Engineering Commons^™

Integrating Laser Charging And Drones For Secure Edge Computing, Weiqi Liu

Dissertations

Drone-mounted base stations (DBSs) have emerged as a promising solution to enhance the flexibility and coverage of wireless networks, potentially revolutionizing communication systems. This dissertation explores the integration of DBSs into 5G and beyond networks, focusing on methodologies to optimize their deployment and performance. A laser charging-enabled DBS framework is proposed to extend flight time and enhance network coverage. By leveraging laser charging technology, the DBS can receive continuous energy transmission from a ground-based charging station while providing communication services to users. The framework is formulated as an optimization problem to jointly maximize flight time and communication data rate, while …

Machine Learning-Based Design Of Doppler Tolerant Radar, Kyle Peter Wensell

Dissertations

In this work, machine learning theory is applied to the design of a radar detector in order to train a machine learning-based detector that is robust against Doppler shifts. The radar system is designed to work with data that would be otherwise intractable to conventional optimal detector design, such as transmitted noise waveforms and the effects of one-bit quantization at the receiver. The detection performance of the one-bit receiver is shown to match the performance of the derived square-law sign correlator detector. The resulting learning-based detector also introduces Doppler tolerance to the system, which allows for the successful detection of …

Graphene 2d Heterostructures For Thz Applications, Omnia Samy Shaaban

Dissertations

THz technology is a promising field that has various applications in communication, medical imaging and diseases’ detection, scanning, and the food industry. Since THz technology is still in its early stages, there is a lot of work to be done to obtain devices that work efficiently in the THz range. One of these devices is THz absorbers that are the basic building blocks for the next generation THz systems whether in communication systems, imaging or shielding. THz absorbers are structures that can absorb electromagnetic waves in the THz range (0.1-10 THz). THz absorbers can be wideband (absorb a wide range …

5g New Radio Access And Core Network Slicing For Next-Generation Network Services And Management, Abdullah Ridwan Hossain

Dissertations

In recent years, fifth-generation New Radio (5G NR) has attracted much attention owing to its potential in enhancing mobile access networks and enabling better support for heterogeneous services and applications. Network slicing has garnered substantial focus as it promises to offer a higher degree of isolation between subscribers with diverse quality-of-service requirements. Integrating 5G NR technologies, specifically the mmWave waveform and numerology schemes, with network slicing can unlock unparalleled performance so crucial to meeting the demands of high throughput and sub-millisecond latency constraints.

While conceding that optimizing next-generation access network performance is extremely important, it needs to be acknowledged that …

Sparse Methods For Blind Source Separation Of Frequency Hopping Rf Sources, Anushreya Ghosh

Dissertations

Blind source separation (BSS) is performed on frequency hopping (FH) sources. These radio frequency (RF) signals are observed by a uniform linear array (ULA) over a Spatial Channel Model (SCM) in four different propagation environments: (i) line-of-sight (LOS), (ii) single-cluster, (iii) multiple-cluster, and (iv) LOS with interference. The sources are spatially sparse, and their activity is intermittent and assumed to follow a hidden Markov model (HMM). BSS is achieved by utilizing direction of arrival (DOA) of the sources and clusters. A sparse detection framework is applied to obtain estimates of the sources' FH and DOA patterns. The solutions are binned …

Resource Allocation, User Association And Placement For Uav-Assisted Communications, Shuai Zhang

Dissertations

In the past few years, unmanned aerial vehicle (UAV)-assisted heterogeneous network has attracted significant attention due to its wide range of applications, such as disaster rescue and recovery, ground macro base station (MBS) traffic offloading, communications for temporary events, and data collection for further processing in Internet of Things (IoT). A UAV can act as a flying base station (BS) to quickly recover the communication coverage in the disaster area when the regular terrestrial infrastructure is malfunctioned. The UAV-assisted heterogeneous network can effectively provision line of sight (LoS) communication links and therefore can mitigate potential signal shadowing and blockage. The …

Private Information Retrieval And Function Computation For Noncolluding Coded Databases, Sarah A. Obead

Dissertations

The rapid development of information and communication technologies has motivated many data-centric paradigms such as big data and cloud computing. The resulting paradigmatic shift to cloud/network-centric applications and the accessibility of information over public networking platforms has brought information privacy to the focal point of current research challenges. Motivated by the emerging privacy concerns, the problem of private information retrieval (PIR), a standard problem of information privacy that originated in theoretical computer science, has recently attracted much attention in the information theory and coding communities. The goal of PIR is to allow a user to download a message from a …

Objectively Determining The Language-Related Communication Challenges For In-Flight Operations, Fehime Utkan

