Orthogonal Pseudo-Random Sequence Enabled Cognitive and Emergency Communications

With the ever-increasing demands for the broadband mobile communications, it is becoming more and more difficult to accommodate all existing and emerging wireless services and applications due to the limited communication resources particularly radio spectrum. In addition, system parameters of wireless communications often need to be adapted due to the variation of channel characteristics and user demands. Cognitive communication is emerged as an effective technique, particularly to improve the utilization rate of limited communication resources adaptively according to the change in its operating conditions and requirements. To handle these challenges efficiently and reliably in cognitive radio scenario, cyclic prefix (CP) of the OFDM system is precoded in this thesis using pseudo-random sequence. This signaling link can effectively carry transmission parameters and system adaptation information. In first part of the thesis, mutual interference minimization and transmission power adaptation enabled by the additional signaling link are also investigated. In order to make use of this precoded cyclic prefix (PCP) signaling link, an efficient demodulation scheme is needed to reduce the implementation complexity. Therefore, a low complexity signaling demodulator along with a multipath combining technique to further improve the performance in real communication scenario like in multipath channel is proposed in the thesis. The final aspect of this thesis is the investigation of a robust communication system using digital television (DTV) transmitter identification watermark signal which is also a modulated pseudo-random sequence. The previous study on PCP signaling is thus extended to an emergency communication system using DTV watermark. It is found that watermark based communication system is more robust than the DTV broadcasting and can reach a much wider coverage with significantly increased network reliability, which is suitable for national emergency situations

Integration of distributed generation along with energy storage system to reduce the high penetration impacts of renewable energy sources into the power grid.

