UNT Theses and Dissertations - 53 Matching Results

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Comparison of Source Diversity and Channel Diversity Methods on Symmetric and Fading Channels.
Channel diversity techniques are effective ways to combat channel fading and noise in communication systems. In this thesis, I compare the performance of source and channel diversity techniques on fading and symmetric continuous channels. My experiments suggest that when SNR is low, channel diversity performs better, and when SNR is high, source diversity shows better performance than channel diversity.
Study of the effects of background and motion camera on the efficacy of Kalman and particle filter algorithms.
This study compares independent use of two known algorithms (Kalmar filter with background subtraction and Particle Filter) that are commonly deployed in object tracking applications. Object tracking in general is very challenging; it presents numerous problems that need to be addressed by the application in order to facilitate its successful deployment. Such problems range from abrupt object motion, during tracking, to a change in appearance of the scene and the object, as well as object to scene occlusions, and camera motion among others. It is important to take into consideration some issues, such as, accounting for noise associated with the image in question, ability to predict to an acceptable statistical accuracy, the position of the object at a particular time given its current position. This study tackles some of the issues raised above prior to addressing how the use of either of the aforementioned algorithm, minimize or in some cases eliminate the negative effects
Electronic Sound Analysis with Hardware System and Remote Internet Display
Currently, standards from government agencies such as the National Institute for Occupation Safety and Health exist to aid in safeguarding individuals’ capacity for hearing, but only in factory settings in which large machines often produce loud levels of sound. Neglecting the fact that these preventative measures are only in place in the most limited of settings, no system currently exists to observe and report sound exposure levels in a manner timely or easily recognizable enough to adequately serve its purpose of hearing conservation. Musicians may also incur significant levels of risk for hearing loss in their day-to-day rehearsals and concerts, from high school marching bands to university wind bands. As a result, music school accrediting organizations such as the National Association of Schools of Music and even the European Union have begun taking steps meant to determine the risks associated with music. To meet these goals and improve upon current technologies, a system has been developed that electronically records sound levels utilizing modern hardware, increases the speed of reporting by transmitting data over computer networks and the Internet, and displays measures calculated from these data in a web browser for a highly viewable, user-friendly interface.
A Bidirectional Two-Hop Relay Network Using GNU Radio and USRP
A bidirectional two-hop relay network with decode-and-forward strategy is implemented using GNU Radio (software) and several USRPs (hardware) on Ubuntu (operating system). The relay communication system is comprised of three nodes; Base Station A, Base Station B, and Relay Station (the intermediate node). During the first time slot, Base Station A and Base Station B will each transmit data, e.g., a JPEG file, to Relay Station using DBPSK modulation and FDMA. For the final time slot, Relay Station will perform a bitwise XOR of the data, and transmit the XORed data to Base Station A and Base Station B, where the received data is decoded by performing another XOR operation with the original data.
Design and Implementation of Broad Band and Narrow Band Antennas and Their Applications
The thesis deals with the design and implementation of broadband and narrowband antennas and their applications in practical environment. In this thesis, a new concept for designing the UWB antenna is proposed based on the CRLH metamaterials and this UWB antenna covers a frequency range from 2.45 GHz to 11.6 GHz. Based on the design of the UWB antenna, another antenna is developed that can cover a very wide bandwidth i.e from 0.66 GHz to 120 GHz. This antenna can not only be used for UWB applications but also for other communication systems working below the UWB spectrum such as GSM, GPS, PCS and Bluetooth. The proposed antenna covering the bandwidth from 0.66 GHz to 120 GHz is by far the largest bandwidth antenna developed based on metamaterials. Wide band antennas are not preferred for sensing purpose as it is difficult to differentiate the received signals. A multiband antenna which can be used as a strain sensor for structural health monitoring is proposed. The idea is to correlate the strain applied along the length or width with the multiple resonant frequencies. This gives the advantage of detecting the strain applied along any direction (either length or width), thus increasing the sensing accuracy. Design and application of a narrow-band antenna as a temperature sensor is also presented. This sensor can be used to detect very high temperature changes (>10000C). This sensor does not require a battery, can be probed wirelessly, simple and can be easily fabricated, can withstand harsh environmental conditions.
Kalman Filtering Approach to Optimize OFDM Data Rate
This study is based on applying a non-linear mapping method, here the unscented Kalman filter; to estimate and optimize data rate resulting from the arrival rate having a Poisson distribution in an orthogonal frequency division multiplexing (OFDM) transmission system. OFDM is an emerging multi-carrier modulation scheme. With the growing need for quality of service in wireless communications, it is highly necessary to optimize resources in such a way that the overall performance of the system models should rise while keeping in mind the objective to achieve high data rate and efficient spectral methods in the near future. In this study, the results from the OFDM-TDMA transmission system have been used to apply cross-layer optimization between layers so as to treat different resources between layers simultaneously. The main controller manages the transmission of data between layers using the multicarrier modulation techniques. The unscented Kalman filter is used here to perform nonlinear mapping by estimating and optimizing the data rate, which result from the arrival rate having a Poisson distribution.
A Real-Time Electronic Sound Analysis System with Graphical User Interface
Noise-induced hearing loss is a serious problem common to musical environments. Current dosimetry technology is primarily designed for industrial environments and not suited for musical settings. At present, there are no government regulations that apply to the educational music environment as it relates to monitoring and prevention of hearing loss. Also, no system exists than can serve as a proactive tool in observation and reporting of sound exposure levels with the goal of hearing conservation. Newly proposed system takes a software based approach in designing a proactive dosimetry system that can assess the risk of sound noise exposure. It provides real-time feedback trough a graphical user interface that is capable of database storage for further study.
