Defense Notices


All students and faculty are welcome to attend the final defense of EECS graduate students completing their M.S. or Ph.D. degrees. Defense notices for M.S./Ph.D. presentations for this year and several previous years are listed below in reverse chronological order.

Students who are nearing the completion of their M.S./Ph.D. research should schedule their final defenses through the EECS graduate office at least THREE WEEKS PRIOR to their presentation date so that there is time to complete the degree requirements check, and post the presentation announcement online.

Upcoming Defense Notices

Luke Staudacher

Enabling Versal-Based Signal Processing Through a Development Framework and User Guide

When & Where:


Nichols Hall, Room 246 (Executive Conference Room)

Committee Members:

Jonathan Owen, Chair
Shannon Blunt
Carl Leuschen
Erik Perrins

Abstract

AMD’s latest generation of adaptive system-on-chip (SoC) devices, the Versal product family, offers enhanced processing capabilities that are attractive to researchers and system designers. However, these capabilities introduce a significant knowledge barrier, limiting the practical benefits of Versal devices compared to more mature platforms from AMD, Intel, and other industry vendors. This project addresses this challenge through two primary deliverables: a software framework and a comprehensive user manual targeting Versal development. The software framework, named RSL Versal Core, provides a framework for users unfamiliar with Versal devices by selectively abstracting away more complex design components. Using a small set of commands, users can synthesize a programmable logic (PL) design, compile a Linux operating system for the onboard Arm processor with PL communication support, and program supported development boards. Following initial setup, the framework also supports extended software and firmware development for specific project needs. The accompanying user manual documents both RSL Versal Core and broader Versal development concepts. It guides users through reproducing and customizing the framework outputs manually and introduces key architectural and design principles useful for effective Versal-based system development. Together, these deliverables enable new developers to rapidly gain proficiency with Versal platforms and enable implementation of digital signal processing (DSP) concepts.


William Powers

Implementation and Analysis of Robust System-Informed Waveform Design

When & Where:


Nichols Hall, Room 246 (Executive Conference Room)

Committee Members:

Jonathan Owen, Chair
Shannon Blunt
Carl Leuschen


Abstract

Due to rapid advances in high-speed analog-to-digital conversion and software-defined architectures, modern radar systems increasingly shift signal generation and conditioning into the digital domain. These architectures enable high-fidelity signal capture and provide substantial flexibility in waveform synthesis and signal processing that was previously impractical in analog implementations. Despite these advances, however, achievable radar performance remains fundamentally constrained by the physical transmit hardware through which the signal is ultimately realized. Nonlinear amplification, finite bandwidth, and memory effects introduce distortion that creates a significant gap between idealized waveform design and the waveform that is physically radiated.

To address this limitation, this work proposes a system-aware radar waveform design framework that couples data-driven system identification with deterministic optimization to generate waveforms tailored to the underlying transmit hardware. A complex baseband memory polynomial model is developed to characterize nonlinear transmit-chain behavior using loopback measurements, where $\ell_1$-regularized LASSO estimation is employed to improve robustness against ill-conditioning and feature redundancy. Under this architecture, a generalized integrated sidelobe level (GISL) objective is reformulated using logarithmic scalarization to produce a numerically stable and Pareto-tunable optimization criterion capable of balancing output energy and sidelobe suppression. Additionally, efficient vectorized gradient expressions are derived using Wirtinger calculus and implemented using gradient-based descent and the limited-memory BFGS algorithm for practical high-dimensional waveform synthesis.

To validate the framework, a comprehensive hardware-in-the-loop testbench was developed supporting direct model identification and experimental evaluation of optimized waveform performance. Simulation and experimental results demonstrate that continuous-phase FM waveforms exhibit strong inherent robustness to nonlinear distortion, while phase-coded waveforms with large instantaneous phase discontinuities show significantly greater sensitivity to transmit-chain impairments. Across both waveform classes, the proposed framework achieves substantial improvements in output power efficiency and pulse compression performance relative to system-agnostic waveform design. These results demonstrate that transmitter constraints must be treated as fundamental design variables rather than secondary effects and establish system-aware optimization as a practical framework for next-generation radar waveform synthesis.


