Nigeria namely: Port Harcourt (PH), Akure, Ilorin, Zaria, and Kano. The proposed DAIS based on fuzzy logic was able to achieve a significant reduction in the transmitting power by about 70% and SNR by 50% across the frequencies considered without altering the information content of the downlink parameters, thereby improving the QoS significantly and adhere to Customer Service Level Agreements (CSLAs) irrespective of the weather dynamics. The overall results show that the adaptive intelligent techniques can effectively fix signal links under the dynamic weather conditions for both satellite and wireless networks in this region. Information from the results is timely because it will serve as the bedrock for the newly launched transformation to the digital video broadcasting (DVB) system in Nigeria for effective service delivery.
In this study, measurements of vertical profiles of rain parameters have been made using vertically pointing micro rain radar (VPMRR) at Akure (7.30° N, 5.13° E). Rain parameter data collected over seven-month rainfall episodes during the intense rainy season (April to October) have been analyzed for a dynamical evolutionary trend over the site. Nearly all the episodes observed followed a similar pattern, hence, a single continuous rainfall episode occurring between 20:45:00 h and 21:14:00 h Greenwich Meridian Time (GMT) local time on 6
th
August 2018 is presented in this report. The results show no significant changes to the rain parameters (such as rain rate and liquid water content) nor contributed to the raindrop size distribution, based on average fall velocity of 6.55 m s
−1
and rain rates within 1.3 and 2.6 mm h
−1
. This is to enable a stable fall for the dominant drops during the period. Further, the results revealed the transformation and collision of smaller drops to enhance a stable fall of larger drops during the rain event. The information from the study will be useful for radar meteorologists and microwave engineers in their designs.
The peculiarity of the tropical climate shows that when the quality of service (QoS) on Satellite-Earth propagation links is to be determined, the statistics of rain-based attenuation (RbA), storm speed, and their impacts are the important parameters to be considered, especially at frequencies above 10 GHz. This paper assesses the influence of storm speed in estimating RbA at Ku-band, based on 2-year rain rate data obtained using automatic weather station (AWS) and RbA beacon measurements in Nigeria. The rain rates based on the time series were employed to deduce the time series RbA based on the synthetic storm technique (SST) algorithm. The results show a seasonal pattern of rain rate that correlates with the SST-based RbA. The RbA generated closely follows suit with the beacon measurement, especially under low wind speed, and outperforms the international telecommunications union–radiocommunication sector (ITU-R) model based on the lowest metric measures. However, at a higher storm speed, the RbA generated deviated widely from the measured RbA values by about 16%. These results are crucial for figuring out what needs to be done to protect QoS in a tropical area where wind and rain are common.
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