Compte tenu du comportement aléatoire et fluctuant des sources d'énergie renouvelable (SER), l'équilibre entre la génération et la demande ne sont pas faciles à contrôler. Par conséquent, la stabilité dynamique du flux d'énergie et le contrôle de la fréquence deviennent de plus en plus difficiles en raison des impacts de la pénétration élevée des SER dans les micro-réseau électrique. Des stratégies de contrôle des convertisseurs/onduleurs avec filtre sont nécessaires pour maintenir l'alimentation électrique appropriée dans l'ensemble du micro-réseau. L'objectif de notre travail est d'explorer les aspects critiques de la génération distribuée (GD), de l'intégration des énergies renouvelables et des systèmes de stockage de l'énergie, en mettant l'accent sur l'amélioration de l'efficacité du réseau électrique tout en minimisant la pollution atmosphérique. Cette thèse reconnaît les avantages environnementaux et économiques de la GD tout en soulignant les défis inhérents à la gestion des sources d'énergie renouvelable fluctuantes. Un algorithme de contrôle pour un système de stockage d'énergie hybride diesel-éolien à forte pénétration est conçu pour maintenir la stabilité dynamique du flux d'énergie et le contrôle de la fréquence du réseau. Les principaux résultats comprennent la réduction efficace du temps de transition dans le flux d'énergie éolienne et des fluctuations de fréquence. D'autre part, cette étude répond aux défis posés par la nature intermittente des SER et leur impact sur la stabilité dynamique et le contrôle de la fréquence. Nous avons introduit un algorithme de contrôle utilisant la logique floue pour un système de stockage d'énergie éolienne en utilisant la méthode de partage de puissance. En comparant cette approche au contrôleur conventionnel, l'algorithme proposé a démontré des améliorations substantielles dans la réduction du temps de transition dans le flux d'énergie éolienne et des fluctuations de fréquence. Dans le cadre de cette thèse, une étude complète de divers convertisseurs statiques est réalisée afin de déterminer le dispositif de stockage d'énergie le plus approprié pour les applications de réseaux intelligents. Ce système de stockage joue un rôle essentiel dans le maintien de la stabilité du réseau tout en minimisant les pertes d'énergie. L'objectif est d'identifier le dispositif de stockage d'énergie le plus adapté à cette application. Les avantages de cette technologie sont d'une grande efficacité et fiabilité, qui peuvent connecter diverses sources d'énergie et réduire les pertes de conduction dans les convertisseurs de puissance. On a analysé l'efficacité et la fiabilité de différents convertisseurs et évalué leur performance dans des conditions de charge et de décharge du système de stockage. Les plages de fonctionnement des convertisseurs élévateur-abaisseur, abaisseur-élévateur et abaisseur-élévateur (-Vout) ont été analysées pour optimiser le système de stockage d'énergie. Cette thèse présente également une analyse complète d'un schéma de simulation qui exploite un système solaire composé de panneaux photovoltaïques intégrés au réseau électrique, à diverses charges, et à un dispositif de stockage d'énergie. Après la modélisation des panneaux photovoltaïques et de leurs caractéristiques opérationnelles, un filtre adaptatif est développé pour atténuer les fluctuations du courant d'entrée. On a exploré en outre l'efficacité et les mécanismes de contrôle des convertisseurs de puissance et des onduleurs, facilitant ainsi l'intégration du système de stockage d'énergie avec le réseau électrique. Plusieurs techniques de contrôle non linéaires sont utilisées pour évaluer les performances du système avec différentes configurations, y compris un onduleur simple, un filtre multi-variable, un filtre passe bande et une configuration sans filtre. Cette recherche nous a permis de proposer une régulation efficace du bus DC au sein du réseau électrique. L'avantage clé de ces régulateurs non linéaires est leur capacité à compenser la puissance réactive et les courants harmoniques, ce qui se traduit par un réseau électrique sans perturbations et une réduction du taux de distorsion harmonique totale (DHT) des onduleurs, améliorant finalement l'efficacité globale du réseau électrique. Cette thèse apporte des connaissances précieuses pour optimiser les performances des systèmes éoliens et solaires ainsi que du dispositif de stockage d'énergie, et leur intégration au réseau grâce à des techniques de contrôle et de filtrage avancées, avec des implications significatives pour l'amélioration de la stabilité et de la fiabilité des sources d'énergie renouvelable dans le réseau électrique. Abstract Being the fluctuation behavior of Renewable Energy Sources (RESs), generation, balance, and demand are not easy tasks to control because it is not desirable to have constant power generation from RESs due to natural prospects. As a result, the dynamic stability of power flow and control of frequency is becoming more challenging due to the high penetration impacts of RESs. Control strategies of converter/inverter with filter are also required to maintain the proper power supply in the entire microgrid where energy storage device plays crucial roles. The objective of this study is to explore critical aspects of distributed generation (DG), renewable energy integration, and energy storage systems, focusing on enhancing power network efficiency while minimizing power losses and environmental air pollution. This doctoral thesis acknowledges the environmental and economic benefits of distributed generation (DG) while highlighting the inherent challenges in managing fluctuating renewable energy sources (RESs). A control algorithm for a high-penetration hybrid diesel-wind-based energy storage system is designed to maintain dynamic stability in power flow and control network frequency. The key findings include the effective reduction of transient time in wind power flow and frequency fluctuations through the use of an integral-derivative (I-D) controller. On the other hand, it recognizes the challenges posed by the intermittent nature of renewable energy sources (RESs) and their impact on dynamic stability and frequency control. This thesis introduced a control algorithm employed with a Fuzzy Logic (FL) controller for a wind-based energy storage system using the power-sharing method. By comparing this approach to the traditional Proportional Integral Derivative (PID) controller, the study demonstrated substantial improvements in reducing transient time in wind power flow and frequency fluctuations. A storage system (battery) plays a crucial role in maintaining network stability while minimizing energy losses. As a part of this thesis, a comprehensive survey of various DC-DC converters is done to determine the most suitable energy storage device for smart grid applications. The main objective is to identify this application's most appropriate energy storage device. The advantages of this technology are high efficiency and reliability, which can connect various energy sources and reduce conduction losses in the power converters. The study analyzed the efficiency and reliability of different converters and evaluated their performance in charging and discharging conditions of a battery. The operating ranges of boost-buck, buck-boost, and buck-boost (-Vout) converters are analyzed to optimize the energy storage system. This doctoral thesis also presents a comprehensive analysis of a simulation scheme that leverages a solar system composed of photovoltaic (PV) panels integrated with the electrical grid, various loads, and an energy storage device. The research begins by investigating the modeling of PV panel cells and their operational characteristics. Subsequently, an adaptive notch filter synthesis is developed to mitigate input current fluctuations. The research further explores the efficiency and control mechanisms of power converters and inverters, facilitating the seamless integration of the energy storage system with the electrical grid. Multiple simulations are conducted, employing nonlinear control techniques to evaluate the performance of the system with different configurations, including a simple inverter, a multi-variable filter, a notch filter, and a filter-less setup. The research aims to achieve effective regulation of the DC bus within the proposed grid. The key advantage of these nonlinear controllers is their ability to compensate for reactive power and harmonic currents, resulting in a disturbance-free power network and a reduction in the Total Harmonic Distortion (THD) rate of the inverters, ultimately enhancing the overall efficiency of the power grid. This thesis contributes valuable insights into optimizing the performance of wind and solar systems along with energy storage device and their integration with the grid through advanced control and filtering techniques, with significant implications for improving the stability and reliability of renewable energy sources in the power grid