Cody Gish

Real-time GPU Based Arbitrary Waveform Generation Utilizing a Software-Defined Radar Platform

When & Where:


Nichols Hall, Room 246 (Executive Conference Room)

Committee Members:

Jonathan Owen, Chair
Shannon Blunt
Patrick McCormick


Abstract

Due to the ever-growing demand for access to the finite resources of the electromagnetic spectrum, significant effort has been directed toward improving spectrum utilization. This has become a particular challenge in radar transmission design, where waveform diversity techniques have emerged as a promising solution despite the accompanying implementation complexity. Diverse signals are inherently non-repeating and pose unique challenges in comparison to traditional radar waveforms. Software defined radios (SDRs) allow for traditional RF components and signal processing to be implemented and controlled in software rather than hardware, providing a platform for testing experimental radar algorithms. This thesis presents a real-time parallel implementation of five previously developed distinct waveform-diverse radar signals for use in a coherent SDR system. The implemented waveforms include stochastic waveform generation (StoWGe), multi-user radar communication (MURC), phase-attached radar communication (PARC), pseudo-random optimized frequency modulation (PRO-FM), and waveform recycling. To enable real-time generation at maximum SDR data rates, these waveforms are implemented using digital synthesis techniques via GPU parallel processing. This approach alleviates CPU resource limitations by offloading computationally intensive waveform generation tasks to the GPU, enabling continuous high-throughput operation. A custom asynchronous transmit and receive architecture is developed to integrate these GPU-accelerated waveforms with UHD-based SDR hardware. The system leverages a multithreaded framework approach that can sustain coherent and synchronized radar operation. To validate the system, a series of loopback testing across all waveforms and a variety of parameters is completed to confirm the execution of the generate-transmit-receive chain.


David Felton

Optimization and Evaluation of Physical Complementary Radar Waveforms

When & Where:


Nichols Hall, Room 129 (Apollo Auditorium)

Committee Members:

Shannon Blunt, Chair
Rachel Jarvis
Patrick McCormick
James Stiles
Zsolt Talata

Abstract

The RF spectrum is a precious, finite resource with ever-increasing demand. Consequently, the mandate to be a "good spectral neighbor" is in direct conflict with the requirements for high-performance sensing where correlation error is fundamentally limited. As such, matched-filter radar performance is often sidelobe-limited with estimation error being constrained by the time-bandwidth (TB) of the collective emission. The methods developed here seek to bridge this gap between idealized radar performance and practical utility via waveform design.    

Estimation error becomes more complex when employing pulse-agility. In doing so, range-sidelobe modulation (RSM) spreads energy across Doppler, rendering traditional methods ineffective. To address this, the gradient-based complementary-FM framework was developed to produce complementary sidelobe cancellation (CSC) after coherently combining subsets within a pulse-agile emission. In contrast to the majority of complementary signals, explored via phase-coding, these Comp-FM waveform subsets achieve CSC while preserving hardware-compatibility since they are FM (though design distortion is never completely avoided). Although Comp-FM addressed practicality via hardware amenability, CSC was localized to zero-Doppler. This work expands the Comp-FM notion to a Doppler-generalized (DG) framework, extending the cancellation condition to an arbitrary span. The same framework can likewise be employed to jointly optimize an entire coherent processing interval (CPI) to minimize RSM within the radar point-spread-function (PSF), thereby generalizing the notion of complementarity and introducing the potential for cognitive operation if sufficient scattering knowledge is available a-priori.          

Sensing with a single emitter is limited by self-inflicted error alone (e.g., clutter, sidelobes), while MIMO systems must additionally contend with the cross-responses from emitters operating concurrently (e.g., simultaneously, spatially proximate, in a shared spectrum), further degrading radar sensitivity. Now, total correlation error is dictated by the overlapping TB (i.e., how coincident are the signals) and number of operating emitters, compounding difficulty to estimate if left unaddressed. As such, the determination of "orthogonal waveforms" comprises a large portion of MIMO literature, though remains a phenomenological misnomer for pulsed emissions. Here, the notion of complementary-FM is applied to a multi-emitter context in which transmitter-amenable quasi-orthogonal subsets, occupying the same spectral band, are produced via a similar gradient-based approach. To further practicalize these MIMO-Comp-FM waveform subsets, the same "DG" approach described above, addressing the otherwise-default Doppler-induced degradation of complementary signals, is applied. In doing so, Doppler-independent separability and complementarity greatly improves estimation sensitivity for multi-emitter systems. 

