Radio Frequency Systems and Signal Processing for Indoor Sensing in IoT and Emerging Applications

Abstract

The Internet of Things (IoT) envisions technologies featuring radio frequency signals and systems as one of the most important media for both communications and sensing. This talk will focus on the design and implementation of RF systems and signal processing techniques for indoor sensing tasks, focusing on IoT applications with coverage on other emerging applications like joint communications and sensing (JCAS). As localization of RF markers is a critical technology in IoT, we will discuss an ultra-narrowband high-precision phased-based localization framework that leverages spatial diversity of transmitter and receiver antenna locations as measuring points to achieve millimeter-precision 3D localization, implemented by Universal Software Radio Peripheral (USRP) and harmonic radio-frequency identification (RFID) at 1 GHz. In addition, vast deployment of RFID tags enable device-free object detection, locating and people counting using conventional inverse methods and deep learning models. IoT sensing will become a service for next-generation communication networks, for which we briefly introduce our ongoing investigations on OFDM-based JCAS using mmWave systems. The talk will conclude with discussions and outlooks on mmWave JCAS and biomedical sensing applications.

Biography

Guoyi Xu, postdoctoral research scientist in the Department of Electrical Engineering at Columbia University, received a bachelor of engineering degree in electrical engineering from the University of Electronic Science and Technology of China in 2018 and a PhD degree in electrical and computer engineering from Cornell University in 2023, advised by Professor Edwin Kan. He works with Professor Harish Krishnaswamy at Columbia University.