Frequency control in the presence of renewable energy sources in the power network

Distributed generation (DG) becomes more popular power generation system in the presence of power engineering sector. It has environmental and economic benefit compared with other power generation system and run new technologies to have more efficient and less pollution in the environment. Due to the fluctuating behavior of renewable energy sources (RES), balancing, production and demand are not an easy task to control because it is not possible to get constant power from the renewable energy sources due to the natural situation. That’s why control of frequency in the power systems becomes more difficult due to the increasing of penetration of renewable resources. Therefore, a more effective control technique is needed to avoid a network collapse during power distribution. To better understand the technology of DG, methods of control, regulation of frequency related factors, the impact of DG on the voltage, power quality, and frequency during its connection to the grid distribution is identified in introduction part and the literature review based on DG in chapter I. Power grid connected to a wind turbine has been discussed in chapter II. Three scenarios of power system operation with control technique have been discussed for a hybrid diesel / high-penetration wind-based energy storage system in chapter III. In this application, PID and the fuzzy logic controller have been compared to each other to observe the fluctuation behavior of frequency. Therefore, some limitations and prospects of this methodology are identified in the conclusion

Healthcare Capacity, Health Expenditure, and Civil Society as Predictors of COVID-19 Case Fatalities: A Global Analysis

Background: The rapid growth in cases of COVID-19 has challenged national healthcare capacity, testing systems at an advanced ICU, and public health infrastructure level. This global study evaluates the association between multi-factorial healthcare capacity and case fatality of COVID-19 patients by adjusting for demographic, health expenditure, population density, and prior burden of non-communicable disease. It also explores the impact of government relationships with civil society as a predictor of infection and mortality rates. Methods: Data were extracted from the Johns Hopkins University database, World Bank records and the National Civic Space Ratings 2020 database. This study used data from 86 countries which had at least 1,000 confirmed cases on 30th April 2020. Negative binomial regression model was used to assess the association between case fatality (a ratio of total number of confirmed deaths to total number of confirmed cases) and healthcare capacity index adjusting for other covariates. Findings: Regression analysis shows that greater healthcare capacity was related to lesser case-fatality [incidence rate ratio (IRR) 0.5811; 95% confidence interval (CI) 0.4727–0.7184; p < 0.001] with every additional unit increase in the healthcare capacity index associated with a 42% decrease in the case fatality. Health expenditure and civil society variables did not reach statistical significance but were positively associated with case fatalities. Interpretation: Based on preliminary data, this research suggests that building effective multidimensional healthcare capacity is the most promising means to mitigate future case fatalities. The data also suggests that government's ability to implement public health measures to a degree determines mortality outcomes

Evaluation of graft uptake in underlay myringoplasty using dry and wet temporalis fascia graft

Chronic otitis media (COM) is a vital cause of deafness worldwide. Myringoplasty is one of the best treatment options for COM (inactive mucosal variety). Temporalis Fascia is the most favored grafting material among various autografts, which can be used as dry or wet depending upon the Surgeon's choice. The main focus of this study is to compare the graft uptake rate by using dry and wet temporalis fascia by underlay technique. This cross-sectional comparative study was directed from January 2018 to June 2019 at the Department of Otolaryngology-Head & Neck Surgery of BSMMU, Dhaka. All consecutive cases of COM (inactive mucosal) who underwent surgery were randomly assigned either into the dry (Group-A) or wet temporalis fascia group (Group-B). At 12 weeks follow-up, the density of graft failure (4.4% vs. 8.8%) and retraction pocket (0% vs. 2.2%) were higher in the wet procedure. However anterior blunting (2.2% vs. 2.2%) were the same in both procedures, and medialization (2.2% vs. 0%) were more in the dry procedure. Air Bone Gap (ABG) improved significantly in both groups following operation but reduced in Group-A more significantly than Group-B. On the other hand, there was no remarkable difference in successful graft uptake between the groups (Dry group-91.12% vs. wet group-84.44%, p>0.05). No graft material is superior to others in terms of graft uptake. BSMMU J 2022; 15(2): 84-8

