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
Andrew Riachi
An Investigation Into The Memory Consumption of Web Browsers and A Memory Profiling Tool Using Linux SmapsWhen & Where:
Nichols Hall, Room 246 (Executive Conference Room)
Committee Members:
Prasad Kulkarni, ChairPerry Alexander
Drew Davidson
Heechul Yun
Abstract
Web browsers are notorious for consuming large amounts of memory. Yet, they have become the dominant framework for writing GUIs because the web languages are ergonomic for programmers and have a cross-platform reach. These benefits are so enticing that even a large portion of mobile apps, which have to run on resource-constrained devices, are running a web browser under the hood. Therefore, it is important to keep the memory consumption of web browsers as low as practicable.
In this thesis, we investigate the memory consumption of web browsers, in particular, compared to applications written in native GUI frameworks. We introduce smaps-profiler, a tool to profile the overall memory consumption of Linux applications that can report memory usage other profilers simply do not measure. Using this tool, we conduct experiments which suggest that most of the extra memory usage compared to native applications could be due the size of the web browser program itself. We discuss our experiments and findings, and conclude that even more rigorous studies are needed to profile GUI applications.
Elizabeth Wyss
A New Frontier for Software Security: Diving Deep into npmWhen & Where:
Eaton Hall, Room 2001B
Committee Members:
Drew Davidson, ChairAlex Bardas
Fengjun Li
Bo Luo
J. Walker
Abstract
Open-source package managers (e.g., npm for Node.js) have become an established component of modern software development. Rather than creating applications from scratch, developers may employ modular software dependencies and frameworks--called packages--to serve as building blocks for writing larger applications. Package managers make this process easy. With a simple command line directive, developers are able to quickly fetch and install packages across vast open-source repositories. npm--the largest of such repositories--alone hosts millions of unique packages and serves billions of package downloads each week.
However, the widespread code sharing resulting from open-source package managers also presents novel security implications. Vulnerable or malicious code hiding deep within package dependency trees can be leveraged downstream to attack both software developers and the end-users of their applications. This downstream flow of software dependencies--dubbed the software supply chain--is critical to secure.
This research provides a deep dive into the npm-centric software supply chain, exploring distinctive phenomena that impact its overall security and usability. Such factors include (i) hidden code clones--which may stealthily propagate known vulnerabilities, (ii) install-time attacks enabled by unmediated installation scripts, (iii) hard-coded URLs residing in package code, (iv) the impacts of open-source development practices, (v) package compromise via malicious updates, (vi) spammers disseminating phishing links within package metadata, and (vii) abuse of cryptocurrency protocols designed to reward the creators of high-impact packages. For each facet, tooling is presented to identify and/or mitigate potential security impacts. Ultimately, it is our hope that this research fosters greater awareness, deeper understanding, and further efforts to forge a new frontier for the security of modern software supply chains.
Alfred Fontes
Optimization and Trade-Space Analysis of Pulsed Radar-Communication Waveforms using Constant Envelope ModulationsWhen & Where:
Nichols Hall, Room 246 (Executive Conference Room)
Committee Members:
Patrick McCormick, ChairShannon Blunt
Jonathan Owen
Abstract
Dual function radar communications (DFRC) is a method of co-designing a single radio frequency system to perform simultaneous radar and communications service. DFRC is ultimately a compromise between radar sensing performance and communications data throughput due to the conflicting requirements between the sensing and information-bearing signals.
A novel waveform-based DFRC approach is phase attached radar communications (PARC), where a communications signal is embedded onto a radar pulse via the phase modulation between the two signals. The PARC framework is used here in a new waveform design technique that designs the radar component of a PARC signal to match the PARC DFRC waveform expected power spectral density (PSD) to a desired spectral template. This provides better control over the PARC signal spectrum, which mitigates the issue of PARC radar performance degradation from spectral growth due to the communications signal.
The characteristics of optimized PARC waveforms are then analyzed to establish a trade-space between radar and communications performance within a PARC DFRC scenario. This is done by sampling the DFRC trade-space continuum with waveforms that contain a varying degree of communications bandwidth, from a pure radar waveform (no embedded communications) to a pure communications waveform (no radar component). Radar performance, which is degraded by range sidelobe modulation (RSM) from the communications signal randomness, is measured from the PARC signal variance across pulses; data throughput is established as the communications performance metric. Comparing the values of these two measures as a function of communications symbol rate explores the trade-offs in performance between radar and communications with optimized PARC waveforms.