This MIMO-Comp-FM framework is developed for standard matched filter processing. Coupling this framework with a "DG" form of the previously explored MIMO-MiCRFt is also investigated, illustrating the added benefit of pairing optimized subsets with similarly calibrated processing. 

Each of these methods is developed to address unique and increasingly complex sources of estimation error. All approaches are initially developed and evaluated via simulated analysis where ground-truth is known. Then, despite hardware-induced distortion being unavoidable, the MIMO-Comp-FM framework is confirmed via loopback measurements to preserve the majority of CSC that was observed in simulation. Finally, open-air demonstration of each approach validates practical utility on a radar system.


Past Defense Notices

Dates

ZAID HAYYEH

Exploiting Wireless Networks for Covert Communications

When & Where:


246 Nichols Hall

Committee Members:

Victor Frost, Chair
Shannon Blunt
Erik Perrins
David Petr
Jeffrey Lang

Abstract

The desire to hide communications has existed since antiquity. This includes hiding the existence of the transmission and the location of the sender. Wireless networks offer an opportunity for hiding a transmission by placing a signal in the radio frequency (RF) occupied by a target network which also has the added benefit of lowering its probability of detection. 

This research hides a signal within the RF environment of a packet based wireless (infrastructure) network. Specifically, in this research the interfering (covert) signal is placed in the guard band of the target network’s orthogonal frequency division multiplexed (OFDM) signal. We show that the existence of adaptive protocols allow the target network to adjust to the existence of the covert signal. In other words, the wireless network views the covert network as a minor change in the RF environment; this work shows that the covert signal can be indistinguishable from other wireless impairments such as fading. 

The impact of the covert signal on the target system performance is discovered through analysis and simulation; the analysis and simulation begin at the physical layer where the interaction between the target and covert systems occurs. After that, analysis is performed on the impact of the covert link on the target system at data-link layer. Finally, we analyze the performance of the target system at the transmission control protocol (TCP) layer which characterizes the end-to-end performance. The results of this research demonstrate the potential of this new method for hiding the transmission of information. The results of this research could encourage the creation of new protocols to protect these networks from exploitation of this manner.


RAMESH KUMAR DUGAR

Pulsed Doppler Lidar for Velocity Measurement using Coherent Detection

When & Where:


250 Nichols Hall

Committee Members:

Ron Hui, Chair
Glenn Prescott
Jim Stiles


Abstract

Measurement of wind velocity is of essential to enhance the wind energy utilization which is very important considering the fact that it one of most important renewable source of energy and LIDAR (Light Detection and Ranging) has become a very popular technology for such measurements. In this study, a pulsed Doppler Lidar operating at 1.5µm is demonstrated with coherent detection technique for measurement of velocity of spinning disc which is a hard target used in this project. This Lidar uses the principle of Doppler shift to measure the velocity and an Acousto-optic modulator is used for frequency shifting in the transmitter to produce an intermediate frequency. A data acquisition board (DAQ) was used to generate the pulses and also to process the data once it was collected by the receiver using mat lab. A graphical user interface was used to interface the DAQ with the system and changing parameters like PRF, pulse width, record directory etc. could be changed directly from the computer. A thorough study of literature has been done and same has been presented. The architecture of the Lidar, velocity results, future work and an analysis of SNR’s dependence on range and pulse energy under predefined atmospheric conditions will be discussed.


SREE HARSHA KAKARLA

Design of Transmitter and SMPS for Blood Oxygen Level Tomography

When & Where:


246 Nichols Hall

Committee Members:

Ron Hui, Chair
Chris Allen
James Stiles


Abstract

Ever since the invention of near infrared optical spectroscopy almost three decades ago, research has still been going actively to improve the accuracy of biological tissue oxygenation measurements and make it commercially available in clinics for medical diagnosis and imaging. Hemoglobin concentration in blood especially near brain can be found by determining the absorption and scattering coefficient of chromosphere at a particular wavelength. But there are many challenges to overcome when infrared light penetrates deeper into our skull which acts as a high scattering medium. This improvement has taken a new shape with the application of diffusion theory to separate the absorbed light and scattered light in tissues. With this motivation, in this project we designed a dual-frequency (120MHz and 125MHz) based two wavelengths LED transmitting system to transmit optical power through fibers and penetrate NIR light into a scattering medium which is then received by the detection and demodulation circuit for data acquisition. Different methods available to measure absorption and reduced scattering coefficient for non-homogenous medium will be discussed.