Data Compression Using a Multi-residue System (Mrs)
This work presents a novel technique for data compression based on multi-residue number systems. The basic theorem is that an under-determined system of congruences could be solved to accomplish data compression for a signal satisfying continuity of its information content and bounded in peak-to -peak amplitude by the product of relatively prime moduli,. This thesis investigates this property and presents quantitative results along with MATLAB codes. Chapter 1 is introductory in nature and Chapter 2 deals in more detail with the basic theorem. Chapter 3 explicitly mentions the assumptions made and chapter 4 shows alternative solutions to the Chinese remainder theorem. Chapter 5 explains the experiments in detail whose results are mentioned in chapter 6. Chapter 7 concludes with a summary and suggestions for future work.
An Interactive Tool to Investigate the Inference Performance of Network Dynamics From Data
Network structure plays a significant role in determining the performance of network inference tasks. An interactive tool to study the dependence of network topology on estimation performance was developed. The tool allows end-users to easily create and modify network structures and observe the performance of pole estimation measured by Cramer-Rao bounds. The tool also automatically suggests the best measurement locations to maximize estimation performance, and thus finds its broad applications on the optimal design of data collection experiments. Finally, a series of theoretical results that explicitly connect subsets of network structures with inference performance are obtained.
Design and Application of Phased Array System
Since its invention, phased array has been extensively applied in both military and civil areas. The applications include target detecting and tracking, space probe communication, broadcasting, human-machine interfaces, and remote sensing. Although the phased array applications show a broad range of potential market, there are some limitations of phased array's development: high cost, complex structure, narrow bandwidth, and high power consumption. Therefore, novel ideas are needed to reduce these constraints. In this thesis, several new approaches about the design and application of phased array are presents. First, the principle of phased array and fundamental design equations are introduced. Second, a new application of phased array antenna for radar respiration measurement is presented. By integrating a 4×4 Butler matrix with four-element antenna array, there will be four distinct main beams in radiation pattern. This new approach can improve the measurement accuracy and realize a high detecting rate. Third, a compact phased array antenna system based on dual-band operations is introduced. Dual-band function can make N-antenna system obtain 2N unique radiation beams (N is an integer) and achieve a significant size reduction compared to the conventional single-band system. To verify the design concept, a four-element phased array antenna working at 5GHz and 8GHz is designed and fabricated. The measurement results make a good agreement with the simulations. Finally, a novel architecture of steering phase feeding network by using bi-directional series-fed topology is presented. This bi-directional series-fed network needs less phase shifters and realizes steering phase function by applying control voltage.
Synthesis and Design of Microwave Filters and Duplexers with Single and Dual Band Responses
In this thesis the general Chebyshev filter synthesis procedure to generate transfer and reflection polynomials and coupling matrices were described. Key concepts such as coupled resonators, non-resonant nodes have been included. This is followed by microwave duplexer synthesis. Next, a technique to design dual band filter has been described including ways to achieve desired return loss and rejection levels at specific bands by manipulating the stopbands and transmission zeros. The concept of dual band filter synthesis has been applied on the synthesis of microwave duplexer to propose a method to synthesize dual band duplexers. Finally a numerical procedure using Cauchy method has been described to estimate the filter and duplexer polynomials from measured responses. The concepts in this thesis can be used to make microwave filters and duplexers more compact, efficient and cost effective.
An Application of Digital Video Recording and Off-grid Technology to Burrowing Owl Conservation Research
Through this research, engineering students and conservation biologists constructed an off-grid video system for observing western burrowing owls in El Paso, Texas. The burrowing owl has a declining population and their range decreasing, driving scientists' interest to see inside the den for observing critical nesting behavior. Texas Parks and Wildlife Department (TPWD) biologists wanted videos from inside the dark, isolated hillside owl burrows. This research yielded a replicable multi-camera prototype, empowering others to explore applications of engineering and wildlife monitoring. The remote station used an off-the-shelf video recording system, solar panels, charge controller, and lead acid batteries. Four local K-12 science educators participated in system testing at Lake Ray Roberts State Park through the Research Experiences for Teachers (RET, NSF #1132585) program, as well as four undergraduate engineering students as senior design research.
Design Space Exploration of Domain Specific CGRAs Using Crowd-sourcing
CGRAs (coarse grained reconfigurable array architectures) try to fill the gap between FPGAs and ASICs. Over three decades, the research towards CGRA design has produced number of architectures. Each of these designs lie at different points on a line drawn between FPGAs and ASICs, depending on the tradeoffs and design choices made during the design of architectures. Thus, design space exploration (DSE) takes a very important role in the circuit design process. In this work I propose the design space exploration of CGRAs can be done quickly and efficiently through crowd-sourcing and a game driven approach based on an interactive mapping game UNTANGLED and a design environment called SmartBricks. Both UNTANGLED and SmartBricks have been developed by our research team at Reconfigurable Computing Lab, UNT. I present the results of design space exploration of domain-specific reconfigurable architectures and compare the results comparing stripe vs mesh style, heterogeneous vs homogeneous. I also compare the results obtained from different interconnection topologies in mesh. These results show that this approach offers quick DSE for designers and also provides low power architectures for a suite of benchmarks. All results were obtained using standard cell ASICs with 90 nm process.
