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Electrical and Computer Engineering Faculty Research & Creative Works

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Modeling And Mitigation Of Radio Frequency Interference For Wireless Devices, Chulsoon Hwang, Jun Fan Jan 2023

Modeling And Mitigation Of Radio Frequency Interference For Wireless Devices, Chulsoon Hwang, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

This article reviews the electromagnetic framework used to model radio frequency interference (RFI) and the resulting development of mitigation methods. With the rise of IoT devices, wireless devices in which RF antennas are integrated with high-performance digital systems in small form factors suffer from electromagnetic interference, known as RF interference or RF desensitization. The simple yet rigorous framework can be used for a systematic RFI-aware design, saving time and effort for trial-and-error troubleshooting.

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Distributed Detection Over Blockchain-Aided Internet Of Things In The Presence Of Attacks, Yiming Jiang, Jiangfan Zhang Jan 2023

Distributed Detection Over Blockchain-Aided Internet Of Things In The Presence Of Attacks, Yiming Jiang, Jiangfan Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

Distributed detection over a blockchain-aided Internet of Things (BIoT) network in the presence of attacks is considered, where the integrated blockchain is employed to secure data exchanges over the BIoT as well as data storage at the agents of the BIoT. We consider a general adversary model where attackers jointly exploit the vulnerability of IoT devices and that of the blockchain employed in the BIoT. The optimal attacking strategy which minimizes the Kullback-Leibler divergence is pursued. It can be shown that this optimization problem is nonconvex, and hence it is generally intractable to find the globally optimal solution to such …

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Machine Learning Based Pcb/Package Stack-Up Optimization For Signal Integrity, Wenchang Huang, Jiahuan Huang, Minseok Kim, Bumhee Bae, Chulsoon Hwang, Subin Kim Jan 2023

Machine Learning Based Pcb/Package Stack-Up Optimization For Signal Integrity, Wenchang Huang, Jiahuan Huang, Minseok Kim, Bumhee Bae, Chulsoon Hwang, Subin Kim

Electrical and Computer Engineering Faculty Research & Creative Works

PCB/package stack-up design optimization is time-consuming and requiring a great deal of experience. Although some iterative optimization algorithms are applied to implement automatic stack-up design, evaluating the results of each iteration is still time-intensive. This paper proposes a combined Bayesian optimization-artificial neural network (BO-ANN) algorithm, utilizing a trained ANN-based surrogate model to replace a 2D cross-section analysis tool for fast PCB/package stack-up design optimization. With the acceleration of ANN, the proposed BO-ANN algorithm can finish 100 iterations in 40 seconds while achieving the target characteristic impedance. To better generalize the BO-ANN algorithm, a strategy of effective dielectric calculation is applied …

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Development Of A Matlab-Based Structural Analysis Toolbox For Sensor Placement In A Multi-Domain Physical System, Arnold A. Fernandes, Kartikeya J.P. Veeramraju, Jonathan W. Kimball Jan 2023

Development Of A Matlab-Based Structural Analysis Toolbox For Sensor Placement In A Multi-Domain Physical System, Arnold A. Fernandes, Kartikeya J.P. Veeramraju, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper discusses a Bond Graph (BG) Structural Analysis Toolbox developed in MATLAB® (MATSAT) that performs causal analysis on the BG and assists the user in the sensor selection process for a multi-domain physical system. MATSAT contains modules for performing the Sequential Causality Assignment Procedure (SCAP) and Causal Path Search (CaPS). The modules can be combined to check for structural properties such as structural observability (SO) for any sensor set. The working of MATSAT is shown for standard systems. Verification of SCAP, CaPS, and necessary and sufficient SO conditions is shown.

