432 ISEC

PhD Proposal Review: Coupling Methods for Wireless Intra-body Communication and Sensing Stella Banou Location: 432 ISEC Abstract: Advances in miniaturized bio-compatible Internet of Things (IoT) device design and wireless connectivity have resulted in rapid strides towards realizing the vision of connected health and ubiquitous monitoring of physiological conditions. Core enablers of this capability are wearable and implanted IoT devices, albeit with limitations arising from their low energy storage and computational power. This thesis goes beyond the RF-only communication standards by…

PhD Proposal Review: RF Channel Models for Static and Mobile Scenarios: From Simulations to Models for Large-scale Emulations Miead Tehrani-Moayyed Location: ISEC 432 Abstract: The extremely high data rates provided by communications at higher frequency bands, e.g., millimeter waves (mmWave), can help address the unprecedented demands of next-generation wireless networks. However, as several impairments limit wireless coverage at higher frequencies, accurate models of wireless scenarios and testing at scale are needed to show actual potential and to realize the promises…

"High Efficiency RF Energy Harvesting and Power Management Circuits Techniques for IoT Application" Abstract: As the number of Internet of Things (IoT) devices is continuing to grow, there is a need that a significant percentage these devices operate at ultra-low power (ULP) levels, either using harvested energy or using a small battery with a long lifetime. Energy harvesting techniques can help to achieve long lifetimes, but the system should be able to operate efficiently with a small amount of harvested…

"Softwarized Approaches for the Open RAN of NextG Cellular Networks" Abstract: The 5th and 6th generations of cellular networks (5G and 6G), also known as NextG, will bring unprecedented flexibility to the wireless cellular ecosystem. Because of a typically closed and rigid market, the telco industry has incurred high costs and non-trivial obstacles for delivering new services and functionalities that satisfy the requirements and the demands of NextG networks. To break this trend the industry is now moving toward open…

"Ultra-Low Power and Robust Analog Computing Circuits and System Design Framework for Machine Learning Applications" Abstract: As the scaling of CMOS transistors has almost halted, performance gains of digital systems have also started to stagnate. There is a renewed interest in alternate computing techniques such as in-memory computing, hybrid computing, approximate computing, and analog computing. In particular, analog computing has reemerged as a promising alternative to save power and improve performance specifically for machine-learning (ML) applications. Power and chip area…

"Multiple UAVs for Synchronous - Shared Tasks and Long-term Autonomy" Abstract: This thesis focuses on the use of multiple unmanned aerial vehicles(UAVs) in a distributed framework from a systems perspective to synchronously perform shared tasks such as aerial beamforming and coordinated mapping and to enhance the reliability of performing periodic (mapping) tasks at remote locations for long-term autonomous(LTA) missions. We present an autonomy stack for multiple, heterogeneous UAVs with a simulation framework. We implemented the end-to-end pipelines for perception and…

"Multiphysics Simulation of Graphene Transistors for On-Chip Plasmonic THz Signal Generation and Modulation" Abstract: Terahertz communication is envisioned as a key technology not only for the next generation of macro-scale networks (e.g., 6G+), but also for transformative networking applications at the nanoscale (e.g., wireless nanosensor networks and wireless networks on chip). This proposal focuses on the development of a multiphysics simulation platform for a plasmonic THz nanogenerator with on-chip modulation. The in-house developed finite-element-method platform, which self-consistently solves the hydrodynamic…

"RF Front-End Components based on Linear-Time-Variant Modulation of Piezoelectric MEMS Resonators" Abstract: Throughout the last decade, radio frequency (RF) components for over-the-air communication and sensing have been subject to sustained market pressure to adapt to the novel trends such as spectrum sharing, programmability, and low-power operation. When these features are required in chip-scale RF hardware, innovative solutions are necessary as conventional materials and techniques become bottlenecks for next-generation radios. In this work, we explore advanced wave manipulation circuital techniques such…

"Ferroelectric Micro-machined Ultrasonic Transducers for Biomedical and Processing In-Sensor Applications" Abstract: Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) are Micro Electro-Mechanical Systems (MEMS) devices that have become an established technology in applications such as range-finding, fingerprint sensing and imaging due to their capability of ultrasonic transduction in a miniaturized footprint, easily amenable to create large arrays. However, their application space still remains quite open. PMUTs are well fitted to applications in liquid media, such as implantable and underwater devices, due to their…

"Terahertz Communication for Space Systems" Abstract: With the ultimate vision of ubiquitous egalitarian worldwide coverage driven by the rapid proliferation of high-speed satellite networks, private companies are launching satellites into orbit at unprecedented rates. The main goal of such networks enabled by dense constellations in space is to build a more robust telecommunications infrastructure and provide worldwide internet access to users on Earth. Similarly, small satellites are included in the vision of non-terrestrial networks (NTN) for 6G networks which promise…

"Channel-and-Adversary-Resilient Radio Fingerprinting through Data-Driven Approaches at Scale" Committee: Prof. Tommaso Melodia (Advisor) Prof. Kaushik Chowdhury Prof. Francesco Restuccia Abstract: Radio fingerprinting authenticates wireless devices by leveraging tiny hardware-level imperfections inevitably present in the radio circuitry. This way, devices can be directly identified at the physical layer– thus avoiding energy-expensive upper-layer cryptography that resource-limited embedded devices may not be able to afford. Recent advances have proven that employing deep learning algorithms can achieve fingerprinting accuracy levels that were impossible to…

"Parametric Circuits for Enhanced Sensing and RF Signal Processing" Committee Members: Prof. Cristian Cassella (Advisor) Prof. Marvin Onabajo Prof. Matteo Rinaldi Prof. Andrea Alù Abstract: Massive deployments of wireless sensor nodes (WSNs) that continuously detect physical, biological or chemical parameters are needed to truly benefit from the unprecedented possibilities opened by the Internet‑of‑Things (IoT). Just recently, new sensors with higher sensitivities have been demonstrated by leveraging advanced on‑chip designs and microfabrication processes. Yet, WSNs using such sensors require energy to…

Title: Real-Time Spectrum Sensing for Inference and Control Committee Members: Prof. Tommaso Melodia (Advisor) Prof. Kaushik Choudhury Prof. Francesco Restuccia Abstract: Through growing cellular innovations, the usage and congestion of the wireless spectrum is increasing at incredible speeds. High demand and limited supply pose a resource issue known as the "spectrum crunch". With the high diversity of users sharing a large portion of the spectrum to request and receive diverse services, spectrum coordination becomes very difficult. Large scale device synchronization…