DONGSHENG ZHANG

Modeling Critical Node Attacks in Mobile Wireless Networks

When & Where:


246 Nichols Hall

Committee Members:

James Sterbenz, Chair
Victor Frost
Gary Minden
Bernhard Plattner
John Symons

Abstract

Understanding network behavior under challenges is essential to constructing a resilient and survivable network. Due to the mobility and wireless channel properties, it is more difficult to model and analyze mobile wireless networks under various challenges. We provide a comprehensive model to analyze malicious attacks against mobile ad hoc networks. We analyze comprehensive graph-theoretical properties and network performance of the dynamic networks under attacks against the critical nodes using both synthetic and real-world mobility traces. Our study provides insights into the design and construction of resilient and survivable mobile wireless networks.


JOHN GIBBONS

Modeling Content Lifespan in Online Social Networks Using Data Mining

When & Where:


246 Nichols Hall

Committee Members:

Arvin Agah, Chair
Perry Alexander
Jerzy Grzymala-Busse
Jim Miller
Prajna Dhar

Abstract

Online Social Networks (OSNs) are integrated into business, entertainment, politics, and education; they are integrated into nearly every facet of our everyday lives. They have played essential roles in milestones for humanity, such as the social revolutions in certain countries, to more day-to-day activities, such as streaming entertaining or educational materials. Not surprisingly, social networks are the subject of study, not only for computer scientists, but also for economists, sociologists, political scientists, and psychologists, among others. In this dissertation, we build a model that is used to classify content on the OSNs of Reddit, 4chan, Flickr, and YouTube according the types of lifespan their content have and the popularity tiers that the content reaches. The proposed model is evaluated using 10-fold cross-validation, using data mining techniques of Sequential Minimal Optimization (SMO), which is a support vector machine algorithm, Decision Table, Naïve Bayes, and Random Forest. The run times and accuracies are compared across OSNs, models, and data mining algorithms. 
Our experiments compared the runtimes and accuracy of SMO, Naïve Bayes, Decision Table, and Random Forest to classify the lifespan of content on Reddit, 4chan, and Flickr as well as classify the popularity tier of content on Reddit, 4chan, Flickr, and YouTube. The experimental results indicate that SMO is capable of outperforming the other algorithms in runtime across all OSNs. Decision Table has the longest observed runtimes, failing to complete analysis before system crashes in some cases. The statistical analysis indicates, with 95% confidence, there is no statistically significant difference in accuracy between the algorithms across all OSNs. Reddit content was shown, with 95% confidence, to be the OSN least likely to be misclassified. All other OSNs, were shown to have no statistically significant difference in terms of their content being more or less likely to be misclassified when compared pairwise with each other.


MIKE ZAKHAROV

Designing a Multichannel Sense-and-Avoid Radar for Small UASs

When & Where:


2001B Eaton Hall

Committee Members:

Chris Allen, Chair
Ron Hui
Jim Stiles


Abstract

To enhance the capabilities of autonomous flight systems for Unmanned Aircraft Systems (UASs), a multichannel Frequency-Modulated Continuous Wave (FMCW) collision-avoidance radar with a center frequency of 1.445 GHz is designed. The radar is intended to provide situational awareness for a 40% Yak-54 model aircraft by providing in real time range, radial velocity and angle-of-arrival (AoA) information on surrounding targets with an update rate of 10 Hz. A target’s range and Doppler is determined by employing a two-dimensional (2-D) Fast Fourier Transform (FFT) on the received signal which maps the target to a specific range-Doppler bin. Tests have shown that the proto-type radar is capable of providing range detection up to 430 m with an accuracy of 0.6 m for a target with a 1-m2 radar cross section (RCS). The radar is designed to provide a Doppler resolution of 10 Hz. An array of receiving antennas is used to determine a target’s elevation and azimuth angles by exploiting the received signal’s phase difference at each individual antenna. The AoA measurement error due to thermal noise was found to be less than 3° for a signal-to-noise ratio (SNR) of 18 dB.


