AWaRE REU – ND Wireless Institute
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Mesh Assisted Devices for Real-Time Asset Tracking (MADRAT)

Principal Investigator:

Dr. Billo, Associate Vice President for Research; Professor of Computer Science and Engineering. This project also involves Dr. Hochwald, of the Electrical Engineering Department.

Project Summary:

While the advancement of technologies such as GPS and location data based on cell coverage have improved the capabilities of tracking shipments in recent decades, a gap in coverage particularly while cargo is on the ocean still remains due to the cost and technical hurdles.  Tracking the shipments of cargo in real-time has historically been cost-prohibitive and reserved for big-ticket items only.  Additionally, the placement of a container inside of an ocean-going vessel typically obscures a direct line of sight to satellites and as a result, the container is tracked via the vessel.  In the event that a container is lost or damaged, it is unknown to the owner of the cargo until the ship arrives at its destination.  The ability to provide container-specific data through a system independent of GPS and cellular service offers a solution to these problems and provides cargo owners, insurers, and carriers a level of transparency and the ability to know location and cargo-specific data in real-time.

The proposed MADRAT product can be utilized to track the location, temperature, humidity, and acceleration of shipping containers and their cargo in real-time. MADRAT utilizes long-range, low power wireless communications technology (LoRa), RFID, and a self-healing mesh network protocol to operate independently of cellular networks. In this project, students will work alongside Drs. Hochwald and Billo to design the hardware, network, and software architectures of a system that will ultimately have the capability to track items in real-time anyplace in the world.

Student’s Role:

The REU participant’s skills need to include completed coursework in programming, database design, network communications and/or wireless communications. Previous lab experience a plus.

Collaborative Intelligent Radio Systems for Congested Wireless Environments

Principal Investigator:

Dr. Laneman, Department of Electrical Engineering

Project Summary:

The Citizens Broadband Radio Service (CBRS), currently targeting a radio frequency (RF) band centered around 3.5 GHz, represents a breakthrough in wireless technology and policy in the United States. For the first time, widespread commercial cellular networks based upon LTE technology will intelligently utilize RF spectrum that has otherwise been exclusively reserved for government systems like Navy radars. As RF spectrum becomes more crowded, and sharing spectrum among very different commercial and government systems becomes the norm, wireless system engineers need to build radios and network services that are much more context-aware and collaborative compared to current designs, basically redesigning such systems from the ground up to be more resilient to interference in congested environments.

To address problems in this space, our team has been developing prototypes, models, and algorithms for what is being called a collaborative intelligent radio system (CIRS). A CIRS needs to be able to sense what is going on in the RF spectrum in and around its intended band of operation, and then adaptive its transmission formats and receiver signal processing algorithms accordingly. Our radio prototypes are based upon software-defined radio (SDR), with which our team has extensive experience. Student projects involve learning how to use and develop for the prototyping platform, designing and implementing a set of new features, and testing and demonstrating those features to the group.

Student’s Role:

The REU student will work with graduate students, a software engineer, and the faculty advisor to develop and test new radio models and signal processing algorithms for CIRS. Opportunities to develop courseware and participate in the DARPA Spectrum Collaboration Challenge will also be available during the Summer and beyond.

Wireless Microimplants for Deep Tissue Disease Monitoring and Treatment

Principal Investigator:

Dr. O’Sullivan, Department of Electrical Engineering

Project Summary:

Despite the explosive growth in the development of wearable and implantable sensors for monitoring health and personal wellness, there are currently no viable sensor technologies that can sense targets deep within the human body. Current sensors are limited to sensing cutaneous or shallow subcutaneous tissue volumes, have limited functionality, or are simply too large and obtrusive. This prevents their use in some of the most impactful areas of medicine including monitoring solid tumors, simultaneous deep brain sensing and stimulation, and monitoring diseases of the internal organs. The long-term goal of this project is to develop an extensible microimplant platform that can ultimately be placed anywhere in the human body and provide sensitivity to multiple biomolecular targets continuously and in real-time. This project entails sensor design, modeling (mechanical and functional), and prototyping of wireless microimplants using advanced manufacturing processes.

Student’s Role:

The REU student will work with graduate students and the faculty advisor to test and optimize wireless microimplant prototypes in both benchtop and in vivo small animal model experiments. The student will also be expected to develop testing protocols which may include setting up data acquisition systems and developing software, and provide comprehensive analysis of the collected data. Although students of all levels will be considered, candidates should be studying electrical, mechanical, or biomedical engineering.