Dynamic WIFI Fingerprinting Indoor Positioning System
A technique is proposed to improve the accuracy of indoor positioning systems based on WIFI radio-frequency signals by using dynamic access points and fingerprints (DAFs). Moreover, an indoor position system that relies solely in DAFs is proposed. The walking pattern of indoor users is classified as dynamic or static for indoor positioning purposes. I demonstrate that the performance of a conventional indoor positioning system that uses static fingerprints can be enhanced by considering dynamic fingerprints and access points. The accuracy of the system is evaluated using four positioning algorithms and two random access point selection strategies. The system facilitates the location of people where there is no wireless local area network (WLAN) infrastructure deployed or where the WLAN infrastructure has been drastically affected, for example by natural disasters. The system can be used for search and rescue operations and for expanding the coverage of an indoor positioning system.
The Effect of Mobility on Wireless Sensor Networks
Wireless sensor networks (WSNs) have gained attention in recent years with the proliferation of the micro-electro-mechanical systems, which has led to the development of smart sensors. Smart sensors has brought WSNs under the spotlight and has created numerous different areas of research such as; energy consumption, convergence, network structures, deployment methods, time delay, and communication protocols. Convergence rates associated with information propagations of the networks will be questioned in this thesis. Mobility is an expensive process in terms of the associated energy costs. In a sensor network, mobility has significant overhead in terms of closing old connections and creating new connections as mobile sensor nodes move from one location to another. Despite these drawbacks, mobility helps a sensor network reach an agreement more quickly. Adding few mobile nodes to an otherwise static network will significantly improve the network’s ability to reach consensus. This paper shows the effect of the mobility on convergence rate of the wireless sensor networks, through Eigenvalue analysis, modeling and simulation.
An Interactive Framework for Teaching Fundamentals of Digital Logic Design and VLSI Design
Integrated Circuits (ICs) have a broad range of applications in healthcare, military, consumer electronics etc. The acronym VLSI stands for Very Large Scale Integration and is a process of making ICs by placing millions of transistors on a single chip. Because of advancements in VLSI design technologies, ICs are getting smaller, faster in speed and more efficient, making personal devices handy, and with more features. In this thesis work an interactive framework is designed in which the fundamental concepts of digital logic design and VLSI design such as logic gates, MOS transistors, combinational and sequential logic circuits, and memory are presented in a simple, interactive and user friendly way to create interest in students towards engineering fields, especially Electrical Engineering and Computer Engineering. Most of the concepts are explained in this framework by taking the examples which we see in our daily lives. Some of the critical design concerns such as power and performance are presented in an interactive way to make sure that students can understand these significant concepts in an easy and user friendly way.
Teaching Fundamentals of Digital Logic Design and VLSI Design Using Computational Textiles
This thesis presents teaching fundamentals of digital logic design and VLSI design for freshmen and even for high school students using e-textiles. This easily grabs attention of students as it is creative and interesting. Using e-textiles to project these concepts would be easily understood by students at young age. This involves stitching electronic circuits on a fabric using basic components like LEDs, push buttons and so on. The functioning of these circuits is programmed in Lilypad Arduino. By using this method, students get exposed to basic electronic concepts at early stage which eventually develops interest towards engineering field.
An Arduino Based Control System for a Brackish Water Desalination Plant
Water scarcity for agriculture is one of the most important challenges to improve food security worldwide. In this thesis we study the potential to develop a low-cost controller for a small scale brackish desalination plant that consists of proven water treatment technologies, reverse osmosis, cation exchange, and nanofiltration to treat groundwater into two final products: drinking water and irrigation water. The plant is powered by a combination of wind and solar power systems. The low-cost controller uses Arduino Mega, and Arduino DUE, which consist of ATmega2560 and Atmel SAM3X8E ARM Cortex-M3 CPU microcontrollers. These are widely used systems characterized for good performance and low cost. However, Arduino also requires drivers and interfaces to allow the control and monitoring of sensors and actuators. The thesis explains the process, as well as the hardware and software implemented.
Design fully-integrated dual-band two-stage class-E CMOS PA
In retrospect we can see that from the last century, wireless electronic technology has been in a rapid state of development. With the popularity of wireless communication, the power amplifier demand is rising. In general, magnitude, maximum noise figure, minimum noise figure, efficiency, and output power are important indicators of the amplifier. The IC industry is exploring how to reduce the additional cost and improve the high-frequency performance. Therefore, designing a strong adaptability and high cost performance of the PA has become a priority. As these technologies advance, the power amplifiers need to have better integration, lower cost, and lower power dissipation. Also, some special requirements are being asked in some areas, such as multi-mode and multi-band. In general, people have to use several power amplifiers parallel to frame a multifunction chip. Each of them working at different frequencies of interest has to have separate matching network, design, and area; also, the diversity amplifier prices will increase with the number of amplifiers, and its cost is also changed. In this thesis, because Class E power amplifier has lower power dissipation, 100% ideal efficiency, simple circuit structure, and strong applicability, the Class E is used as power amplifier in main stage. Moreover, in order to decrease input power and increase output power, the class A power amplifier is used as driver stage. It can use very small amount of power to provide a larger power. Moreover, we use a switched variable inductor and capacitor to constitute a dual band matching network which can let the PA work at more than one frequency. In fact, we design a Class A PA which is as a driver stage. Then, when we support 1 dBm input power, the driver stage can have 8 dBm output power. Also the output will be the input power …
Design of Frequency Output Pressure Transducer
Piezoelectricity crystal is used in different area in industry, such as downhole oil, gas industry, and ballistics. The piezoelectricity crystals are able to create electric fields due to mechanical deformation called the direct piezoelectric effect, or create mechanical deformation due to the effect of electric field called the indirect piezoelectric effect. In this thesis, piezoelectricity effect is the core part. There are 4 parts in the frequency output pressure transducer: two crystal oscillators, phase-locked loop (PLL), mixer, frequency counter. Crystal oscillator is used to activate the piezoelectricity crystal which is made from quartz. The resonance frequency of the piezoelectricity crystal will be increased with the higher pressure applied. The signal of the resonance frequency will be transmitted to the PLL. The function of the PLL is detect the frequency change in the input signal and makes the output of the PLL has the same frequency and same phase with the input signal. The output of the PLL will be transmitted to a Mixer. The mixer has two inputs and one output. One input signal is from the pressure crystal oscillator and another one is from the reference crystal oscillator. The frequency difference of the two signal will transmitted to the frequency counter from the output of the mixer. Thus, the frequency output pressure transducer with a frequency counter is a portable device which is able to measure the pressure without oscilloscope or computer.