Qua Nguyen
Hybrid Array and Privacy-Preserving Signaling Optimization for NextG Wireless CommunicationsWhen & Where:
Zoom Defense, please email jgrisafe@ku.edu for link.
Committee Members:
Erik Perrins, ChairMorteza Hashemi
Zijun Yao
Taejoon Kim
KC Kong
Abstract
This PhD research tackles two critical challenges in NextG wireless networks: hybrid precoder design for wideband sub-Terahertz (sub-THz) massive multiple-input multiple-output (MIMO) communications and privacy-preserving federated learning (FL) over wireless networks.
In the first part, we propose a novel hybrid precoding framework that integrates true-time delay (TTD) devices and phase shifters (PS) to counteract the beam squint effect - a significant challenge in the wideband sub-THz massive MIMO systems that leads to considerable loss in array gain. Unlike previous methods that only designed TTD values while fixed PS values and assuming unbounded time delay values, our approach jointly optimizes TTD and PS values under realistic time delays constraint. We determine the minimum number of TTD devices required to achieve a target array gain using our proposed approach. Then, we extend the framework to multi-user wideband systems and formulate a hybrid array optimization problem aiming to maximize the minimum data rate across users. This problem is decomposed into two sub-problems: fair subarray allocation, solved via continuous domain relaxation, and subarray gain maximization, addressed via a phase-domain transformation.
The second part focuses on preserving privacy in FL over wireless networks. First, we design a differentially-private FL algorithm that applies time-varying noise variance perturbation. Taking advantage of existing wireless channel noise, we jointly design differential privacy (DP) noise variances and users transmit power to resolve the tradeoffs between privacy and learning utility. Next, we tackle two critical challenges within FL networks: (i) privacy risks arising from model updates and (ii) reduced learning utility due to quantization heterogeneity. Prior work typically addresses only one of these challenges because maintaining learning utility under both privacy risks and quantization heterogeneity is a non-trivial task. We approach to improve the learning utility of a privacy-preserving FL that allows clusters of devices with different quantization resolutions to participate in each FL round. Specifically, we introduce a novel stochastic quantizer (SQ) that ensures a DP guarantee and minimal quantization distortion. To address quantization heterogeneity, we introduce a cluster size optimization technique combined with a linear fusion approach to enhance model aggregation accuracy. Lastly, inspired by the information-theoretic rate-distortion framework, a privacy-distortion tradeoff problem is formulated to minimize privacy loss under a given maximum allowable quantization distortion. The optimal solution to this problem is identified, revealing that the privacy loss decreases as the maximum allowable quantization distortion increases, and vice versa.
This research advances hybrid array optimization for wideband sub-THz massive MIMO and introduces novel algorithms for privacy-preserving quantized FL with diverse precision. These contributions enable high-throughput wideband MIMO communication systems and privacy-preserving AI-native designs, aligning with the performance and privacy protection demands of NextG networks.
Arin Dutta
Performance Analysis of Distributed Raman Amplification with Different Pumping ConfigurationsWhen & Where:
Nichols Hall, Room 246 (Executive Conference Room)
Committee Members:
Rongqing Hui, ChairMorteza Hashemi
Rachel Jarvis
Alessandro Salandrino
Hui Zhao
Abstract
As internet services like high-definition videos, cloud computing, and artificial intelligence keep growing, optical networks need to keep up with the demand for more capacity. Optical amplifiers play a crucial role in offsetting fiber loss and enabling long-distance wavelength division multiplexing (WDM) transmission in high-capacity systems. Various methods have been proposed to enhance the capacity and reach of fiber communication systems, including advanced modulation formats, dense wavelength division multiplexing (DWDM) over ultra-wide bands, space-division multiplexing, and high-performance digital signal processing (DSP) technologies. To maintain higher data rates along with maximizing the spectral efficiency of multi-level modulated signals, a higher Optical Signal-to-Noise Ratio (OSNR) is necessary. Despite advancements in coherent optical communication systems, the spectral efficiency of multi-level modulated signals is ultimately constrained by fiber nonlinearity. Raman amplification is an attractive solution for wide-band amplification with low noise figures in multi-band systems.
