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Item Indigenous waveform development for spread spectrum communication(UMT.Lahore, 2024) Basmah AhmadThis research work presents a comprehensive comparative analysis of various phase codes, including Gold codes, Kasami codes, Barker codes, Frank codes, and chaotic codes. The study aimed to evaluate their performance in terms of autocorrelation, cross correlation properties, probability of false alarms and range doppler maps. Additionally, interpulse coding technique is applied to develop a waveform that exhibits desirable characteristics. The initial phase of the research involved a detailed investigation and theoretical analysis of each phase code. The properties of autocorrelation , cross correlation and Peak-To-Side-Lobe Ratio were evaluated for these codes, revealing their strengths and weaknesses in different scenarios. This comparative analysis provided valuable insights into the performance of phase codes, allowing for informed selection and optimization. In addition to it, the interpulse coding has also been applied to study various phase codes configurations. Furthermore, Kronecker product is also implemented to different phase codes configurations in order to analyze different methods to achieve improved results in terms of correlation properties. This research contributes to the understanding of phase codes’ properties and their suitability for different applications. The incorporation of range doppler analysis offers a promising approach, making it particularly valuable in scenarios where reliable communication is essential. The findings of this study can be advantageous in the development of future communication systems that utilize phase codes to achieve robust and efficient signal transmissionItem Indoor localization through wi-fi rf fingerprinting using machine learning(UMT.Lahore, 2024) Hafiza Faiza Zahid KhanGlobal Positioning System (GPS) is the most reliable solution for outdoor localization. However, the GPS signal has less penetration power and does not provide accurate position estimation for indoor areas. In this research, Wi-Fi RF fingerprinting using RSSI and Machine Learning is implemented to predict the location of a person in an indoor environment. Radio Frequency (RF) signals provide long-range area coverage and Wi-Fi – which is the most widely used communication technology utilizes RF signals for communication. RSSI is accessible to all devices and does not require any additional hardware for its implementation. This means that no additional or special hardware is required for the implementation of Wi-Fi-based indoor location methods. RSSI signals are highly affected by obstacles and changes in environmental characteristics. Therefore, collecting large amounts of RSSI data at different time instances is crucial. Hence, to overcome these limitations and improve the accuracy of the model Machine Learning is introduced. Machine Learning model – Extreme Gradient Boost is implemented in this research for indoor localization and is trained on the RF mapping of RSSI fingerprints. Every indoor has its unique characteristics and to compare the performance of the desired approach with the models trained on open-source data sets is inappropriate. Therefore, traditional Machine Learning models, KNN, SVM, and Random Forest are also applied to evaluate the performance of XGBoost. From the results obtained, it is proved that the XGBoost achieves the maximum percentage of F1- score as 98 % , outperforming KNN, SVM, and Random Forest at 96.75 %,95.34 %,and 97.65 % respectively. Index Terms: Indoor localization, machine learning, received strength indicator (RSSI), supervised machine learning, Wi-Fi fingerprinting.Item Design of bidirectional dual active bridge converter for ess in electrical vehicle application(UMT.Lahore, 2024) Rimsha MusharrafThis thesis presents a bidirectional DC-DC Dual Active Bridge converter for Electrical Vehicle application integrating with DC microgrid. The bidirectional DC-DC Dual Active Bridge (DAB) converter controls the power flow between the DC grid and the battery. The converter is simulated in Matlab Simulink. Steady state and transient response of the battery under constant current charging and constant voltage charging is investigated. The effects of different charging rates on the battery's internal resistance and charging time are evaluated and the effects of voltage limits on the battery's charging time and state of charge are analyzed. The battery's behavior under discharge is studied, and the effects of different discharge rates on the battery's capacity and voltage are evaluated. The results obtained from the simulation provide valuable insights into the performance of batteries and their behavior under different charging and discharging conditions working in conjunction with DC microgrid. The results obtained from simulation model indicate faster response in charging and discharging of battery. The study on battery transient and steady responses provides important insights for the design and optimization of battery energy storage systems (ESS) with DAB converters. Overall, this research can contribute to the development of more reliable and efficient EVs with advanced energy storage systems. Index Terms: Dual Active Bridge Converter (DAB), Electrical vehicle, Energy storage system (ESS)