Modeling and Control of a Motor System Using the Lego EV3 Robot
In this thesis, I present my work on the modeling and control of a motor system using the Lego EV3 robot. The overall goal is to apply introductory systems and controls engineering techniques for estimation and design to a real-world system. First I detail the setup of materials used in this research: the hardware used was the Lego EV3 robot; the software used was the Student 2014 version of Simulink; a wireless network was used to communicate between them using a Netgear WNA1100 wifi dongle. Next I explain the approaches used to model the robot’s motor system: from a description of the basic system components, to data collection through experimentation with a proportionally controlled feedback loop, to parameter estimation (through time-domain specification relationships, Matlab’s curve-fitting toolbox, and a formal least-squares parameter estimation), to the discovery of the effects of frictional disturbance and saturation, and finally to the selection and verification of the final model through comparisons of simulated step responses of the estimated models to the actual time response of the motor system. Next I explore three different types of controllers for use within the motor system: a proportional controller, a lead compensator, and a PID controller. I catalogue the design and performance results – both in simulation and on the real system – of each controller. One controller is then selected to be used within two Controls Systems Engineering final course projects, both involving the robot traveling along a predetermined route. The controller’s performance is analyzed to determine whether it improves upon the accumulation of error in the robot’s position when the projects are executed without control.
A Preliminary Controller Design for Drone Carried Directional Communication System
In this thesis, we conduct a preliminary study on the controller design for directional antenna devices carried by drones. The goal of the control system is to ensure the best alignment between two directional antennas so as to enhance the performance of air-to-air communication between the drones. The control system at the current stage relies on the information received from GPS devices. The control system includes two loops: velocity loop and position loop to suppress wind disturbances and to assure the alignment of two directional antennae. The simulation and animation of directional antennae alignment control for two-randomly moving drones was developed using SIMULINK. To facilitate RSSI-based antenna alignment control to be conducted in the future work, a study on initial scanning techniques is also included at the end of this thesis.
Applied Real-Time Integrated Distributed Control Systems: An Industrial Overview and an Implemented Laboratory Case Study
This thesis dissertation mainly compares and investigates laboratory study of different implementation methodologies of applied control systems and how they can be adopted in industrial, as well as commercial, automation applications. Namely the research paper aims to assess or evaluate eventual feedback control loops' performance and robustness over multiple conventional or state-of-the-art technologies in the field of applied industrial automation and instrumentation by implementing a laboratory case study setup: the ball on beam system. Hence, the paper tries to close the gap between industry and academia by: first, conducting a historical study and background information of main evolutional and technological eras in the field of industrial process control automation and instrumentation. Then, some related basic theoretical as well as practical concepts are reviewed in Chapter 2 of the report before displaying the detailed design. After that, the next Chapter, analyses the ball on beam control system problem as the case studied in the context of this research through reviewing previous literature, modeling and simulation. The following Chapter details the proposed design and implementation of the ball on beam case study as if it is under the introduced distributed industrial automation architecture. Finally, Chapter 5 concludes this work by listing several points leaned, remarks, and observations, and stating possible development and the future vision of this research.
The Design and Implementation of an Effective Vision-Based Leader-Follower Tracking Algorithm Using PI Camera
The thesis implements a vision-based leader-follower tracking algorithm on a ground robot system. One camera is the only sensor installed the leader-follower system and is mounted on the follower. One sphere is the only feature installed on the leader. The camera identifies the sphere in the openCV Library and calculates the relative position between the follower and leader using the area and position of the sphere in the camera frame. A P controller for the follower and a P controller for the camera heading are built. The vision-based leader-follower tracking algorithm is verified according to the simulation and implementation.
Measurement and Analysis of Indoor Air Quality Conditions
More than 80% of the people in urban regions and about 98% of cities in low and middle income countries have poor air quality according to the World Health Organization. People living in such environment suffer from many disorders like a headache, shortness of breath or even the worst diseases like lung cancer, asthma etc. The main objective of the thesis is to create awareness about the air quality and the factors that are causing air pollution to the people which is really important and provide tools at their convenience to measure and analyze the air quality. Taking real time air quality scenarios, various experiments were made using efficient sensors to study both the indoor and outdoor air quality. These experimental results will eventually help people to understand air quality better. An outdoor air quality data measurement system is developed in this research using Python programming to provide people an opportunity to retrieve and manage the air quality data and get the concentrations of the leading pollutants. The entire designing of the program is made to run with the help of a graphical user interface tool for the user, as user convenience is considered as one of the objectives of the thesis. A graphical user interface is made for the user convenience to visualize graphically the data from the database. The designed system is tested and used for the measurement and analysis of the outdoor air quality. This data will be available in the database so it can be used for analyzing the air quality data for several days or months or years. Using the GrayWolf system and the designed outdoor air quality data measurement system, both the indoor and outdoor air quality was measured to analyze and correlate.