YEFENG SUN

Optical Absorption Simulation by ZnTe/CdTe Superlattices Based on Kronig-Penney Model

When & Where:


246 Nichols Hall

Committee Members:

Ron Hui, Chair
Ken Demarest
Victor Frost


Abstract

Nowadays superlattices (SLs) are widely used as optical materials due to optical absorption properties. Short-period superlattices with certain optical properties such as InAs/GaSb type-II superlattices and ZnTe/CdTe superlattices can serve for mid-infrared (MIR) detection and solar cells. In this study, a standard Kronig-Penney model is applied to calculate the mini band structure of such SLs. On the basis of the energy-balance equation derived from the Boltzmann equation, a simple approach is used to calculate the optical absorption coefficient for the corresponding SL systems. Comparison of simulation results and experimental findings will be made in this study. And reasonable causes of error and future work will be discussed.


ADAM VAN HORN

Machine Learning Techniques for High Performance Engine Calibration

When & Where:


2001B Eaton Hall

Committee Members:

Arvin Agah, Chair
Jerzy Grzymala-Busse
James Miller
Christopher Depcik

Abstract

Ever since the advent of electronic fuel injection, auto manufacturers have been able to increase fuel efficiency and power production, and to meet stricter emission standards. Most of these systems use engine sensors (RPM, Throttle Position, etc.) in concert with look-up tables to determine the correct amount of fuel to inject. While these systems work well, it is time and labor intensive to fine tune the parameters for these look-up tables. Automobile manufacturers are able to absorb the cost of this calibration since the variation between engines in a new model line is often small enough as to be inconsequential for a specific calibration. 

However, a growing number of drivers are interested in modifying their vehicles with the intent of improving performance. While some aftermarket performance upgrades can be accounted for by the original manufacturer equipped (OEM) electronic control unit (ECU), other more significant changes, such as adding a turbocharger or installing larger fuel injectors, require more drastic accommodations. These modifications often require an entirely new ECU calibration or an aftermarket ECU to properly control the upgraded engine. The problem then, is that the driver becomes responsible for the calibration of the ECU of this “new” engine. However, most drivers are unable to devote the resources required to achieve a calibration of the same quality as the original manufacturers. At best, this results in reduced fuel economy and performance, and at worst, unsafe and possibly destructive operation of the engine. 

The purpose of this thesis is to design and develop—using machine learning techniques—an approximate predictive model from current engine data logs, which can be used to rapidly and incrementally improve the calibration of the engine. While there has been research into novel control methods for engine air-fuel ratio control, these methods are inaccessible to the majority of end users, either due to cost or the required expertise with engine calibration. This study shows that there is a great deal of promise in applying machine learning techniques to engine calibration and that the process of engine calibration can be expedited by the application of these techniques.


LANE RYAN

Polyphase-Coded FM Waveform Optimization within a LINC Transmit Architecture

When & Where:


246 Nichols Hall

Committee Members:

Chris Allen, Chair
Shannon Blunt
Jim Stiles


Abstract

Linear amplification using nonlinear components (LINC) is a design approach that can suppress the effects of the nonlinear distortion introduced by the transmitter. A typical transmitter design requirement is for the high power amplifier to be operated in saturation. The LINC approach described here employs a polyphase-coded FM (PCFM) waveform that is able to overcome this saturated amplifier distortion to greatly improve the spectral containment of the transmitted waveform. A two stage optimization process involving simulation and hardware-in-the-loop routines is used to create the final PCFM waveform code.


YUFEI CHENG

Performance Analysis of Different Traffic Types in Mobile Ad-hoc Networks

When & Where:


246 Nichols Hall

Committee Members:

James Sterbenz, Chair
Fengjun Li
Gary Minden


Abstract

Mobile Ad Hoc networks~(MANETs) present great challenges to new protocol design, especially in scenarios where nodes are high mobile. Routing protocols performance is essential to the performance of wireless networks especially in mobile ad-hoc scenarios. The development of new routing protocols requires comparing them against well-known protocols in various simulation environments. Furthermore, application traffic like transactional application traffic has not been investigated for domain-specific MANETs scenarios. Overall, there are not enough performance comparison work in the past literatures. This thesis presents extensive performance comparison work with MANETs and uses inclusive parameter sets including both highly-dynamic environment as well as low-mobility cases.