Bringing 5G Smarts to Network Measurement

Principal Investigator:

Dr. Striegel, Department of Computer Science and Engineering

Project Summary:

Traditionally, most network measurement tools such as Speedtest.net and others measure the network in an isolated manner. Further, while peak speed can be interesting, it often fails to capture all of the dynamics of modern wireless networks. The focus of this project is to study the interplay of how sharing various pieces of network information between apps and wireless devices can lead to improved network understanding and performance.

Student’s Role:

Create Linux or mobile app library that can interwork with our suite of Fast Mobile Network approaches and study the interplay/trade-offs with respect to WiFi and cellular network measurement accuracy versus energy consumption.

Networked Robots: Coordination and Control

Principal Investigator:

Dr. Lin, Department of Electrical Engineering

Project Summary:

This REU project aims to develop a team of robotic systems that can accomplish complex team missions even in the face of uncertain and dynamic environments. Applications that motivate this project include, but not limited to, emergency response, future manufacturing systems, and service robots. In this REU project, we will touch topics on both hardware/software development and theoretical/algorithm design, such as communication-aware coordinated motion planning, sensing, task planning through formal methods, a counterexample-guided synthesis which combines logic inference with optimization.

Student’s Role:

Develop algorithms to synthesize robust trajectories, and to adapt the trajectories during run-time to deal with unknown obstacles or other agents in the environment. Implement these algorithms in real robotic platforms, such as Pioneer 3AT/3DX and Baxter. Background/interest in optimization, embedded systems, control, algorithms, real-time programming. Preferred skills in MATLAB, C/C++, and Linux.

Machine Learning for RF Information Leakage Characterization in Low Cost Bluetooth Implementation

Principal Investigator:

Dr. Joshi, Department of Computer Science and Engineering

Project Summary:

Due to tight on-die integration in low-cost, low-power wireless modules, digital and mixed-signal subsystems are often placed very close to each other. Noise coupling from the digital system is often indicative of the computations being performed and thus leaks information to the outside world. We would like to characterize this leakage and see what can we infer about the computations occurring inside the chip using only the signals leaking outside.

Student’s Role:

The student will be conducting in-lab experiments with commercial bluetooth development boards, the student will be working with software-defined radio kits to record this information. The student will then learn how to use modern machine learning tools to automate the process of information extraction and capture.

High-Frequency Characterization and Modeling of GaN Transistors

Principal Investigator:

Dr. Fay, Department of Electrical Engineering

Project Summary:

GaN-based transistors are increasingly attractive for applications across the microwave and millimeter-wave frequency range, including power amplifiers, low-noise amplifiers, switches for reconfigurable RF systems, and more. This project includes measuring the performance of several GaN transistor designs (including DC measurement, low-frequency AC, and high-frequency on-wafer characterization) and developing models suitable for computer-aided circuit design of these transistors from the measured characteristics. Comparisons of different models (e.g. ASM-HEMT, Angelov, etc.) and their respective abilities to capture key device performance features are included to evaluate the suitability of the models for different circuit applications.

Student’s Role:

The student will also be instrumental in using the collected data to extract the model parameters for the selected transistor model, and comparing the model’s projected performance against the measured results. Preparing a design kit, including documenting the model’s strengths and weaknesses, is also included.

Phased Arrays and Lenses for Low-Power 5G MMW Communications

Principal Investigator:

Dr. Chisum, Department of Electrical Engineering

Project Summary:

Phased arrays have proven to be an enabler for high-performance communications and sensing in the sub-6 GHz bands. They enable high-gain links to individual remote radios which can be tracked in space to achieve high data rates, enable spatial reuse, and even provide location-aware applications. This technology was initially developed in the defense sector at great cost and with significant power consumption. However, commercial-off-the-shelf (COTS) DACs and ADCs have seen a dramatic reduction in cost and power consumption and a wide range of integrated RF components in the sub-6 GHz bands have become available. These trends have enabled the technology to transition to the commercial sector with great success.

More recently the same technology was transitioned to the millimeter-wave (MMW) bands (>30 GHz) to enable 5G MMW communications with data rates beyond 1 Gbps. Unfortunately, the technology (data converters and radio components) did not scale well so the 5G MMW phased arrays consume extremely high power. In fact, the first generation of 5G MMW-enabled mobile phones were only capable of operating at Gbps rates for ~10 minutes before the battery was drained.

Instead of taking technologies that worked well at low-frequencies and moving them up in frequency, an alternative approach is to take technologies which natively work at high frequencies such as lens antennas, and modify them to provide the desired functionality (high-speed beam-scanning and multi-beam apertures) for 5G MMW.

The purpose of this research project is to explore the length to which switch-beam lens antennas can provide the most important features and capabilities of a phased array but at a fraction of the cost and power. This project will build off of the MMW lens antenna demonstrations from the PIs research group and will include theoretical electromagnetic antenna modeling as well as linear systems analysis (especially beam-forming theory and beam-synthesis methods from field theory). In addition, the student will use the PI’s measurement laboratory and near-field antenna range to demonstrate phased-array-fed lens antennas using state-of-the-art beamformer integrated circuits.