The Modeling and Simulation of EV3 Motor Dynamics
This paper describes a procedure to find the transfer function for the Lego Mindstorms Ev3. Lego Mindstorms Ev3 can serve as the platform for a system modeling and a controller design course. It is economical and accessible. It is also very compatible with Matlab and Simulink. This platform can be used for concepts of modeling, feedback, and controller design. The main approach in this work focuses on the closed loop instead of open loop. Although this approach turns the problem into a more complicated puzzle, it reveals more details. In this work, different techniques have been used, such as time domain, root locus, and least square estimation. Different tools have also been utilized such as Matlab SISO tool, the Matlab System Identification tool, and Simulink. These methods and implementations assisted to acquire different types of transfer functions for the system. By simulating the transfer functions and comparing them with experimental studies, the matching scores were calculated to decide on the best transfer function. Finding the finest transfer function for this gadget enables us to prepare diverse practical undergraduate and graduate curricula.
Wireless Signal Conditioning
This thesis presents a new approach to extend and reduce the transmission range in wireless systems. Conditioning is defined as purposeful electromagnetic interference that affects a wireless signal as it propagates through the air. This interference can be used constructively to enhance a signal and increase its energy, or destructively to reduce energy. The constraints and limitations of the technology are described as a system model, and a flow chart is used to describe the circuit process. Remaining theoretical in nature, practical circuit implementations are foregone in the interest of elementary simulations depicting the interactions of modulated signals as they experience phase mismatch. Amplitude modulation and frequency modulation are explored with using both positive and negative conditioning, and conclusions to whether one is more suitable than the other are made.
BLE Controller Module for Wireless Sensor Networks
Sensors have been an integral part of our life since a long time. Traditionally, the transmit information to a data collection center through a physical wire. However, with the introduction of Bluetooth Low Energy (BLE) communication protocol, more research is being done into the field of wireless sensor networks (WSN). BLE was introduced to target low power applications. The CC2650 Launchpad designed by Texas Instruments (TI) can lead to a bulky final product. The aim was to design hardware for the CC2650 micro-controller with the aim of making it more compact for use in WSNs. A top-down approach was used wherein the available product is studied to identify the redundant and reverse engineer it to design a new product. A 2 layer printed circuit board (PCB) was designed which resulted in a 64 percent decrease in size compared to the Launchpad. Also, experiments were performed to test the proof of concept.
A Convergence Analysis of LDPC Decoding Based on Eigenvalues
Low-density parity check (LDPC) codes are very popular among error correction codes because of their high-performance capacity. Numerous investigations have been carried out to analyze the performance and simplify the implementation of LDPC codes. Relatively slow convergence of iterative decoding algorithm affects the performance of LDPC codes. Faster convergence can be achieved by reducing the number of iterations during the decoding process. In this thesis, a new approach for faster convergence is suggested by choosing a systematic parity check matrix that yields lowest Second Smallest Eigenvalue Modulus (SSEM) of its corresponding Laplacian matrix. MATLAB simulations are used to study the impact of eigenvalues on the number of iterations of the LDPC decoder. It is found that for a given (n, k) LDPC code, a parity check matrix with lowest SSEM converges quickly as compared to the parity check matrix with high SSEM. In other words, a densely connected graph that represents the parity check matrix takes more iterations to converge than a sparsely connected graph.
Development and Analysis of a Mobile Node Tracking Antenna Control System
A wireless communication system allows two parties to exchange information over long distances. The antenna is the component of a wireless communication system that allows information to be converted into electromagnetic radiation that propagates through the air. A system using an antenna with a highly directional beam pattern allows for high power transmission and reception of data. For a directional antenna to serve its purpose, it must be accurately pointed at the object it is communicating with. To communicate with a mobile node, knowledge of the mobile node's position must be gained so the directional antenna can be regularly pointed toward the moving target. The Global Positioning System (GPS) provides an accurate source of three-dimensional position information for the mobile node. This thesis develops an antenna control station that uses GPS information to track a mobile node and point a directional antenna toward the mobile node. Analysis of the subsystems used and integrated system test results are provided to assess the viability of the antenna control station.
Formation Control of Multi-Agent Systems
Formation control is a classical problem and has been a prime topic of interest among the scientific community in the past few years. Although a vast amount of literature exists in this field, there are still many open questions that require an in-depth understanding and a new perspective. This thesis contributes towards exploring the wide dimensions of formation control and implementing a formation control scheme for a group of multi-agent systems. These systems are autonomous in nature and are represented by double integrated dynamics. It is assumed that the agents are connected in an undirected graph and use a leader-follower architecture to reach formation when the leading agent is given a velocity that is piecewise constant. A MATLAB code is written for the implementation of formation and the consensus-based control laws are verified. Understanding the effects on formation due to a fixed formation geometry is also observed and reported. Also, a link that describes the functional similarity between desired formation geometry and the Laplacian matrix has been observed. The use of Laplacian matrix in stability analysis of the formation is of special interest.