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Continual Reinforcement Learning Formulation For Zero-Sum Game-Based Constrained Optimal Tracking, Behzad Farzanegan, Sarangapani Jagannathan Jan 2023

Continual Reinforcement Learning Formulation For Zero-Sum Game-Based Constrained Optimal Tracking, Behzad Farzanegan, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This study provides a novel reinforcement learning-based optimal tracking control of partially uncertain nonlinear discrete-time (DT) systems with state constraints using zero-sum game (ZSG) formulation. To address optimal tracking, a novel augmented system consisting of tracking error and its integral value, along with an uncertain desired trajectory, is constructed. A barrier function (BF) with a tradeoff factor is incorporated into the cost function to keep the state trajectories to remain within a compact set and to balance safety with optimality. Next, by using the modified value functional, the ZSG formulation is introduced wherein an actor–critic neural network (NN) framework is …

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Continual Optimal Adaptive Tracking Of Uncertain Nonlinear Continuous-Time Systems Using Multilayer Neural Networks, Irfan Ganie, S. (Sarangapani) Jagannathan Jan 2023

Continual Optimal Adaptive Tracking Of Uncertain Nonlinear Continuous-Time Systems Using Multilayer Neural Networks, Irfan Ganie, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This study provides a lifelong integral reinforcement learning (LIRL)-based optimal tracking scheme for uncertain nonlinear continuous-time (CT) systems using multilayer neural network (MNN). In this LIRL framework, the optimal control policies are generated by using both the critic neural network (NN) weights and single-layer NN identifier. The critic MNN weight tuning is accomplished using an improved singular value decomposition (SVD) of its activation function gradient. The NN identifier, on the other hand, provides the control coefficient matrix for computing the control policies. An online weight velocity attenuation (WVA)-based consolidation scheme is proposed wherein the significance of weights is derived by …

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Three-Terminal Noise Source Extraction From A Qi-Based Wireless Power Transfer System For Predicting Conducted Emissions, Srinath Penugonda, Siqi Bai, Varittha Sanphuang, Nevin Altunyurt, Hongseok Kim, Daryl G. Beetner, Jun Fan Jan 2023

Three-Terminal Noise Source Extraction From A Qi-Based Wireless Power Transfer System For Predicting Conducted Emissions, Srinath Penugonda, Siqi Bai, Varittha Sanphuang, Nevin Altunyurt, Hongseok Kim, Daryl G. Beetner, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

An equivalent method to extract a three-terminal noise source from a Qi-based wireless power transfer system is proposed in this article. This method is capable of extracting a source for both the positive (P) and negative (N) lines with respect to the third terminal (the ground chassis or reference plane). The extracted sources are independent of the setup configuration and can be used to predict currents or voltages on the P and N lines on a setup that is different from the extraction setup. In the following article, a three-terminal model independent of the setup configuration is first extracted. The …

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Patients Arms Segmentation And Gesture Identification Using Standalone 3d Lidar Sensors, Omar Rinchi, Nathanael Nisbett, Ahmad Alsharoa Jan 2023

Patients Arms Segmentation And Gesture Identification Using Standalone 3d Lidar Sensors, Omar Rinchi, Nathanael Nisbett, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

The intelligent and autonomous learning of patients' activities will lead to an incredible progression toward future smart e-health systems. With the recent advances in artificial intelligence, signal processing, and computational capabilities; light detection and ranging (LiDAR) technology can play a significant role in enhancing the current patients' activity recognition (PAR) systems. In this paper, we propose confidential and accurate patient arms behavior monitoring using a standalone three-dimensional (3D) LiDAR sensor. Due to the unavailability of LiDAR data, we use a computer-programmed 3D simulator to generate virtual-LiDAR (V-LiDAR) 3D point cloud data that simulates real patient movements. These virtual data are …

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Investigation Of The Radiation Mechanism Of Heatsinks Based On Characteristic Mode Theory, Xu Wang, Matthew Wu, Jagan Rajagopalan, Akshay Mohan, Donghyun Kim, Chulsoon Hwang Jan 2023

Investigation Of The Radiation Mechanism Of Heatsinks Based On Characteristic Mode Theory, Xu Wang, Matthew Wu, Jagan Rajagopalan, Akshay Mohan, Donghyun Kim, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Heatsinks may cause radiated emission and radio frequency interference problems when they are mounted on printed circuit boards. In this article, the radiation mechanism of heatsinks is systematically investigated using characteristic mode theory. The dipole moment is a commonly used equivalent source model for integrated circuits that drive radiated emission from heatsinks. On the basis of a simplified modal weighting coefficient formulation, the interactions between the dipole moment and the significant modes of the heatsink are efficiently evaluated, thus providing a clear physical insight into noise source placement. Finally, the grounding post design, a commonly used EMI mitigation method, is …

