Data Harvesting from Hard-to-Reach IoT Deployments: Aerial Data Collection Approach Sun, Jan 23 2022 Research Problem Statement The growing adoption of the Internet of Things (IoT) across diverse industries faces critical challenges in energy sustainability and operational efficiency. IoT devices, which are predominantly battery-powered, experience significant energy consumption due to continuous communication and sensing operations. This results in frequent battery replacements, which are impractical for large-scale deployments, especially in hard-to-reach areas. Additionally, current data collection methods, such as terrestrial LoRaWAN networks, are limited in scalability, cost-efficiency, and
GNSS Attitude Determination and Precise Positioning Sat, May 1 2021 Research Global Navigation Satellite Systems (GNSS), including GPS, GLONASS, Galileo or BeiDou, are used in many applications, most notably tracking the position and attitude (or orientation) of a vehicle or any moving platform. The advances in automated driving systems have recently reignited interest in GNSS positioning and attitude determination. The goal of this research project is to develop accurate real-time techniques for GNSS positioning and attitude determination. Our current and future research in this area focuses on three main areas 1) Attitude Determination; 2) Precise real-time
Massive MIMO and Terahertz Communications Tue, May 1 2018 Research THz-Band Ultra-Massive MIMO System and Channel Modeling To advance signal processing for THz communications research [1, 2], we developed TeraMIMO , an accurate, open-source MATLAB simulator for stochastic wideband ultra-massive multiple-input multiple-output (UM-MIMO) THz channels. TeraMIMO models critical THz channel statistics, including coherence time, coherence bandwidth, Doppler spread, and root-mean-square (RMS) delay spread. It captures frequency-selective and time-variant THz channels across various communication distances, ranging from nano-communications to short-range indoor