Investigation of the Effect of Functional Units/Connectivity Arrangement on Energy Consumption of Reconfigurable Architectures Using an Interactive Design Framework
Allocation of expensive resources, (such as Multiplier) onto the CGRA has been of interest from quite some time. For these architectural solutions to fulfill the designers' requirements, it is of utmost importance that the design offers high performance, low power consumption, and effective area utilization. The allocation problem is studied using the UntangledII gaming environment, which has been developed at the Reconfigurable Computing Lab at UNT to discover the design of custom domain-specific architectures. This thesis explores several case-studies to investigate the arrangement of functional units and interconnects to achieve a low power, high performance, and flexible heterogeneous designs that can fit for a suite of applications. In the later part, several human mapping strategies of top and bottom players to design a custom domain-specific architecture are presented. Some common trends that were examined while analyzing the mapping strategies of the players are also discussed.
Optimization of an SDR Based Aerial Base Station
Most times people are unprepared to face natural disasters resulting in chaos, increased number of deaths, etc.Emergency responders need an efficiently working communication network to get in touch with the emergency services like hospitals, police, fire and rescue as well as people who are stranded. Such a network is also the need of the hour for survivors to contact their near and dear ones. One of the major barriers of communication during an emergency is the destruction of network elements. In case the communication devices survive the calamity, odds of the network getting congested are certainly high because almost everyone will be trying to use the same network resources. An important factor when dealing with emergency situations is the calls for an immediate response and an efficient Emergency Communication Systems (ECS). Currently there is a capability gap between existing ECS solutions and what we dream of achieving. Most current solutions do not meet cost or mobility constraints. An inexpensive, portable and mobile system will fulfill this capability gap. The main purpose of this research is to optimize the altitude and received signal strength of an aerial base station to provide maximum radio coverage on the ground as well as propose the best fit radio propagation channel model to carry out the experiment for the current scenario.
Reconfigurable Aerial Computing System: Design and Development
In situations where information infrastructure is destroyed or not available, on-demand information infrastructure is pivotal for the success of rescue missions. In this paper, a drone-carried on-demand information infrastructure for long-distance WiFi transmission system is developed. It can be used in the areas including emergency response, public event, and battlefield. In years development, the Drone WIFI System has developed from single-CPU platform, twin-CPU platform, Atmega2560 platform to NVIDIA Jetson TX2 platform. By the upgrade of the platform, the hardware shows more and more reliable and higher performance which make the application of the platform more and more exciting. The latest TX2 platform can provide real time and thermal video transmission, also application of deep learning of object recognition and target tracing. All these up-to-date technology brings more application scenarios to the system. Therefore, the system can serve more people in more scenarios.
A Cognitive MIMO OFDM Detector Design for Computationally Efficient Space-Time Decoding
In this dissertation a computationally efficient cognitive multiple-input multiple-output (MIMO) orthogonal frequency division duplexing (OFDM) detector is designed to decode perfect space-time coded signals which are able maximize the diversity and multiplexing properties of a rich fading MIMO channel. The adaptive nature of the cognitive detector allows a MIMO OFDM communication system to better meet to needs of future wireless communication networks which require both high reliability and low run-time complexity depending on the propagation environment. The cognitive detector in conjunction with perfect space-time coding is able to achieve up to a 2 dB bit-error rate (BER) improvement at low signal-to-noise ratio (SNR) while also achieving comparable runtime complexity in high SNR scenarios.
Modeling and Design of Antennas for Loosely Coupled Links in Wireless Power Transfer Applications
Wireless power transfer (WPT) systems are important in many areas, such as medical, communication, transportation, and consumer electronics. The underlying WPT system is comprised of a transmitter (TX) and receiver (RX). For biomedical applications, such systems can be implemented on rigid or flexible substrates and can be implanted or wearable. The efficiency of a WPT system is based on power transfer efficiency (PTE). Many WPT system optimization techniques have been explored to achieve the highest PTE possible. These are based on either a figure-of-merit (FOM) approach, quality factor (Q-factor) maximization, or by sweeping values for coil geometries. Four WPT systems for biomedical applications are implemented with inductive coupling. The thesis later presents an optimization technique for finding the maximum PTE of a range of frequencies and coil shapes through frequency, geometry and shape sweeping. Five optimized TX coil designs for different operating frequencies are fabricated for three shapes: square, hexagonal, and octagonal planar-spirals. The corresponding RX is implemented on polyimide tape with ink-jet-print (IJP) silver. At 80 MHz, the maximum measured PTE achieved is 2.781% at a 10 mm distance in the air for square planar-spiral coils.
Realization of LSTM Based Cognitive Radio Network
This thesis presents the realization of an intelligent cognitive radio network that uses long short term memory (LSTM) neural network for sensing and predicting the spectrum activity at each instant of time. The simulation is done using Python and GNU Radio. The implementation is done using GNU Radio and Universal Software Radio Peripherals (USRP). Simulation results show that the confidence factor of opportunistic users not causing interference to licensed users of the spectrum is 98.75%. The implementation results demonstrate high reliability of the LSTM based cognitive radio network.