Distributed Raman Amplification (DRA) have been deployed in recent high-capacity transmission experiments to achieve a relatively flat signal power distribution along the optical path and offers the unique advantage of using conventional low-loss silica fibers as the gain medium, effectively transforming passive optical fibers into active or amplifying waveguides. Also, DRA provides gain at any wavelength by selecting the appropriate pump wavelength, enabling operation in signal bands outside the Erbium doped fiber amplifier (EDFA) bands. Forward (FW) Raman pumping configuration in DRA can be adopted to further improve the DRA performance as it is more efficient in OSNR improvement because the optical noise is generated near the beginning of the fiber span and attenuated along the fiber. Dual-order FW pumping scheme helps to reduce the non-linear effect of the optical signal and improves OSNR by more uniformly distributing the Raman gain along the transmission span.
The major concern with Forward Distributed Raman Amplification (FW DRA) is the fluctuation in pump power, known as relative intensity noise (RIN), which transfers from the pump laser to both the intensity and phase of the transmitted optical signal as they propagate in the same direction. Additionally, another concern of FW DRA is the rise in signal optical power near the start of the fiber span, leading to an increase in the non-linear phase shift of the signal. These factors, including RIN transfer-induced noise and non-linear noise, contribute to the degradation of system performance in FW DRA systems at the receiver.
As the performance of DRA with backward pumping is well understood with relatively low impact of RIN transfer, our research is focused on the FW pumping configuration, and is intended to provide a comprehensive analysis on the system performance impact of dual order FW Raman pumping, including signal intensity and phase noise induced by the RINs of both 1st and the 2nd order pump lasers, as well as the impacts of linear and nonlinear noise. The efficiencies of pump RIN to signal intensity and phase noise transfer are theoretically analyzed and experimentally verified by applying a shallow intensity modulation to the pump laser to mimic the RIN. The results indicate that the efficiency of the 2nd order pump RIN to signal phase noise transfer can be more than 2 orders of magnitude higher than that from the 1st order pump. Then the performance of the dual order FW Raman configurations is compared with that of single order Raman pumping to understand trade-offs of system parameters. The nonlinear interference (NLI) noise is analyzed to study the overall OSNR improvement when employing a 2nd order Raman pump. Finally, a DWDM system with 16-QAM modulation is used as an example to investigate the benefit of DRA with dual order Raman pumping and with different pump RIN levels. We also consider a DRA system using a 1st order incoherent pump together with a 2nd order coherent pump. Although dual order FW pumping corresponds to a slight increase of linear amplified spontaneous emission (ASE) compared to using only a 1st order pump, its major advantage comes from the reduction of nonlinear interference noise in a DWDM system. Because the RIN of the 2nd order pump has much higher impact than that of the 1st order pump, there should be more stringent requirement on the RIN of the 2nd order pump laser when dual order FW pumping scheme is used for DRA for efficient fiber-optic communication. Also, the result of system performance analysis reveals that higher baud rate systems, like those operating at 100Gbaud, are less affected by pump laser RIN due to the low-pass characteristics of the transfer of pump RIN to signal phase noise.
Audrey Mockenhaupt
Using Dual Function Radar Communication Waveforms for Synthetic Aperture Radar Automatic Target RecognitionWhen & Where:
Nichols Hall, Room 246 (Executive Conference Room)
Committee Members:
Patrick McCormick, ChairShannon Blunt
Jon Owen
Abstract
As machine learning (ML), artificial intelligence (AI), and deep learning continue to advance, their applications become more diverse – one such application is synthetic aperture radar (SAR) automatic target recognition (ATR). These SAR ATR networks use different forms of deep learning such as convolutional neural networks (CNN) to classify targets in SAR imagery. An emerging research area of SAR is dual function radar communication (DFRC) which performs both radar and communications functions using a single co-designed modulation. The utilization of DFRC emissions for SAR imaging impacts image quality, thereby influencing SAR ATR network training. Here, using the Civilian Vehicle Data Dome dataset from the AFRL, SAR ATR networks are trained and evaluated with simulated data generated using Gaussian Minimum Shift Keying (GMSK) and Linear Frequency Modulation (LFM) waveforms. The networks are used to compare how the target classification accuracy of the ATR network differ between DFRC (i.e., GMSK) and baseline (i.e., LFM) emissions. Furthermore, as is common in pulse-agile transmission structures, an effect known as ’range sidelobe modulation’ is examined, along with its impact on SAR ATR. Finally, it is shown that SAR ATR network can be trained for GMSK emissions using existing LFM datasets via two types of data augmentation.