Student’s Role:

The student will perform measurement and simulation of both phased array systems and lens antenna systems. They will take advantage of the Matlab simulation models developed by the PI’s group as well as the PI’s measurement laboratory and near-field antenna range. This will be done with guidance from graduate students and the PI. Then they will develop models of each.

By the end of the summer, the student will have applied electromagnetic theory and systems analysis to the question of low-power millimeter-wave beam-scanning antennas. The outcome of the work will be an assessment of how well lens antenna systems can accomplish the same thing as phased arrays at a fraction of the power and cost.

 

RadioHound: A Low-Cost Spectrum Sensor

Principal Investigator:

Dr. Hochwald, Department of Electrical Engineering. This project also involves Drs. Laneman and Chisum, of the Department of Electrical Engineering, and Dr. Striegel from the Department of Computer Science and Engineering.

Project Summary:

RadioHound, an ongoing project at NDWI, is the development of low-cost, portable spectrum measurement sensors capable of tuning over a wide range of frequencies commonly used by everything from cellular phones to wireless local area networks, to radios and televisions. One goal is to distribute these sensors over a wide geographical area and thereby crowd-source the real-time measurements to create a “heat-map” of spectrum usage over the area and across frequency. Such a map would be used, for example, to determine where spectrum congestion is dense. We are on our third version of the sensor.

We are in the fifth year of this project.

Student’s Role:

The project has many hardware and software components and opportunities for students to contribute, depending on their technical software and hardware maturities and skillsets. Basic hardware and laboratory capabilities, and knowledge of C, Python, and networking are a plus, but not required. In particular, we have an opening for help with Version 3 of the board, including laboratory measurements, and experimental verification of spectrum heat-maps. Hence, knowledge of laboratory equipment and practices is advantageous.

Radar Signal Processing and Data Analysis

Project Summary:

Notre Dame is involved in the development and implementation of target detection and identification concepts for radar applications. Evaluation of these concepts will be assessed experimentally using software-defined radar platforms. The research for the undergraduate student is expected to involve participation in experiments to evaluate one or more radar concepts, depending on project needs. The student will have opportunities to contribute to various facets of the research, including field tests, data analyses, and documentation.

Student’s Role:

Research opportunities for the undergraduate student will involve one or more topics associated with radar, including advanced radar architectures, distributed radar systems, and novel target characterizations. The undergraduate students will participate in radar literature surveys, radar subsystem implementations (in Matlab), field experimentation, and data analysis. The student is expected to provide research products in the form of slides and weekly status reports. The undergraduate students will work on a team 4 of researchers that includes the PI, research engineers, and graduate students. The student will gain exposure to radar concepts as well as to state-of-the-art equipment, including a software-defined radios, a custom $700K multi-antenna transceiver system, and two 9-ton field research vehicles that are used in experimentation.

High Linearity GaN Transistors for Enhanced LNA Dynamic Range

Project Summary:

Novel transistor designs for improved linearity in GaN-based FETs are being explored for their potential to improve dynamic range in mm-wave low noise amplifiers (LNAs). This project includes device design, modeling, fabrication, and characterization of devices, as well as design of low-noise amplifiers (based on the extracted models) and comparison with designs based on conventional transistors in order to fully understand the potential benefits and any associated design trade-offs for mm-wave receiver applications.

 

Student’s Role:

Student involvement in this project can take several forms; focus on one particular aspect (e.g. device design, characterization, LNA design) is anticipated. For example, for device design work student would perform physics-based TCAD simulations of candidate designs, and optimize the device structure for best input IP3 and gain performance. For characterization, fabricated devices will be characterized on-wafer using nonlinear vector network analysis and on-wafer noise-parameter measurements in order to experimentally characterize the nonlinearities as well as noise figure and noise parameters. LNA design will include design of mm-wave LNA blocks (e.g. single-stage amplifier with reactive matching) to form the basis of comparative studies between new and conventional device designs.

Environmental Sensing using Passive WiFi Properties

Principal Investigator:

Dr. Striegel, Department of Computer Science and Engineering

Project Summary:

Beyond serving as an essential part of connectivity for our various smart devices, WiFi also can be helpful in providing environmental context such as the likely presence of people using devices, the density of devices being used, and changes in the nearby environment. The focus of this project is to explore the extent to which vehicle-mounted WiFi sensing could help better discern important environmental cues that are of interest to researchers and government entities.

Student’s Role:

The REU student will help gather data, process, analyze, and visualize data from our WiFi gathering tools and help design a next-generation sensing platform.