Electronic Engineering

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Correlation of rain dropsize distribution with rain rate derived from disdrometers and rain gauge networks in Southern Africa.
(2011) Alonge, Akintunde Ayodeji.; Afullo, Thomas Joachim Odhiambo.
Natural phenomena such as rainfall are responsible for communication service disruption, leading to severe outages and bandwidth inefficiency in both terrestrial and satellite systems, especially above 10 GHz. Rainfall attenuation is a source of concern to radio engineers in link budgeting and is primarily related to the rainfall mechanism of absorption and scattering of millimetric signal energy. Therefore, the study of rainfall microstructure can serve as a veritable means of optimizing network parameters for the design and deployment of millimetric and microwave links. Rainfall rate and rainfall drop-size are two microstructural parameters essential for the appropriate estimation of local rainfall attenuation. There are several existing analytical and empirical models for the prediction of rainfall attenuation and their performances largely depend on regional and climatic characteristics of interest. In this study, the thrust is to establish the most appropriate models in South African areas for rainfall rate and rainfall drop-size. Statistical analysis is derived from disdrometer measurements sampled at one-minute interval over a period of two years in Durban, a subtropical site in South Africa. The measurements are further categorized according to temporal rainfall regimes: drizzle, widespread, shower and thunderstorm. The analysis is modified to develop statistical and empirical models for rainfall rate using gamma, lognormal, Moupfouma and other ITU-R compliant models for the control site. Additionally, rain drop-size distribution (DSD) parameters are developed from the modified gamma, lognormal, negative exponential and Weibull models. The spherical droplet assumption is used to estimate the scattering parameters for frequencies between 2 GHz and 1000 GHz using the disdrometer diameter ranges. The resulting proposed DSD models are used, alongside the scattering parameters, for the prediction and estimation of rainfall attenuation. Finally, the study employs correlation and regression techniques to extend the results to other locations in South Africa. The cumulative density function analysis of rainfall parameters is applied for the selected locations to obtain their equivalent models for rainfall rate and rainfall DSD required for the estimation of rainfall attenuation.
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.
Queueing theory approach to rain fade analysis at microwave and millimeter bands in tropical Africa.
(2014) Alonge, Akintunde Ayodeji.; Afullo, Thomas Joachim Odhiambo.
With an overwhelming demand of larger bandwidth required for high capacity data with content-rich services ranging from high-speed video streaming to multimedia content, there is a continuous need to migrate to higher microwave bands, particularly beyond the regular Ku and Ka bands (between 11 - 40 GHz). The presence of precipitation at these microwave and millimeter bands (3-300 GHz) generally induce rain fade, which is a constraint to network providers intending to achieve optimal service delivery, at acceptable signal to noise ratios (SNRs). In practice, fade countermeasures – static or dynamic – are necessary to combat the consequences of chronic fluctuations of rainfall resulting in signal deterioration and impairment over communication links. However, the implementation of dynamic fade countermeasures is systematically tied upon the available Channel State Information (CSI), which is often timevariant relative to the occurrence of precipitation events. Time-variation of rainfall events are perceptible in measurable rainfall microstructural parameters which vary intensely in space and time. These spatio-temporal variations yield the generation of observable random patterns of signal attenuation during rain events, often in a stochastic manner. To this end, researchers have emphasized on understanding the underlying behaviour of generic rainfall microstructural parameters such as rainfall rate, rainfall Drop Size Distribution (DSD) and radar reflectivity. Therefore, the investigation of these stochastic properties of rainfall processes is primary in the determination of recognisable patterns of rainfall rate and other microstructures. This thesis introduces the queueing theory approach via the Markov Chain technique to investigate the time-varying characteristics of the rainfall process from distrometer data in subtropical and equatorial Africa. Rainfall data obtained from these two climatic locations, at one minute integration time, were processed from sites in Durban, South Africa and Butare, Rwanda, over a specified measurement period. Initial investigation and comparison of rainfall microstructures undertaken at both sites clearly show key differences in their probability distribution profiles at Stratiform-Convective (SC) bounds. The underlying queue discipline of rainfall spikes and their queue metrics are determined and appraised for system performance using rainfall time series database. The results show rain spike generation processes vividly exhibit a First-Come, First- Served (FCFS) semi-Markovian distributed traffic of M/Ek/s discipline, with a varying degree of servers, for different rainfall regimes. Comparison of queue statistics results over different rainfall regimes at the two locations reveal significant differences in their queue metrics and performances. The knowledge obtained from the queue statistics and SC probability analysis are further employed in the determination and classification of rainfall cells, rainfall growth models and path attenuation prediction. The results are compared and validated with data collected from a 6.73km, 19.5 GHz terrestrial link in Durban.
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.
Semi-empirical modelling of subtropical rain attenuation on earth-satellite microwave links.
(2018) Afolayan, Babajide Olugbenga.; Afullo, Thomas Joachim Odhiambo.; Alonge, Akintunde Ayodeji.
