SA-WiSense: A Blind-Spot-Free Respiration Sensing Framework for Single-Antenna Wi-Fi Devices
Guangteng Liu, Xiayue Liu, Zhixiang Xu, Yufeng Yuan, Hui Zhao, Yuxuan Liu, Yufei Jiang

TL;DR
SA-WiSense introduces a cost-effective single-antenna Wi-Fi framework that effectively mitigates blind spots caused by phase offsets, enabling accurate contactless respiration monitoring up to 8 meters.
Contribution
The paper presents a novel CSCR-based blind spot mitigation and GA-based subcarrier selection method for single-antenna Wi-Fi respiration sensing, improving accuracy and robustness.
Findings
Achieves 91.2% detection rate for respiration at 8 meters
Effectively cancels random phase offsets in CSI signals
Outperforms existing single-antenna respiration sensing methods
Abstract
Wi-Fi sensing offers a promising technique for contactless human respiration monitoring. A key challenge, however, is the blind spot problem caused by random phase offsets that corrupt the complementarity of respiratory signals. To address the challenge, we propose a single-antenna-Wi-Fi-sensing (SA-WiSense) framework to improve accuracy of human respiration monitoring, robust against random phase offsets. The proposed SA-WiSense framework is cost-efficient, as only a single antenna is used rather than multiple antennas as in the previous works. Therefore, the proposed framework is applicable to Internet of Thing (IoT), where most of sensors are equipped with a single antenna. On one hand, we propose a cross-subcarrier channel state information (CSI) ratio (CSCR) based blind spot mitigation approach for IoT, where the ratios of two values of CSI between subcarriers are leveraged to…
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Taxonomy
TopicsWireless Networks and Protocols · Bluetooth and Wireless Communication Technologies · Wireless Body Area Networks