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Optimal Tracking Of Nonlinear Discrete-Time Systems Using Zero-Sum Game Formulation And Hybrid Learning, Behzad Farzanegan, S. (Sarangapani) Jagannathan Jan 2023

Optimal Tracking Of Nonlinear Discrete-Time Systems Using Zero-Sum Game Formulation And Hybrid Learning, Behzad Farzanegan, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a novel hybrid learning-based optimal tracking method to address zero-sum game problems for partially uncertain nonlinear discrete-time systems. An augmented system and its associated discounted cost function are defined to address optimal tracking. Three multi-layer neural networks (NNs) are utilized to approximate the optimal control and the worst-case disturbance inputs, and the value function. The critic weights are tuned using the hybrid technique, whose weights are updated once at the sampling instants and in an iterative manner over finite times within the sampling instants. The proposed hybrid technique helps accelerate the convergence of the approximated value functional …

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Aerial Lidar-Based 3d Object Detection And Tracking For Traffic Monitoring, Baya Cherif, Hakim Ghazzai, Ahmad Alsharoa, Hichem Besbes, Yehia Massoud Jan 2023

Aerial Lidar-Based 3d Object Detection And Tracking For Traffic Monitoring, Baya Cherif, Hakim Ghazzai, Ahmad Alsharoa, Hichem Besbes, Yehia Massoud

Electrical and Computer Engineering Faculty Research & Creative Works

The proliferation of Light Detection and Ranging (LiDAR) technology in the automotive industry has quickly promoted its use in many emerging areas in smart cities and internet-of-things. Compared to other sensors, like cameras and radars, LiDAR provides up to 64 scanning channels, vertical and horizontal field of view, high precision, high detection range, and great performance under poor weather conditions. In this paper, we propose a novel aerial traffic monitoring solution based on Light Detection and Ranging (LiDAR) technology. By equipping unmanned aerial vehicles (UAVs) with a LiDAR sensor, we generate 3D point cloud data that can be used for …

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Securing The Transportation Of Tomorrow: Enabling Self-Healing Intelligent Transportation, Elanor Jackson, Sahra Sedigh Sarvestani Jan 2023

Securing The Transportation Of Tomorrow: Enabling Self-Healing Intelligent Transportation, Elanor Jackson, Sahra Sedigh Sarvestani

Electrical and Computer Engineering Faculty Research & Creative Works

The safety of autonomous vehicles relies on dependable and secure infrastructure for intelligent transportation. The doctoral research described in this paper aims to enable self-healing and survivability of the intelligent transportation systems required for autonomous vehicles (AV-ITS). The proposed approach is comprised of four major elements: qualitative and quantitative modeling of the AV-ITS, stochastic analysis to capture and quantify interdependencies, mitigation of disruptions, and validation of efficacy of the self-healing process. This paper describes the overall methodology and presents preliminary results, including an agent-based model for detection of and recovery from disruptions to the AV-ITS.

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Virtual Synchronous Generator Control Using Twin Delayed Deep Deterministic Policy Gradient Method, Oroghene Oboreh-Snapps, Buxin She, Shah Fahad, Haotian Chen, Jonathan W. Kimball, Fangxing Li, Hantao Cui, Rui Bo Jan 2023

Virtual Synchronous Generator Control Using Twin Delayed Deep Deterministic Policy Gradient Method, Oroghene Oboreh-Snapps, Buxin She, Shah Fahad, Haotian Chen, Jonathan W. Kimball, Fangxing Li, Hantao Cui, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a data-driven approach that adaptively tunes the parameters of a virtual synchronous generator to achieve optimal frequency response against disturbances. In the proposed approach, the control variables, namely, the virtual moment of inertia and damping factor, are transformed into actions of a reinforcement learning agent. Different from the state-of-the-art methods, the proposed study introduces the settling time parameter as one of the observations in addition to the frequency and rate of change of frequency (RoCoF). In the reward function, preset indices are considered to simultaneously ensure bounded frequency deviation, low RoCoF, fast response, and quick settling time. …

