IRS-enabled Breath Tracking with Colocated Commodity WiFi Transceivers

Intelligent reflecting surfaces (IRS) are a key enabler of various new applications in 6G smart radio environments. This paper aims to enhance self-interference (SI) cancellation for breath tracking with commodity WiFi devices by utilizing an IRS prototype system. SI suppression is a crucial require...

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Bibliographic Details
Published in:IEEE internet of things journal 2023-04, Vol.10 (8), p.1-1
Main Authors: Tewes, Simon, Heinrichs, Markus, Kronberger, Rainer, Sezgin, Aydin
Format: Article
Language:English
Subjects:
Breath Tracking
Cancellation
Channel State Information (CSI)
Commodities
Hardware
IEEE 802.11
Indoor environments
Intelligent Reflecting Surface (IRS)
Internet of Things
Joint Communication and Sensing
Prototypes
Radar tracking
Radio
Receiving antennas
Reconfigurable Intelligent Surface (RIS)
Sensors
Synchronism
Tracking devices
Transmitting antennas
WiFi
Wireless fidelity
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Summary:Intelligent reflecting surfaces (IRS) are a key enabler of various new applications in 6G smart radio environments. This paper aims to enhance self-interference (SI) cancellation for breath tracking with commodity WiFi devices by utilizing an IRS prototype system. SI suppression is a crucial requirement for breath tracking with a single antenna site, as the SI severely limits the radio sensing range by shadowing the received signal with its own transmit signal. To this end, we propose to assist SI cancellation by exploiting an IRS to form a suitable cancellation signal in the analog domain. Building upon a 256-element IRS prototype, we present results of breath tracking with IRS-assisted SI cancellation from a practical testbed. We use inexpensive WiFi hardware to extract the channel state information (CSI) in the 5 GHz band and analyze the phase change between a colocated transmitter and receiver with added local oscillator (LO) synchronization. As a result, we can track the breath of a test subject regardless of position in an indoor environment with a room-level range. The presented case study achieves promising performance in capturing the breath frequency and breathing patterns.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2022.3228158