Past Defense Notices
Gordon Ariho
Multipass SAR Processing for Ice Sheet Vertical Velocity and Tomography Measurements and Application of Reduced Rank MMSE to Spectrally Efficient Radar DesignWhen & Where:
Zoom Meeting, please contact jgrisafe@ku.edu for link
Committee Members:
Jim Stiles, ChairJohn Paden (Co-Chair)
Shannon Blunt
Carl Leuschen
Emily Arnold
Abstract
First Topic: Ice sheets impact sea-level change and hence their response to climatic variations needs to be continually monitored and studied. We propose to apply multipass differential interferometric synthetic aperture radar (DInSAR) techniques to data from the Multichannel Coherent Radar Depth Sounder (MCoRDS) to measure the vertical displacement of englacial layers within an ice sheet. DInSAR’s accuracy is usually on the order of a small fraction of the wavelength (e.g. millimeter to centimeter precision is common) in monitoring ground displacement along the radar line of sight (LOS). In the case of ice sheet internal layers, vertical displacement is estimated by compensating for the spatial baseline using precise trajectory information and estimates of the cross-track layer slope from direction of arrival analysis. Preliminary results from a high accumulation region near Camp Century in northwest Greenland and Summit Station in central Greenland are presented here. We propose to extend this work by implementing a maximum likelihood estimator that jointly estimates the vertical velocity, the cross-track internal layer slope, and the unknown baseline error due to GPS and INS errors. The multipass algorithm will be applied to additional flights from the decade long NASA Operation IceBridge airborne mission that flew MCoRDS on many repeated flight tracks. We also propose to improve the accuracy of tomographic swaths produced from multipass measurements and investigate the possibility to use focusing matrices to improve wideband tomographic processing.
Second Topic: With the increased demand for bandwidth-hungry applications in the telecommunications industry, radar applications can no longer enjoy the generous frequency allocations within the UHF band. Spectral efficiency, if achievable, leads to the freeing of portions of the radar bandwidth to facilitate spectrum sharing between radar and other wireless systems. A decrease in bandwidth leads to worse radar resolution. In certain scenarios, reduced resolution is acceptable, and bandwidth may be compromised for spectral efficiency. An iterative reduced rank MMSE algorithm based on marginal Fisher information is proposed and investigated to minimize the loss of resolution with the tradeoff of degraded side-lobe performance. The algorithm is applied to the radar measurement model with simulated range profiles and performance results discussed.
Kishanram Kaje
Complex Field Modulation in Direct Detection SystemsWhen & Where:
Zoom Meeting, please contact jgrisafe@ku.edu for link
Committee Members:
Rongqing Hui, ChairChristopher Allen
Victor Frost
Erik Perrins
Jie Han
Abstract
Even though fiber optics communication is providing a high bandwidth channel to achieve high speed data transmission, there is still a need for higher spectral efficiency, faster data processing speeds while reduced resource requirements due to ever increasing data and media traffic. Various multilevel modulation and demodulation techniques are used to improve spectral efficiency. Although, spectral efficiency is improved, there are other challenges that arise while doing so such as requirement for high speed electronics, receiver sensitivity, chromatic dispersion, operational flexibility etc. Here, we investigate complex high speed field modulation techniques in direct detection systems to improve spectral efficiency while focusing to reduce resources required for implementation, compensating for linear and nonlinear impairments in fiber optics communication systems.
We first demonstrated a digital-analog hybrid subcarrier multiplexing (SCM) technique which can reduce the requirement of high speed electronics such as ADC and DAC, while providing wideband capability, high spectral efficiency, operational flexibility and controllable data-rate granularity.
With conventional Quadrature Phase Shift Keying (QPSK), to achieve maximum spectral efficiency, we need high spectral efficient Nyquist filters which takes high FPGA resources for digital signal processing (DSP). Hence, we investigated Quadrature Duobinary (QDB) modulation as a solution to reduce the FPGA resources required for DSP while achieving spectral efficiency of 2bits/s/Hz. Currently we are investigating all analog single sideband (SSB) complex field modulated direct detection system. Here, we are trying to achieve higher spectral efficiency by using QDB modulation scheme in comparison to QPSK while avoiding signal-signal beat interference (SSBI) by providing a guard-band based approach.