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Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh Jan 2023

Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes an intelligent recommendation approach to facilitate personalized education and help students in planning their path to graduation. The goal is to identify a path that aligns with a student's interests and career goals and approaches optimality with respect to one or more criteria, such as time-to-graduation or credit hours taken. The approach is illustrated and verified through application to undergraduate curricula at the Missouri University of Science and Technology.

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A Physics-Based Model For Snapback-Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, Daryl G. Beetner Jan 2023

A Physics-Based Model For Snapback-Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

A simplified physical-based model for deep-snapback transient voltage suppressors (TVS) is developed in this article. While based on physics, the number of parameters and components is minimized, so the model can be tuned easily from available measurements of the packaged TVS. SPICE convergence issues seen in previous snapback device models are eliminated by adding nonlinear damping components to the model. No convergence issues were seen among any of the simulations performed for this study, which includes transmission-line pulse tests with multiple levels and rise times. The proposed model was used to represent two different TVS devices and was validated in …

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Optimal Adaptive Tracking Control Of Partially Uncertain Nonlinear Discrete-Time Systems Using Lifelong Hybrid Learning, Behzad Farzanegan, Rohollah Moghadam, Sarangapani Jagannathan, Pappa Natarajan Jan 2023

Optimal Adaptive Tracking Control Of Partially Uncertain Nonlinear Discrete-Time Systems Using Lifelong Hybrid Learning, Behzad Farzanegan, Rohollah Moghadam, Sarangapani Jagannathan, Pappa Natarajan

Electrical and Computer Engineering Faculty Research & Creative Works

This article addresses a multilayer neural network (MNN)-based optimal adaptive tracking of partially uncertain nonlinear discrete-time (DT) systems in affine form. By employing an actor–critic neural network (NN) to approximate the value function and optimal control policy, the critic NN is updated via a novel hybrid learning scheme, where its weights are adjusted once at a sampling instant and also in a finite iterative manner within the instants to enhance the convergence rate. Moreover, to deal with the persistency of excitation (PE) condition, a replay buffer is incorporated into the critic update law through concurrent learning. To address the vanishing …

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Coaxial Cable Sensing: Review And Perspective, Chen Zhu, Jie Huang Jan 2023

Coaxial Cable Sensing: Review And Perspective, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

The development of sensors has been a hot research topic in both scientific and industrial communities over the past decades. In recent years, a new sensing technology based on coaxial cables has emerged. Inspired by the fiber Bragg grating and motivated by the demand for structural health monitoring, coaxial cable Bragg gratings were first proposed and demonstrated with superior large strain capability ($>$ 5%). Mimicking the mature sensing modalities in fiber-optic sensors, coaxial cable sensors are developed to be promising alternatives for fiber-optic sensors in harsh-environment applications involving heavy duty, large strains, high pressures, and high temperatures. Over the …

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The Partial Elements Equivalent Circuit Method: The State Of The Art, Giulio Antonini, Albert E. Ruehli, Daniele Romano, Fabrizio Loreto Jan 2023

The Partial Elements Equivalent Circuit Method: The State Of The Art, Giulio Antonini, Albert E. Ruehli, Daniele Romano, Fabrizio Loreto

Electrical and Computer Engineering Faculty Research & Creative Works

This year marks about half a century since the birth of the technique known as the partial element equivalent circuit modeling approach. This method was initially conceived to model the behavior of interconnect-type problems for computer-integrated circuits. An important industrial requirement was the computation of general inductances in integrated circuits and packages. Since then, the advances in methods and applications made it suitable for modeling a large class of electromagnetic problems, especially in the electromagnetic compatibility (EMC)/signal and power integrity (SI/PI) areas. The purpose of this article is to present an overview of all aspects of the method, from its …

