Enabling WiFi Sensing on New-generation WiFi Cards

Author:

Yi Enze1ORCID,Zhang Fusang2ORCID,Xiong Jie3ORCID,Niu Kai4ORCID,Yao Zhiyun1ORCID,Zhang Daqing5ORCID

Affiliation:

1. Key Laboratory of High Confidence Software Technologies (Ministry of Education), School of Computer Science, Peking University, Beijing, China

2. Institute of Software, Chinese Academy of Sciences, Beijing, China and University of Chinese Academy of Sciences, Beijing, China

3. University of Massachusetts Amherst, Massachusetts, USA

4. Beijing Xiaomi Mobile Software Company Ltd., Beijing, China

5. Key Laboratory of High Confidence Software Technologies (Ministry of Education), School of Computer Science, Peking University, Beijing, China, Telecom SudParis and Institut Polytechnique de Paris, Evry, France

Abstract

The last few years have witnessed the rapid development of WiFi sensing with a large spectrum of applications enabled. However, existing works mainly leverage the obsolete 802.11n WiFi cards (i.e., Intel 5300 and Atheros AR9k series cards) for sensing. On the other hand, the mainstream WiFi protocols currently in use are 802.11ac/ax and commodity WiFi products on the market are equipped with new-generation WiFi chips such as Broadcom BCM43794 and Qualcomm QCN5054. After conducting some benchmark experiments, we find that WiFi sensing has problems working on these new cards. The new communication features (e.g., MU-MIMO) designed to facilitate data transmissions negatively impact WiFi sensing. Conventional CSI base signals such as CSI amplitude and/or CSI phase difference between antennas which worked well on Intel 5300 802.11n WiFi card may fail on new cards. In this paper, we propose delicate signal processing schemes to make wireless sensing work well on these new WiFi cards. We employ two typical sensing applications, i.e., human respiration monitoring and human trajectory tracking to demonstrate the effectiveness of the proposed schemes. We believe it is critical to ensure WiFi sensing compatible with the latest WiFi protocols and this work moves one important step towards real-life adoption of WiFi sensing.

Funder

Beijing Natural Science Foundation

Youth Innovation Promotion Association, Chinese Academy of Sciences

NSFC A3 Project

PKU-NTU Collaboration Project

Beijing Nova Program

National Natural Science Foundation of China

Publisher

Association for Computing Machinery (ACM)

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