Another topic we investigated, both through simulation and experiments, is a way to compensate for nonlinearities generated by semiconductor optical amplifiers (SOA) when operated in gain saturation in a field modulated direct detection systems. We successfully, compensated for the SOA nonlinearities in the presence of fiber chromatic dispersion, which was post compensated using electronic dispersion compensation after restoring the phase information of the received signal using Kramers-Kronig receiver.
Theresa Moore
Array Manifold Calibration for Multichannel SAR SoundersWhen & Where:
Zoom Meeting, please contact jgrisafe@ku.edu for link
Committee Members:
James Stiles, ChairJohn Paden (Co-Chair)
Shannon Blunt
Carl Leuschen
Leigh Stearns
Abstract
Multichannel synthetic aperture radar (SAR) sounders with cross-track antenna arrays map ice sheet basal morphology in three dimensions with a single pass using tomography. The tomographic ice-sheet imaging method leverages parametric direction-finding techniques like the Maximum Likelihood Estimator and the Multiple Signal Classification algorithm to resolve scattering interfaces in elevation. These techniques have received considerable attention because of their potential to exceed the Rayleigh resolution limit of the receive array under certain conditions. This performance is predicated on having perfect knowledge of the frequency-dependent response of the array to directional sources, referred to as the array manifold. Even modest amounts of mismatch between the assumed and actual manifold model degrade the accuracy of parametric angle estimators and erode their sought-after superresolution potential.
Array manifold calibration refers to the step in the array processor of refining our representation of the directional array-response vectors by accounting for factors such as mutual coupling, geometric uncertainties, and channel-to-channel gain imbalances. Pilot calibration requires measuring the in-situ array over its field of view and storing the manifold in a look-up-table. Alternatively, the array transfer function may be modeled parametrically to levy an estimation framework for characterizing mismatch. Parametric calibration theory for sensor position perturbations has been established for several decades. However, there remains a marked disconnect between the signal processing and antennas communities regarding how to include mutual coupling within the parametric framework. To date, literature lacks validated studies that address parameterization of the embedded element patterns for direction-finding arrays.
A manifold calibration methodology is proposed for an airborne, multichannel ice-penetrating SAR. The methodology departs from conventional approaches by extracting calibration targets from SAR imagery of well-understood terrain to empirically characterize the directional responses of the integrated array's embedded element patterns. This work presents a Maximum Likelihood Estimator for nonlinear parameters common across disjoint calibration sets that has the potential to improve the accuracy of our estimated geometric uncertainties by increasing the total Fisher information in our observations. The investigation contributes to specific gaps in array signal processing and remote sensing literature by treating the unique challenge of calibrating in-situ arrays used in direction-finding applications.
Dung Viet Nguyen
Particle Swarm Deep Reinforcement Learning for Base Station Optimization in Urban AreasWhen & Where:
Zoom Meeting, please contact jgrisafe@ku.edu for link
Committee Members:
Taejoon Kim, ChairMorteza Hashemi
Heechul Yun
Abstract
Densifying the network by deploying many small cells has attracted significant interests from wireless industries for exploring its potential to facilitating the proposed many data-intensive use cases in fifth-generation (5G) networks. While such efforts are essential, there are gaps in fundamental research and practical deployment of small cells. It is clear that increased interference from adjacent cells, called intercell interference, is the major limiting factor. In order to address this issue, each base station's parameters should be properly controlled to mitigate the intercell interference. We call the task of designing the base station's parameters the base station optimization (BSO) problem in this work. Due to the large numbers of small cells and mobile users distributed over the network, solving BSO by precisely modeling the network conditions is almost infeasible. One of the popular approaches that has attracted many researchers recently is a data-based framework called machine learning (ML). While supervised ML is prevalent, it requires pre-labeled off-line data that are not available in many wireless scenarios. Unlike supervised ML, reinforcement learning (RL) can handle this situation because it is based on designing a good policy to find the best exploration-\&-exploitation tradeoff without the pre-labeled training dataset. Thus, in this work, we present a new approach to the problem of BSO, based on the application of deep reinforcement learning (DRL) to enhance the quality of service (QoS) experienced by mobile users. To speed up the exploration of DRL, we employ particle swarm optimization (PSO), which shows improved QoS and convergence compared to conventional DRL.