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Rafid: A Lightweight Approach To Radio Frequency Interference Detection In Time Domain Using Lstm And Statistical Analysis, Luke A. Smith, Vishesh Kumar Tanwar, Maciej Jan Zawodniok, Sanjay Kumar Madria Jan 2023

Rafid: A Lightweight Approach To Radio Frequency Interference Detection In Time Domain Using Lstm And Statistical Analysis, Luke A. Smith, Vishesh Kumar Tanwar, Maciej Jan Zawodniok, Sanjay Kumar Madria

Electrical and Computer Engineering Faculty Research & Creative Works

Recently, the utilization of Radio Frequency (RF) devices has increased exponentially over numerous vertical platforms. This rise has led to an abundance of Radio Frequency Interference (RFI) continues to plague RF systems today. The continued crowding of the RF spectrum makes RFI efficient and lightweight mitigation critical. Detecting and localizing the interfering signals is the foremost step for mitigating RFI concerns. Addressing these challenges, we propose a novel and lightweight approach, namely RaFID, to detect and locate the RFI by incorporating deep neural networks (DNNs) and statistical analysis via batch-wise mean aggregation and standard deviation (SD) calculations. RaFID investigates the …

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Lifelong Deep Learning-Based Control Of Robot Manipulators, Irfan Ganie, Jagannathan Sarangapani Jan 2023

Lifelong Deep Learning-Based Control Of Robot Manipulators, Irfan Ganie, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

This study proposes a lifelong deep learning control scheme for robotic manipulators with bounded disturbances. This scheme involves the use of an online tunable deep neural network (DNN) to approximate the unknown nonlinear dynamics of the robot. The control scheme is developed by using a singular value decomposition-based direct tracking error-driven approach, which is utilized to derive the weight update laws for the DNN. To avoid catastrophic forgetting in multi-task scenarios and to ensure lifelong learning (LL), a novel online LL scheme based on elastic weight consolidation is included in the DNN weight-tuning laws. Our results demonstrate that the resulting …

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Miniature Optical Fiber-Tip High-Temperature Sensors Modified By Femtosecond Laser, Chen Zhu, Jie Huang Jan 2023

Miniature Optical Fiber-Tip High-Temperature Sensors Modified By Femtosecond Laser, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Miniature optical fiber-tip Fabry-Perot interferometric sensors fabricated by femtosecond laser micromachining for eliminating the additional Fresnel reflection and avoiding complicated amplitude modulation in the reflection spectra are demonstrated.

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Worst-Case Electromagnetic Coupling To An Accelerometer Using An Equivalent Circuit And Experimental Co-Characterization Methodology, Mohamed Z.M. Hamdalla, Thomas Ory, Aaron Harmon, Daryl G. Beetner, Victor Khilkevich, John Mcgeehan, John Willits, Anthony N. Caruso, Ahmed M. Hassan Jan 2023

Worst-Case Electromagnetic Coupling To An Accelerometer Using An Equivalent Circuit And Experimental Co-Characterization Methodology, Mohamed Z.M. Hamdalla, Thomas Ory, Aaron Harmon, Daryl G. Beetner, Victor Khilkevich, John Mcgeehan, John Willits, Anthony N. Caruso, Ahmed M. Hassan

Electrical and Computer Engineering Faculty Research & Creative Works

Worst-Case Coupling Estimation to a Complex Printed Circuit Board (PCB) System Typically Requires an Expensive Computational And/or Experimental Approach. Therefore, there is a Strong Need for a Deterministic Approach that Can Accurately Predict the Worst-Case Coupling with the Least Computational and Experimental Cost. This Work Uses a Hybrid Equivalent Circuit Approach Coupled with Experimental Measurements to Simplify Predicting the Worst-Case Coupling to an Accelerometer Board. the Predictions of the Proposed Methodology Are Validated using Experimental Measurements with Excellent Agreement.