Machine Learning and Meta-Analysis Approach to Identify Patient Comorbidities and Symptoms that Increased Risk of Mortality in COVID-19

Background: Providing appropriate care for people suffering from COVID-19, the disease caused by the pandemic SARS-CoV-2 virus is a significant global challenge. Many individuals who become infected have pre-existing conditions that may interact with COVID-19 to increase symptom severity and mortality risk. COVID-19 patient comorbidities are likely to be informative about individual risk of severe illness and mortality. Accurately determining how comorbidities are associated with severe symptoms and mortality would thus greatly assist in COVID-19 care planning and provision. Methods: To assess the interaction of patient comorbidities with COVID-19 severity and mortality we performed a meta-analysis of the published global literature, and machine learning predictive analysis using an aggregated COVID-19 global dataset. Results: Our meta-analysis identified chronic obstructive pulmonary disease (COPD), cerebrovascular disease (CEVD), cardiovascular disease (CVD), type 2 diabetes, malignancy, and hypertension as most significantly associated with COVID-19 severity in the current published literature. Machine learning classification using novel aggregated cohort data similarly found COPD, CVD, CKD, type 2 diabetes, malignancy and hypertension, as well as asthma, as the most significant features for classifying those deceased versus those who survived COVID-19. While age and gender were the most significant predictor of mortality, in terms of symptom-comorbidity combinations, it was observed that Pneumonia-Hypertension, Pneumonia-Diabetes and Acute Respiratory Distress Syndrome (ARDS)-Hypertension showed the most significant effects on COVID-19 mortality. Conclusions: These results highlight patient cohorts most at risk of COVID-19 related severe morbidity and mortality which have implications for prioritization of hospital resources

Interference mitigation and alignment for interference-limited communication systems

With limited availability of the communication spectrum and ever-increasing demands for high-data-rate services, it is natural to reuse the same time-frequency resource to the greatest degree possible. Depending on the nature of transmission and reception of the users, this leads to different instances of interference, e.g., inter-user interference in an interference network and self-interference in a Full-Duplex (FD) transmission. With a goal to mitigate such interference, in this thesis we investigate emerging interference-limited communication systems, such as FD, Device-to-Device (D2D), and Power Line Communication (PLC). To this end, we propose advanced solutions, namely self-interference mitigation and Interference Alignment (IA). With an objective to reduce the power consumption, we study transceiver design for FD multi-cell Multi-Input Multi-Output (MIMO) systems with guaranteed Quality of Service (QoS). Considering realistic self-interference models and robustness against Channel State Information (CSI) uncertainty, our numerical results reveal transmission scenarios and design parameters for which replacing half-duplex with FD systems is beneficial in terms of power minimization. If the system is not power constrained, however, a natural objective is to optimize the total throughput given a power budget. Nonetheless, throughput maximization underserves the users that experience poor channels, which leads to QoS unfairness. Therefore, we propose a fair transceiver design for FD multi-cell MIMO systems, which can be implemented in a distributed manner. We further extend our design to enforce robustness against CSI uncertainty. As a second contribution within this design theme, the concept of robust fair transceiver design is also extended for D2D communications, where unlike the self-interference in FD transmission, the users suffer from strong inter-user interference. Recognizing that simultaneous multiple connections in PLC contribute to (interuser) interference-limited communication, we introduce IA techniques for PLC networks, for which the results confirm a significant sum-rate improvement. To overcome the implementation burden of CSI availability for IA techniques, we then study Blind Interference Alignment (BIA) for PLC X-network, and show that the characteristics of the PLC channel thwart simple implementation of this technique via impedance modulation. We therefore resort to a transmission scheme with multiple receiving ports, which can achieve the maximum multiplexing gain for this network.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat