Radio Digital Twins for Wireless Sensing - Location Tracking and mmWave Imaging
Abstract:
Despite the tremendous advances in data-driven solutions for both wireless communication (e.g. beamforming, decoding, channel estimation) and sensing (e.g. location tracking, radar imaging), these benefits have remained out of reach for the average consumer. The primary bottleneck in adoption of these solutions in real-world deployments is their generalizability.The heterogeneous nature of devices deployed as well as the varying impact of the different physical environments on wireless propagation makes it almost impossible to develop a one-shot data-driven wireless solution.
In this talk, we present a vision for democratizing development of practical data-driven solutions for wireless sensing using enhanced Radio Digital Twins. Specifically, we will present solutions for off-the-shelf wireless devices to track themselves outdoors and develop hand-held mmWave imaging autofocus relying purely on synthetically generated wireless data from Radio Digital Twins. Finally, we will present a long-term vision for extending this initial vision towards long-term wireless foundation models.
Bio:
Akshay Gadre is an Assistant Professor at the Electrical and Computer Engineering department of University of Washington. His Networking and Emerging Wireless Technologies (NEWT) lab explores the upcoming application domains such as satellite IoT, mmWave imaging and underwater devices, to apply wireless expertise for improving communication and sensing capability of these devices while preserving the security and privacy of sensor data. He has published at premier cyber-physical systems and mobile systems venues like IPSN, NSDI, MobiCom, and ICC and his work has received the Best Paper Awards at ACM IPSN 2018 and IPSN 2020. His lab was awarded the Most Engaging Presentation Award at T-Challenge 2024 - AI for Telecommunication, ahead of leading telecom start-ups and companies. He was also awarded the ACM SIGBED-SIGSOFT Frank Anger Memorial Award 2021 for his cross-disciplinary research across embedded systems and software engineering. He received his Ph.D in ECE at Carnegie Mellon University and his B.Tech (Honors) + M.Tech degree in CSE from IIT Madras.