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Embedded Aperture-Based Fss Sensor, Lauryn Morris, Swathi Muthyala Ramesh, Logan M. Wilcox, Doyle T. Motes, Kristen M. Donnell Jan 2023

Embedded Aperture-Based Fss Sensor, Lauryn Morris, Swathi Muthyala Ramesh, Logan M. Wilcox, Doyle T. Motes, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency Selective Surfaces (FSSs) Are Two-Dimensional Periodic Arrays of Electrically Conductive Elements or Apertures that Have a Specific Electromagnetic Reflection And/or Transmission Response. in This Work, an Aperture-Based Sensor Design Was Proposed that is Capable of Sensing Strain When Embedded in a Layered Dielectric Structure (I.e., an Embedded Sensor). an Aperture Approach Was Selected Due to the Potential for Operation in Reflection Mode Without a Conductive Backplane. the Sensor Was Designed to Operate within the K-Band to Improve the Potential Strain Measurement Resolution, as the Unit Cell Dimensions Are Inversely Related to the Operating Frequency and Directly Related to Strain …

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Modified H-Plane Sectoral Horn For Fss Sensing Applications, Logan M. Wilcox, Doyle T. Motes, Kristen M. Donnell Jan 2023

Modified H-Plane Sectoral Horn For Fss Sensing Applications, Logan M. Wilcox, Doyle T. Motes, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

The Use of Frequency Selective Surfaces (FSSs) as Sensors Has Found Recent Success in the Structural Health Monitoring Realm. FSS Theory Assumes Infinite FSS Dimensions and Planewave Illumination. However, in Practice, an FSS Sensor is Finite, and the Illuminating Field Varies Across the Plane of the Sensor. as Such, it is of Interest to Reduce the Nonuniformity of the Incident Electromagnetic Energy Incident on the Sensor. to This End, This Work Explores the Modification of a Standard H-Plane Sectoral Horn through the Addition of a Ridge to Generate a Uniform Electric Field over a Specified Region of Interest. in Addition …

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Pcb Based Modulated Scatter With Enhanced Modulation Depth, Dylan A. Crocker, Kristen M. Donnell Jan 2023

Pcb Based Modulated Scatter With Enhanced Modulation Depth, Dylan A. Crocker, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

The Modulated Scatterer Technique (MST) Has Shown Promise for Applications in Microwave Imaging, Electric Field Mapping, and Materials Characterization. Traditionally, MST Scatterers Are Dipoles Centrally Loaded with an Element Capable of Modulation (E.g., a PIN Diode). by Modulating the Load Element State, the Scattered Fields Are Also Modulated. However, Due to the Small Size of Such Scatterers, It Can Be Difficult to Reliably Detect the Response. Increasing the Modulation Depth (MD) of the Scattered Signal May Improve Detectability. This Paper Presents Simulations and Measurements of PCB-Based MST Elements that, through Reactive Loading, Are Designed to Be Electrically Invisible during the …

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Enhancing Near-Field Wireless Localization With Lidar-Assisted Ris In Multipath Environments, Omar Rinch, Ahmed Elzanaty, Ahmad Alsharoa Jan 2023

Enhancing Near-Field Wireless Localization With Lidar-Assisted Ris In Multipath Environments, Omar Rinch, Ahmed Elzanaty, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

In Next-Generation Wireless Networks that Adopt Millimeter-Waves and Large RIS, the User is Expected to Be in the Near-Field Region, Where the Widely Adopted Far-Field Algorithms based on Far-Field Can Yield Low Positioning Accuracy. Also, the Localization of UE Becomes More Challenging in Multipath Environments. in This Paper, We Propose a Localization Algorithm for a UE in the Near-Field of a RIS in Multipath Environments. the Proposed Scheme Utilizes a LiDAR to Assist the UE Positioning by Providing Geometric Information About Some of the Scatterers in the Environment. This Information is Fed to a Sparse Recovery Algorithm to Improve the …

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Experimental Verification Of Characteristic Mode Analysis (Cma) Using Reverberation Chamber, Haran Manoharan, Xu Wang, Matthew Wu, Jagan Rajagopalan, Akshay Mohan, Chulsoon Hwang Jan 2023