Dissertations

Communication breakdowns between pilots and air traffic controllers (ATCs) have been identified as primary factors in fatal airplane accidents (Wu et. al., 2019; Bauh & Stolzer, 2018; Ritter, 1996; Eurocontrol, 2011). Although there are various aspects that have affected communication efficiency, language-related issues have been mostly associated with transmissions involved in serious incidents, especially in multicultural flight environments (Sexton & Helmrich, 2000). More than 2,000 people have died in accidents where miscommunication was a primary factor (Bauh & Stolzer, 2018; Patty, 2016). By the year of 2025, the air transportation system is projected to become more complex, and the volume …

Communications With Spectrum Sharing In 5g Networks Via Drone-Mounted Base Stations, Liang Zhang

Dissertations

The fifth generation wireless network is designed to accommodate enormous traffic demands for the next decade and to satisfy varying quality of service for different users. Drone-mounted base stations (DBSs) characterized by high mobility and low cost intrinsic attributes can be deployed to enhance the network capacity. In-band full-duplex (IBFD) is a promising technology for future wireless communications that can potentially enhance the spectrum efficiency and the throughput capacity. Therefore, the following issues have been identified and investigated in this dissertation in order to achieve high spectrum efficiency and high user quality of service.

First, the problem of deploying DBSs …

Storage Systems For Mobile-Cloud Applications, Nafize R. Paiker

Dissertations

Mobile devices have become the major computing platform in todays world. However, some apps on mobile devices still suffer from insufficient computing and energy resources. A key solution is to offload resource-demanding computing tasks from mobile devices to the cloud. This leads to a scenario where computing tasks in the same application run concurrently on both the mobile device and the cloud.

This dissertation aims to ensure that the tasks in a mobile app that employs offloading can access and share files concurrently on the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. …

Vision-Based Framework For Monitoring Of Eating Behavior Of Persons With Alzheimer’S Disease, Haitham Al-Anssari

Dissertations

Dementia is a syndrome used to describe an array of significant declines in cognitive abilities due to progressive and irreversible loss of neurons and brain functioning. This neurodegeneration seriously affects daily life activities like driving, shopping, working and speaking. Among these, Alzheimer’s disease is the most common type of dementia, with individuals experiencing loss of memory and thinking and reasoning skills. Due to cognitive decline, individuals with Alzheimer’s often suffer from malnutrition, since they do not eat, even when food is presented, and must be fed with assistance. This assistance presents a significant burden of time to caregivers, and consequently …

Integrated Compressive Sensing And Feature Descriptors- A Framework For Facial Recognition Systems, Ali Kadhem Jaber

Dissertations

Facial recognition is still a challenge in many applications, particularly in surveillance, security systems, and human-computer interactive (HCI) tools. The impact of real-world environmental variations on the performance of any facial recognition system can be significant. These variations may include illumination, facial expressions, poses, disguises (facial hair, glasses or cosmetics) and partial face occlusion. Furthermore, the number of images (samples) needed for facial recognition systems can be very large, much larger than what is typically required by an algorithm, and this is often made worse with expansion of the feature space dimensionality. Truly, the “curse of dimensionality” haunts any real-time …

Intelligent Approaches For Modeling And Optimizing Hvac Systems, Iii Raymond Tesiero

Dissertations

Advanced energy management control systems (EMCS), or building automation systems (BAS), offer an excellent means of reducing energy consumption in heating, ventilating, and air conditioning (HVAC) systems while maintaining and improving indoor environmental conditions. This can be achieved through the use of computational intelligence and optimization. This research will evaluate model-based optimization processes (OP) for HVAC systems utilizing MATLAB, genetic algorithms and self-learning or self-tuning models (STM), which minimizes the error between measured and predicted performance data. The OP can be integrated into the EMCS to perform several intelligent functions achieving optimal system performance. The development of several self-learning HVAC …

Adaptive Security-Aware Scheduling For Packet Switched Networks Using Real-Time Multi-Agent Systems, Ma'en Saleh Saleh

Dissertations

Conventional real-time scheduling algorithms are in care of timing constraints; they don’t pay any attention to enhance or optimize the real-time packet’s security performance. In this work, we propose an adaptive security-aware scheduling with congestion control mechanism for packet switching networks using real-time agentbased systems. The proposed system combines the functionality of real-time scheduling with the security service enhancement, where the real-time scheduling unit uses the differentiated-earliest-deadline-first (Diff-EDF) scheduler, while the security service enhancement scheme adopts a congestion control mechanism based on a resource estimation methodology.

The security service enhancement unit was designed based on two models: singlelayer and weighted …