Semi-empirical modelling of subtropical rain attenuation on earth-satellite microwave links.

Doctoral Degree. University of KwaZulu-Natal, Durban.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

Rainfall attenuation prediction model for dynamic rain fade mitigation technique considering millimeter wave communication link.

Doctoral Degree. University of KwaZulu-Natal, Durban.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

Study of lower sampling intervals on rainfall queue characteristics over Radio Links in South Africa.

Masters Degree. University of KwaZulu-Natal, Durban.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

Radio wave propagation modeling under precipitation and clear-air at microwave and millimetric bands over wireless links in the horn of Africa.

Doctor of Philosophy in Electronic Engineering. University of KwaZulu-Natal, Durban 2017.Abstract available in PDF file

High Energy Cosmic Neutrinos

While the general principles of high-energy neutrino detection have been understood for many years, the deep, remote geographical locations of suitable detector sites have challenged the ingenuity of experimentalists, who have confronted unusual deployment, calibration, and robustness issues. Two high energy neutrino programs are now operating (Baikal and AMANDA), with the expectation of ushering in an era of multi-messenger astronomy, and two Mediterranean programs have made impressive progress. The detectors are optimized to detect neutrinos with energies of the order of 1-10 TeV, although they are capable of detecting neutrinos with energies of tens of MeV to greater than PeV. This paper outlines the interdisciplinary scientific agenda, which span the fields of astronomy, particle physics, and cosmic ray physics, and describes ongoing worldwide experimental programs to realize these goals.Comment: 15 pages, 9 figures, talk presented at the Nobel Symposium on Particle Physics and the Universe, Sweden, August 199

Multi-Objective Reinforcement Learning for Cognitive Radio-Based Satellite Communications

Previous research on cognitive radios has addressed the performance of various machine-learning and optimization techniques for decision making of terrestrial link properties. In this paper, we present our recent investigations with respect to reinforcement learning that potentially can be employed by future cognitive radios installed onboard satellite communications systems specifically tasked with radio resource management. This work analyzes the performance of learning, reasoning, and decision making while considering multiple objectives for time-varying communications channels, as well as different cross-layer requirements. Based on the urgent demand for increased bandwidth, which is being addressed by the next generation of high-throughput satellites, the performance of cognitive radio is assessed considering links between a geostationary satellite and a fixed ground station operating at Ka-band (26 GHz). Simulation results show multiple objective performance improvements of more than 3.5 times for clear sky conditions and 6.8 times for rain conditions

Queueing theory approach to rain fade analysis at microwave and millimeter bands in tropical Africa.

Ph. D. University of KwaZulu-Natal, Durban 2014.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

Satellite Communications

This study is motivated by the need to give the reader a broad view of the developments, key concepts, and technologies related to information society evolution, with a focus on the wireless communications and geoinformation technologies and their role in the environment. Giving perspective, it aims at assisting people active in the industry, the public sector, and Earth science fields as well, by providing a base for their continued work and thinking