Experimental Verification Of Characteristic Mode Analysis (Cma) Using Reverberation Chamber, Haran Manoharan, Xu Wang, Matthew Wu, Jagan Rajagopalan, Akshay Mohan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Work, a Novel Experimental Validation of Characteristic Mode Analysis (CMA) is Proposed using Reverberation Chamber Measurements. using the Modal Weighting Coefficient Formulation based on the Magnetic Moment and Modal H Field Obtained from Solvers, the Total Radiated Power (TRP) is Calculated. This TRP is Compared with the TRP Obtained from the Reverberation Chamber Measurements. a Good Correlation between the Simulation and Measurement Was Achieved for a Simple Rectangular Plate of Size 15 Cm X 8 Cm with an Error of Less Than 4 DB.

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Analysis Of Voltage Regulator Module (Vrm) Noise Coupling To High-Speed Signals With Vrm Via Designs, Junho Joo, Manish K. Mathew, Soumya Singh, Seema Pk, Arun Chada, Bhyrav Mutnury, Chulsoon Hwang, Donghyun Kim Jan 2023

Analysis Of Voltage Regulator Module (Vrm) Noise Coupling To High-Speed Signals With Vrm Via Designs, Junho Joo, Manish K. Mathew, Soumya Singh, Seema Pk, Arun Chada, Bhyrav Mutnury, Chulsoon Hwang, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

The Physical Noise Coupling Mechanism between Voltage Regulator Module (VRM) Noise Coupling to High-Speed Signal Traces is Analyzed and Different Noise Reduction Methods Are Analyzed for the First Time. the Rapid Switching of Field Effect Transistors (FETs) Creates an Unintentional Coupling Region Around the VRM. as High-Speed Traces Are Often Routed in the Inner Signal Layers of Printed Circuit Boards (PCBs) as Striplines for Signal Integrity, the VRM Switching Noise is Mainly Coupled from Noisy Power Vias to the Victim Traces Routed Around the VRM Region. to Analyze Different Coupling Reduction Methods in Practical High-Speed Channels, a Simplified PCB Design …

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Predicting Radiated Emissions From An Electrical Drive System, Giorgi Tsintsadze, Haran Manoharan, Daryl G. Beetner, Daniel Commerou, Brain Booth, Kerry Martin Jan 2023

Predicting Radiated Emissions From An Electrical Drive System, Giorgi Tsintsadze, Haran Manoharan, Daryl G. Beetner, Daniel Commerou, Brain Booth, Kerry Martin

Electrical and Computer Engineering Faculty Research & Creative Works

A Measurement-Based SPICE Model is Proposed to Predict Radiated Emissions from an Electrical Drive System over a Frequency Range from 20-300 MHz. the Model Combines a Model for the Radiated Emissions from the Cabling and Housings with a Model for Coupling Inside the Electrical Motor. the Electromagnetic Properties of the Cabling and Housings Were Captured with Measured S-Parameters. the Coupling Mechanisms Inside the Electrical Machine Were Represented using a Circuit- Element based Model. the Intent is to Provide Insight into How Coupling Mechanisms and Placement of Structures in the Motor Affect Radiated Emissions from the Drive System, and to Give …

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Application Of Tvs Models For Seed Simulation Of A Variety Of Tvs Devices, Li Shen, Yang Xu, Steffen Holland, Sergej Bub, David Pommerenke, Daryl G. Beetner Jan 2023

Application Of Tvs Models For Seed Simulation Of A Variety Of Tvs Devices, Li Shen, Yang Xu, Steffen Holland, Sergej Bub, David Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate Models of Transient Voltage Suppression (TVS) Devices Are Important for Determining the Suitability of Electrostatic Discharge (ESD) Protection Strategies Early in the Design Process. an Improved TVS Model is Used in the Following Paper to Represent a Variety of TVS Devices, Including a Snapback Device, Non-Snapback Device, and a Varistor. the Models Include Recent Improvements to Represent Conductivity Modulation and the overall Shape of the TVS Device's Transient Response. the Models Are Tuned based on Characterizations of These Protection Devices using a Transmission Line Pulse (TLP) and Are Then Used in a System Efficient ESD Design (SEED) Simulation to …

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