Adaptive Slot Location in the Design of Slotted Microstrip Multi-Frequency Antenna for Radionavigation and Radiolocation Applications
In light of incidents and concerns regarding the vulnerability of the global positioning system (GPS), the main purpose of the thesis is to look at alternative systems for radio guidance and to put up a serious study on such alternatives with receive and transmit antenna. There is also the need to design such antennas with multiple frequencies to offer robustness in the unlikely event that such adversarial attacks on the GPS happen. The basis on which such alternative antennas are designed is a slotted microstrip. The characteristics of the slot or slots on the microstrip are analyzed by mapping their exact locations on the patch and then noting the resultant center frequencies, the return losses, and the bandwidth. The activities associated with this also focus on the design, fabrication, validation, and characterization of one or more slotted antennas prototypes. The measurement of the antenna prototypes does confirm several frequencies that coexist to see applications, in aeronautical radionavigation, fixed-mobile radionavigation, and radiolocation. The antennas could also feature in a wide-area augmentation system (WAAS), satellite ground link system (SGLS) as well as in surveillance and precision approach radars. Some variations of the antenna are deployed in the areas of law enforcement, surveillance, and unmanned aerial vehicle (UAV). Applications of the antenna in an unmanned ground vehicle (UGV) are feasible due to its multiple resonant frequencies. Radiolocation and radionavigation antennas have also been known to be mounted in UAVs or on tethered balloons along the borders of the United States to detect low-flying aircraft in support of drug interdiction programs.
Assistive Navigation Technology for Visually Impaired Individuals
Sight is essential in our daily tasks. Compensatory senses have been used for centuries by visually impaired individuals to navigate independently. The help of technology can minimize some challenges for visually impaired individuals. Assistive navigation technologies facilitate the pathfinding and tracing in indoor scenarios. Different modules are added to assistive navigation technologies to warn about the obstacles not only on the ground but about hanging objects. In this work, we attempt to explore new methods to assist visually impaired individuals in navigating independently in an indoor scenario. We employed a location estimation algorithm based on the fingerprinting method to estimate the initial location of the user. We mitigate the error of estimation with particle filter. The shortest path has been calculated with an A* algorithm. To provide the user with an accident-free experiment, we employed an obstacle avoidance algorithm capable of warning the users about the potential hazards. Finally, to provide an effective means of communication with the user, we employed text-to-speech and speech recognition algorithms. The main contribution of this work is to glue these modules together efficiently and affordably.
The Role of Eigenvalues of Parity Check Matrix in Low-Density Parity Check Codes
The new developments in coding theory research have revolutionized the application of coding to practical systems. Low-Density Parity Check (LDPC) codes form a class of Shannon limit approaching codes opted for digital communication systems that require high reliability. This thesis investigates the underlying relationship between the spectral properties of the parity check matrix and LDPC decoding convergence. The bit error rate of an LDPC code is plotted for the parity check matrix that has different Second Smallest Eigenvalue Modulus (SSEM) of its corresponding Laplacian matrix. It is found that for a given (n,k) LDPC code, large SSEM has better error floor performance than low SSEM. The value of SSEM decreases as the sparseness in a parity-check matrix is increased. It was also found from the simulation that long LDPC codes have better error floor performance than short codes. This thesis outlines an approach to analyze LDPC decoding based on the eigenvalue analysis of the corresponding parity check matrix.
Asynchronous Level Crossing ADC for Biomedical Recording Applications
This thesis focuses on the recording challenges faced in biomedical systems. More specifically, the challenges in neural signal recording are explored. Instead of the typical synchronous ADC system, a level crossing ADC is detailed as it has gained recent interest for low-power biomedical systems. These systems take advantage of the time-sparse nature of the signals found in this application. A 10-bit design is presented to help capture the lower amplitude action potentials (APs) in neural signals. The design also achieves a full-scale bandwidth of 1.2 kHz, an ENOB of 9.81, a power consumption of 13.5 microwatts, operating at a supply voltage of 1.8 V. This design was simulated in Cadence using 180 nm CMOS technology.
Design of Low-Power Front End Compressive Sensing Circuitry and Energy Harvesting Transducer Modeling for Self-Powered Motion Sensor
Compressed sensing (CS) is an innovative approach of signal processing that facilitates sub-Nyquist processing of bio-signals, such as a neural signal, electrocardiogram (ECG), and electroencephalogram (EEG). This strategy can be used to lower the data rate to realize ultra-low-power performance, As the count of recording channels increases, data volume is increased resulting in impermissible transmitting power. This thesis work presents the implementation of a CMOS-based front-end design with the CS in the standard 180 nm CMOS process. A novel pseudo-random sequence generator is proposed, which consists of two different types of D flip-flops that are used for obtaining a completely random sequence. This thesis work also includes the (reverse electrowetting-on-dielectric) REWOD based energy harvesting model for self-powered bio-sensor which utilizes the electrical energy generated through the process of conversion of mechanical energy to electrical energy. This REWOD based energy harvesting model can be a good alternative to battery usage, particularly for the bio-wearable applications. The comparative analysis of the results generated for voltage, current and capacitance of the rough surface model is compared to that of results of planar surface REWOD.
Development and Application of Novel Computer Vision and Machine Learning Techniques
The following thesis proposes solutions to problems in two main areas of focus, computer vision and machine learning. Chapter 2 utilizes traditional computer vision methods implemented in a novel manner to successfully identify overlays contained in broadcast footage. The remaining chapters explore machine learning algorithms and apply them in various manners to big data, multi-channel image data, and ECG data. L1 and L2 principal component analysis (PCA) algorithms are implemented and tested against each other in Python, providing a metric for future implementations. Selected algorithms from this set are then applied in conjunction with other methods to solve three distinct problems. The first problem is that of big data error detection, where PCA is effectively paired with statistical signal processing methods to create a weighted controlled algorithm. Problem 2 is an implementation of image fusion built to detect and remove noise from multispectral satellite imagery, that performs at a high level. The final problem examines ECG medical data classification. PCA is integrated into a neural network solution that achieves a small performance degradation while requiring less then 20% of the full data size.
