Browsing by Author "Nabangala, Mary."

Now showing 1 - 2 of 2

Determination of rainfall parameters for specific attenuation due to rain for different integration times for terrestrial line-of-sight links in South Africa.
(2016) Nabangala, Mary.; Afullo, Thomas Joachim Odhiambo.; Alonge, Akintunde Ayodeji.
Currently, there have been large demand for end-user services that use large bandwidths, while requiring best throughputs; these requirements are often not realistic because of meagre allocation of radio resources. Consequently, for many networks, the traditional option of migrating to higher frequency bands in the microwave and millimeter wave spectrum (3-300 GHz) is often the immediate solution. However, this option suffers a huge drawback most especially at geographical locations which experience signal deterioration from larger levels of hydrometeors (presence of water in the atmosphere). More importantly, the influence of ubiquitous hydrometeors such as precipitation, is reputed to be a major constraint to communication links between base stations at microwave and millimeter bands. This often cripples many radio networks, as a result of incessant and spontaneous outages experienced during rainfall events. Therefore, there is need for radio system engineers to acquire sufficient information on effects of rain in a particular locality for planning and design of reliable communication links. In this work, the choice of approaching this problem tallies with the International Telecommunication Union (ITU) concept of rainfall rate point estimation but with emphasis on measurements at lower integration time of 30-seconds. This dissertation considers local rainfall rate measurements from 10 locations across South Africa at 5-minute integration time as obtained from South African Weather Services. Using rainfall measurements at one-minute and 30-second data from the coastal city of Durban (29°52’S, 30°58’E), various rainfall rate conversion models are obtained for these selected locations by applying rainfall statistics at higher integration time. Power-law functions obtained over South Africa reveals that rainfall statistics at 30-second integration time provides more information compared with one-minute and 5-minute integration times. In addition, a comparison of these results with ITU-R estimations have shown a close agreement with rainfall rates at 99.99% availability at the investigated locations. Furthermore, a comparison of rainfall Drop Size Distribution (DSD) at 30-second and one-minute integration time over Durban is undertaken to establish temporal variability in disdrometer measurements. These variations are compared using statistical DSD models of lognormal and modified gamma distributions with two parameter estimation techniques: Method of Moments (MM) and Method of Maximum Likelihood (ML). Datasets employed are subset rainfall measurements with seasonal cycles comprising of summer, autumn, winter and spring, and on lumped yearly basis. Finally, investigations of the effects of rainfall integration time on rainfall attenuation are compared over Durban using one-minute and 30-second data. For this purpose, Mie scattering theory is employed to calculate the power-law coefficients and the frequency dependency of rainfall measurements at 30-seconds integration time.
Rainfall attenuation prediction model for dynamic rain fade mitigation technique considering millimeter wave communication link.
(2018) Nabangala, Mary.; Alonge, Akintunde Ayodeji.; Afullo, Thomas Joachim Odhiambo.
To deliver modern day broadband services to both fixed and mobile devices, ultra-high speed wireless networks are required. Innovative services such as the Internet-of-Things (IoT) can be facilitated by the deployment of next generation telecommunication networks such as 5G technologies. The deployment of 5G technologies is envisioned as a catalyst in the alleviation of spectrum congestion experienced by current technologies. With their improved network speed, capacity and reduced communication latency, 5G technologies are expected to enhance telecommunication networks for next generation services. These technologies, in addition to using current Long Term Evolution (LTE) frequency range (600 MHz to 6 GHz), will also utilize millimetre wave bands in the range 24-86 GHz. However, these high frequencies are susceptible to signal loss under rain storms. At such high frequencies, the size of the rain drop is comparable to the wavelength of the operating signal frequency, resulting in energy loss in the form of absorption and scattering by water droplets. This study investigates the effect of intense rain storms on link performance to accurately determine and apply dynamic rain fade mitigation techniques such as the use of a combination of modulation schemes to maintain link connectivity during a rain event. The backpropagation neural network (BPNN) model is employed in this study to predict the state of the link for decision making in employment of dynamic rain fade mitigation. This prediction model was tested on all rainfall regimes including intense rain storms and initial results are encouraging. Further on, the prediction model has been tested on a rainfall event rainfall data collected over Butare (2.6078° S, 29.7368° E), Rwanda, and the results demonstrate the portability of the proposed prediction model to other regions. The evolution of R0.01 (rain rate exceeded for 0.01% of the time in an average year) parameter due to intense rain storms over the region of study is examined and detailed analysis shows that this parameter is double the proposed ITU-R value of 60 mm/h. Moreover, an investigation on the largest rain drop size present in each rain storm is carried out for different storm magnitudes. The study goes further to examine the frequency of occurrence of rain storms using the Markov chain approach. Results of this approach show that rain spikes with maximum rain rates from 150 mm/h and above (intense storms) are experienced in the region of study with probability of occurrence of 11.42%. Additionally, rain spike service times for various rain storm magnitudes are analyzed using the queueing theory technique. From this approach, a model is developed for estimation of rain cell diameter that can be useful for site diversity as a dynamic rain fade mitigation strategy. Finally, the study further investigates second-order rain fade statistics at different attenuation thresholds.