The exponential rise in demand for high fidelity content on multiple platforms has in recent years made increased use of the higher echelons of radio communication frequency inevitable. At these high frequencies, wavelength becomes small enough to compare with the size of rain drops and in some cases smaller than drop size. This implies that the impairment due to rain, which already usually forms the most severe form of impairment at higher radio frequency bands, will become even more acute and require rigorous parameterization. This thesis investigates both by rigorous measurements and by theoretical approaches, the attenuation effect of rainfall in a subtropical climate (Durban, South Africa) on a microwave earth-satellite link operating at 12.6 GHz. The link was set up and the received signal level monitored via spectrum analyser sweeps conducted every minute. A Joss-Waldvogel impact disdrometer was installed such that its diaphragm is located a few meters away from the link’s receive antenna. From such a location, all precipitation recorded by the disdrometer are assumed to have some effect on the link. The monthly variation in the received signal during clear air was investigated by taking into consideration the average monthly values of temperature, relative humidity and atmospheric pressure. By employing multiple regression, a linear expression was obtained that can be used to predict the change in received signal level in clear air over the link given the values of these three atmospheric parameters. The attenuation due to the rain events was extracted from the data by carrying out an even-by-event matching of rain rate spikes with the corresponding drop observed in the received signal level at and around the time of the precipitation. The average monthly received signal level during clear air was extracted from the spectrum analyser data and used as the base channel power to which the received signal during rain in the particular month is compared. The difference between the two is stored as the attenuation due to rain in that instant of measurement time. The attenuation data thus accumulated were entered into a computer algorithm and a regression fitting procedure carried out to deduce an empirical set of logarithmic and power law models that relate the total path attenuation to rain rate. The models were then validated by a largely favourable comparison with four existing models, one of which is the in-force ITU-recommended model for slant path attenuation estimations. Random number properties of rain attenuation statistics obtained from the measurement model were exploited to develop a Markov chain approach by which seasonal and annual slant path rain attenuation time series can be generated. By investigating the nature of the probability distributions of the seasonal and annual measured path attenuation statistics, which was found to be lognormal, the state probability matrix necessary for implementing a Markov chain prediction model for future patterns of rain attenuation on a similar link was obtained as the lognormal probability density function. The state transition probability vector for each time period was developed by extracting the fade slope statistics of the measured attenuation. The discrete-time Gaussian distributed fade slope PDF forms the basis for the state transition probability matrix. With these, Markov-generated time series of seasonal and annual slant path attenuation for up to five iterations were obtained. The results make useful data that can be used for long-term planning for rain fade mitigation in a subtropical climate easier to generate without the expense of measurements. The theoretical approach called the Synthetic Storm Technique was also applied to investigate the nature of slant path rain attenuation in Durban. Based on the rainfall pattern captured by the disdrometer, SST approximations for the four seasons of the subtropical year and for years of rain data collection were carried out. The results were compared with the values generated from the measurement model. It reveals that the two models exhibit significant agreement because in a majority of the cases, the A0.01 values obtained are very close. Comparison of the performance of SST as a theoretical model with that of the ITU-recommended method also reveals that the ITU performs slightly better as an alternative to measurement than the SST model. It was observed that during certain precipitation events, the satellite link registers significant attenuation levels several minutes before the disdrometer records any precipitation on the ground. This anomaly was investigated in this work and a few conclusions drawn. By proceeding on the assumption that the observed delay was due to the migrating rain cell interacting with the satellite beam several minutes before reaching the receive antenna, it was demonstrated that the time of delay between precipitation and attenuation is related to the rain height during that particular rain event. A simple mathematical analysis is presented that enables the rain height to be estimated from the delay time. The results obtained range between 1.4 km to 6.7 km which is similarity to rain height values obtained by the ITU model which range from 1.36 km to 6.36 km.
Study of lower sampling intervals on rainfall queue characteristics over Radio Links in South Africa.
(2017) Mazibuko, Godfrey Nkululeko.; Afullo, Thomas Joachim Odhiambo.; Alonge, Akintunde Ayodeji.
Rainfall attenuation in tropical and subtropical regions of the world has continued to attract great interest; as there is a urgent emphasis on proper spectrum management and sharing, particularly at microwave and millimeter bands above 10 GHz. To this end, there have been arguments pertaining to the need to improve the ‘sensing’ of rainfall events to enhance the opportunities provided by adaptive rain fade mitigation schemes, while conserving base station power requirements during rainy events. To implement this approach, an extensive understanding of rainfall time series via the available statistical tools is often required to properly harness the characteristics of rainfall behavior. To this end, a study was undertaken to examine the behavior of rainfall and its impact on radio links at 1-minute sampling time by using the Queueing Theory Technique (QTT). Interesting results were obtained in the process of the study, except that the effect of the sampling time on rainfall queues remained unknown. Therefore, this thesis presents the investigation of the sampling time effects on rainfall queues over radio links in Durban, South Africa. Rainfall measurements were collected at 30-second sampling time using the RD-80 Joss–Waldvogel (JW) distrometer in Durban (29o52’S, 30o58’E), the same location where the 1-minute data was previously collected. As before, the rainfall data is classified into four rainfall regimes, namely drizzle, widespread, shower and thunderstorm. The queue parameters required for rainfall traffic analysis such as inter-arrival time and service-time distribution are empirically determined to be Erlang-k distributed, whereas the overlap time is exponentially distributed. It is thus established that the queue discipline for rain spikes over radio waves is a non-Markovian process (Ek/Ek/s/∞/FCFS). Comparison between the 30-second rainfall queues results and previous results of 1-minute sampling time, shows that more rainfall spikes are revealed at 30-second sampling time. Furthermore, it is determined that there is a strong polynomial relationship between the 30-second and 1-minute sampling time data – hence some of the 1-minute data may be converted into 30-second data by using the polynomial function, with the appropriate polynomial coefficients according to rainfall queue parameters in each regime. The converted data is amalgamated with the actual 30-second data for the investigation of the rainfall long-term behavior. It is found that the rainfall long-term behavior resembles the behavior of the short-term data - hence implying that the rainfall process at 30-second sampling time in Durban has the attributes of a self-similar process. From rain attenuation investigation, it is determined that since more rain spikes are evident in the 30-second data, the former has higher rain attenuation exceedance values (R0.01) compared to the 1-minute data.

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