Dalton Hahn
Delving Into DevOps: Examining the Security Posture of State-of-Art Service Mesh ToolsWhen & Where:
Zoom Meeting, please contact jgrisafe@ku.edu for link
Committee Members:
Alex Bardas, ChairDrew Davidson
Fengjun Li
Abstract
Explosion in the use of containers and a shift in software engineering design from monolithic applications into a microservice model has driven a need for software solutions that can manage the deployment and networking of microservices at enterprise-level scale. Service meshes have emerged as a promising solution to the microservice eruption that enterprise software is currently experiencing. This work examines service meshes from the perspective of security solutions offered within the tools and how the available security mechanisms impact the original goals of service meshes. As part of this study, we propose a relevant threat model to the service mesh domain and consider two different levels of configuration of these tools. The first configuration we study is the “idealized” configuration; one in which a system administrator has deep knowledge and the ability to properly configure and enable all available security mechanisms within a service mesh. The second configuration scenario is that of the default configuration deployment of service meshes. Through this work, we consider a range of adversarial approaches and scenarios that comprehensively cover the available attack surface of service meshes. Our experimental results show a distinct lack in security support of service meshes when deployed under default configurations, and additionally, in many idealized scenarios studied, it is possible for attackers to achieve some of their adversarial goals, presenting tempting targets to attackers.
Calen Carabajal
Development of Compact UWB Transmit Receive Modules and Filters on Liquid Crystal Polymer for RadarWhen & Where:
Zoom Meeting, please contact jgrisafe@ku.edu for link
Committee Members:
Carl Leuschen, ChairFernando Rodriguez-Morales (Co-Chair)
Christopher Allen
Abstract
Microwave and mm-wave radars have been used extensively for remote sensing applications, and ultra-wideband (UWB) radars have provided particular utility in geophysical research due to their ability to resolve narrowly-spaced targets or media interface levels. With increased availability of unmanned aerial vehicles (UAS) and expanded application of microwave radars into other realms requiring portability, miniaturization of radar systems is a crucial goal. This thesis presents the design and development of various microwave components for a compact, airborne snow-probing radar with multi-gigahertz bandwidth and cm-scale vertical resolution.
First, a set of UWB, compact transmit and receive modules with custom power sequencing circuits is presented. These modules were rapid-prototyped as an initial step toward the miniaturization of the radar’s front-end, using a combination of custom and COTS circuits. The transmitter and receiver modules operate in the 2–18 GHz range. Laboratory and field tests are discussed, demonstrating performance that is comparable to previous, connectorized implementations of the system, while accomplishing a 5:1 size reduction.
Next, a set of miniaturized band-pass and low-pass filters is developed and demonstrated. This work addressed the lack of COTS circuits with adequate performance in a sufficiently small form factor that is compatible with the planar integration required in a multi-chip module.
The filters presented here were designed for manufacture on a multi-layer liquid crystal polymer (LCP) substrate. A detailed trade study to assess the effects of potential manufacturing tolerances is presented. A framework for the automated creation of panelized design variations was developed using CAD tools. Thirty-two design variations with two different types of launches (microstrip and grounded co-planar waveguide) were successfully simulated, fabricated and tested, showing good electrical performance both as individual filters and cascaded to offer outstanding out-of-band rejection. The size of the new filters is 1 cm x 1 cm x 150 µm, a vertical reduction of over 90% and a reduction of total cascaded length by over 80%.
Kunal Karnik
Augment drone GPS telemetry data onto its Optical Flow linesWhen & Where:
Zoom Meeting, please contact jgrisafe@ku.edu for link
Committee Members:
Andy Gill, ChairDrew Davidson
Prasad Kulkarni
Abstract
Optical flow is the apparent displacement of objects, surfaces and edges in a visual scene caused because of the relative motion between an observer and the scene. This apparent displacement (parallax) is used to render optical flow lines for such objects which hold invaluable information about their motion. In this research, we apply this technique to study a video file. We will locate pixels of objects with strong optical flow displacements. Which will enable us to identify an aerial multirotor craft (drone) from possible object pixels. Further we will not only mark the drones path using optical flow lines, but we will also add value to the video file by augmenting the drone’s 3D Telemetry data onto its optical flow lines.