Electrical Equivalent Modeling of the Reverse Electrowetting-on-Dielectric (REWOD) Based Transducer along with Highly Efficient Energy Harvesting Circuit Design towards Self-Powered Motion Sensor
Among various energy harvesting technologies reverse electrowetting-on-dielectric energy harvesting (REWOD) has been proved to harvest energy from low frequency motion such as many human motion activities (e.g. walking, running, jogging etc.). Voltage rectification and DC-DC boosting of low magnitude AC voltage from REWOD can be used to reliably self-power the wearable sensors. In this work, a commercial component-based rectifier and DC-DC converter is designed and experimentally verified, for further miniaturization standard 180 nm CMOS process is used to design the rectifier and the DC-DC boost converter.This work also includes the MATLAB based model for REWOD energy harvester for various REWOD models. In REWOD energy harvesting, a mechanical input during the motion causes the electrolyte placed in between two dissimilar electrodes to squeeze back and forth thereby periodically changing the effective interfacial area, hence generating alternating current. The alternating current is given to the rectifier design. There is no realistic model that has been developed yet for this technique. Thereby, a MATLAB based REWOD model is developed for the realistic simulation of the REWOD phenomenon. In the work, a comparison of different REWOD models such as planar surface, rough surface and porous models are performed demonstrating the variations in capacitance, current and voltage.
Estimation of Drone Location Using Received Signal Strength Indicator
The main objective of this thesis is to propose a UAV (also called as drones) location estimation system based on LoRaWAN using received signal strength indicator in a GPS denied environment. The drones are finding new applications in areas such as surveillance, search, rescue missions, package delivery, and precision agriculture. Nearly all applications require the localization of UAV during flight. Localization is the method of determining a UAVs physical position using a real or virtual coordinate system. This thesis proposes a LoRaWAN-based UAV location method and presents experimental findings from a prototype. The thesis mainly consists of two different sections: one is the distance estimation and the other is the location estimation. First, the distance is estimated based on the mean RSSI values which are recorded at the ground stations using the path loss model. Later using the slant distance estimation technique, the path loss model parameters L and C are estimated whose values are unknown at the beginning. These values completely depend on the environment. Finally, the trilateration system architecture is employed to find the 3-D location of the UAV.
Formation Control and Path Planning Strategies for Unmanned Aerial Vehicle Swarms
This dissertation focuses on the path planning of unmanned aerial vehicle (UAV) swarms under distributed and hybrid control scenarios. It presents two such models and analyzes them both from theory and practice. In the first method, a distributed formation control strategy for UAV swarm based on consensus law is presented. This model makes use of the fundamental concepts of leader-follower structure, social potential functions, and algebraic graph theory to jointly address flocking and de-confliction in the formation control problem. The impact of network topology on formation control is analyzed. It is shown that the degree distribution of the network representing the multi-agent system defines the rate at which formation is attained. Conditions for convergence and stability are derived. In the second method, a hybrid framework for path planning and coverage area by UAV swarms is presented. This strategy significantly improves the current labor-intensive and resource-constraint operations in aquaculture farms. To monitor the farms periodically, an optimized back-and-forth flight path based on the Shamos algorithm is utilized. A trajectory tracking strategy for UAV swarms under uncertain wind conditions is presented.
Group Testing with Greedy Algorithm
Group testing is all about identifying properties of a set of elements by testing them.
Traditional and Deep Learning Approaches to Color Image Compression and Pattern Recognition Problems
This thesis includes three separate research projects focusing on computer vision principles and deep learning pattern recognition problems. Chapter 3 entails color quantization applications using traditional Kmeans clustering techniques and random selection of color techniques within the red, green, blue (RGB) color space to maintain a high-quality image while significantly reducing image file size. Chapter 4 consists of a handwriting character recognition algorithm using backpropagation to classify 70,000 handwritten values from US Census Bureau employees and high school students. Chapter 5 proposes a novel classification technique for 109,446 unique heartbeat samples to identify areas of interest and assist medical professionals in diagnosing heart problems.
Advances to Convolutional Neural Network Architectures for Prediction and Classification with Applications in the First Dimensional Space
In the vast field of signal processing, machine learning is rapidly expanding its domain into all realms. As a constituent of this expansion, this thesis presents contributive work on advancements in machine learning algorithms by building on the shoulder of giants. The first chapter of this thesis contains enhancements to a CNN (convolutional neural network) for better classification of heartbeat arrhythmia. The network goes through a two stage development, the first being augmentations to the network and the second being the implementation of dropout. Chapter 2 involves the combination of CNN and LSTM (long short term memory) networks for the task of short-term energy use data regression. Exploiting the benefits of two of the most powerful neural networks, a unique, novel neural network is created to effectually predict future energy use. The final section concludes this work with directions for future works.
Efficient Convolutional Neural Networks for Image Processing Applications
Modern machine learning techniques focus on extremely deep and multi-pathed networks, resulting in large memory and computational requirements. This thesis explores techniques for designing efficient convolutional networks including pixel shuffling, depthwise convolutions, and various activation fucntions. These techniques are then applied to two image processing domains: single-image super-resolution and image compression. The super-resolution model, TinyPSSR, is one-third the size of the next smallest model in literature while performing similar to or better than other larger models on representative test sets. The efficient deep image compression model is significantly smaller than any other model in literature and performs similarly in both computational cost and reconstruction quality to the JPEG standard.
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