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Zero-Power Backscatter RFID for Healthcare Sensing and Robust Communication

Zhang, Y; Shi, X; Xu, T; (2025) Zero-Power Backscatter RFID for Healthcare Sensing and Robust Communication. In: Proceedings of ICC 2025 - IEEE International Conference on Communications. (pp. pp. 4439-4444). IEEE: Montréal, Canada. Green open access

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Abstract

In this paper, we propose a radio frequency identification (RFID)-based integrated sensing and communication (ISAC) system that uses the variations in received signal strength (RSS) from a passive tag grid for both robust communication and healthcare monitoring. Our approach utilizes the same RSS fluctuations for dual purposes: human activity triggered key generation and fall detection. Specifically, we conducted a hardware experiment to collect real-time RSS data from the tag grid and proposed a dynamic threshold adjustment-based physical layer key generation algorithm that guarantees robust and secure communication activated by human motion. For the healthcare sensing, we developed a non-wearable-based fall detection system by detecting the sudden RSS variations. We also generated heatmaps to visualize real-time alerts and fall location. By unifying these two functions, our system not only demonstrates the practicality and efficiency of using RFID as an ISAC platform, but also overcomes the traditional trade-off between communication and sensing.

Type: Proceedings paper
Title: Zero-Power Backscatter RFID for Healthcare Sensing and Robust Communication
Event: ICC 2025 - IEEE International Conference on Communications
Dates: 8 Jun 2025 - 12 Jun 2025
ISBN-13: 979-8-3315-0521-9
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/ICC52391.2025.11161960
Publisher version: https://doi.org/10.1109/icc52391.2025.11161960
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: RFID, ISAC, zero-power, backscatter, physical layer key generation, fall detection
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10218273
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