Guojun Xiong
Distributed Filter Design and Power Allocation for Small-Cell MIMO NetworkWhen & Where:
Zoom Meeting, please contact jgrisafe@ku.edu for link
Committee Members:
Taejoon Kim, ChairMorteza Hashemi
Erik Perrins
Abstract
The deluge of wireless data traffic catalyzed by the growing number of data-intensive devices has motivated the deployment of small-cell in fifth-generation (5G) networks. A primary challenge for deploying dense small-cell networks comes from the lack of practical techniques that efficiently handle the increased network interference at a low cost. This has aroused considerable interest in the distributed precoder/combiner coordination techniques that leverage the channel reciprocity, while relying on the local channel state information (CSI) available at each communication end. In this project, a distributed approach is proposed to the problem of signal-to-interference-plus-noise-ratio (SINR)-guaranteed power minimization (SGPM) for multicell multiuser (MCMU) multiple-input multiple-output (MIMO) systems. Unlike prior SGPM approaches, the technique is based on solving necessary and sufficient optimality conditions, which are derived by decomposing the original problem into forward and backward (FB) subproblems, while ensuring the strong duality of each subproblems. The proposed distributed SGPM algorithm makes use of FB adaptation and Jacobi recursion for iterative filter design and power allocation, respectively, which guarantees target SINR performance as well as its convergence to a stationary point. Simulation results illustrate the enhanced power efficiency with the performance guarantees of the proposed method compared to the existing distributed techniques.
Jason Baxter
An FPGA Implementation of Carrier Phase and Symbol Timing Synchronization for 16-APSKWhen & Where:
Zoom Meeting, please contact jgrisafe@ku.edu for link
Committee Members:
Erik Perrins, ChairTaejoon Kim
Carl Leuschen
Abstract
Proper synchronization between a transmitter and receiver, in terms of carrier phase and symbol timing, is critical for reliable communication. Carrier phase synchronization is related to the frequency translation hardware, where perfect synchronization means that the local oscillators of the transmitter’s upconverter and receiver’s downconverter are aligned in phase and frequency. Timing synchronization is related to the analog-to-digital converter in the receiver, where perfect synchronization means that samples of the received signal are taken at transmitted symbol times. Perfect synchronization is unlikely in practical systems for a number of reasons, including hardware limitations and the independence of the transmitter and receiver. This thesis explores an FPGA implementation of a PLL-based carrier phase and symbol timing synchronization subsystem as part of a 16-APSK aeronautical telemetry receiver. The theory behind this subsystem is presented, and the hardware implementation of each component is described. Results demonstrate successful demodulation of a test signal, and system performance is shown to be comparable to double-precision floating point simulations in terms of error vector magnitude, synchronization lock time, and BER.
Adam Petz
An Infrastructure for Faithful Execution of Remote Attestation ProtocolsWhen & Where:
Zoom Meeting, please contact jgrisafe@ku.edu for link
Committee Members:
Perry Alexander, ChairDrew Davidson
Andy Gill
Prasad Kulkarni
Emily Witt
Abstract
Security decisions often rely on trust. An emerging technology for gaining trust in a remote computing system is remote attestation. Remote attestation is the activity of making a claim about properties of a target by supplying evidence to an appraiser over a network. Although many existing approaches to remote attestation wisely adopt a layered architecture–where the bottom layers measure layers above–the dependencies between components remain static and measurement orderings fixed. Further, they are often restricted to a specialized embedded platform, or only perform shallow measurements on a component of interest without considering the trustworthiness of its context or the attestation mechanism itself. For modern computing environments with diverse topologies, we can no longer fix a target architecture any more than we can fix a protocol to measure that architecture.
Copland is a domain-specific language and formal framework that provides a vocabulary for specifying the goals of layered attestation protocols. It remains configurable by measurement capability, participants, and platform topology, yet provides a precise reference semantics that characterizes system measurement events and evidence handling; a foundation for comparing protocol alternatives. The aim of this work is to refine the Copland semantics to a more fine-grained notion of attestation manager execution–a high-privilege thread of control responsible for invoking attestation services and bundling evidence results. This refinement consists of two cooperating components called the Copland Compiler and the Attestation Virtual Machine (AVM). The Copland Compiler translates a Copland specification into a sequence of primitive attestation instructions to be executed in the AVM. These components are implemented as functional programs in the Coq proof assistant and proved correct with respect to the Copland reference semantics. This formal connection is critical in order to trust that protocol specifications are faithfully carried out by the attestation manger implementation. We also explore synthesis of appraisal routines that leverage the same formally verified infrastructure to interpret evidence generated by Copland protocols and make trust decisions.