WiFi-CSI 差异范式

IF 3.6 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-05-13 DOI:10.1145/3659608
Wenwei Li, Ruiyang Gao, Jie Xiong, Jiarun Zhou, Leye Wang, Xingjian Mao, E. Yi, Daqing Zhang
{"title":"WiFi-CSI 差异范式","authors":"Wenwei Li, Ruiyang Gao, Jie Xiong, Jiarun Zhou, Leye Wang, Xingjian Mao, E. Yi, Daqing Zhang","doi":"10.1145/3659608","DOIUrl":null,"url":null,"abstract":"Passive tracking plays a fundamental role in numerous applications such as elderly care, security surveillance, and smart home. To utilize ubiquitous WiFi signals for passive tracking, the Doppler speed extracted from WiFi CSI (Channel State Information) is the key information. Despite the progress made, existing approaches still require a large number of samples to achieve accurate Doppler speed estimation. To enable WiFi sensing with minimum amount of interference on WiFi communication, accurate Doppler speed estimation with fewer CSI samples is crucial. To achieve this, we build a passive WiFi tracking system which employs a novel CSI difference paradigm instead of CSI for Doppler speed estimation. In this paper, we provide the first deep dive into the potential of CSI difference for fine-grained Doppler speed estimation. Theoretically, our new design allows us to estimate Doppler speed with just three samples. While conventional methods only adopt phase information for Doppler estimation, we creatively fuse both phase and amplitude information to improve Doppler estimation accuracy. Extensive experiments show that our solution outperforms the state-of-the-art approaches, achieving higher accuracy with fewer CSI samples. Based on this proposed WiFi-CSI difference paradigm, we build a prototype passive tracking system which can accurately track a person with a median error lower than 34 cm, achieving similar accuracy compared to the state-of-the-art systems, while significantly reducing the required number of samples to only 5%.","PeriodicalId":20553,"journal":{"name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"WiFi-CSI Difference Paradigm\",\"authors\":\"Wenwei Li, Ruiyang Gao, Jie Xiong, Jiarun Zhou, Leye Wang, Xingjian Mao, E. Yi, Daqing Zhang\",\"doi\":\"10.1145/3659608\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Passive tracking plays a fundamental role in numerous applications such as elderly care, security surveillance, and smart home. To utilize ubiquitous WiFi signals for passive tracking, the Doppler speed extracted from WiFi CSI (Channel State Information) is the key information. Despite the progress made, existing approaches still require a large number of samples to achieve accurate Doppler speed estimation. To enable WiFi sensing with minimum amount of interference on WiFi communication, accurate Doppler speed estimation with fewer CSI samples is crucial. To achieve this, we build a passive WiFi tracking system which employs a novel CSI difference paradigm instead of CSI for Doppler speed estimation. In this paper, we provide the first deep dive into the potential of CSI difference for fine-grained Doppler speed estimation. Theoretically, our new design allows us to estimate Doppler speed with just three samples. While conventional methods only adopt phase information for Doppler estimation, we creatively fuse both phase and amplitude information to improve Doppler estimation accuracy. Extensive experiments show that our solution outperforms the state-of-the-art approaches, achieving higher accuracy with fewer CSI samples. Based on this proposed WiFi-CSI difference paradigm, we build a prototype passive tracking system which can accurately track a person with a median error lower than 34 cm, achieving similar accuracy compared to the state-of-the-art systems, while significantly reducing the required number of samples to only 5%.\",\"PeriodicalId\":20553,\"journal\":{\"name\":\"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-05-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3659608\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3659608","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

被动跟踪在老年人护理、安全监控和智能家居等众多应用中发挥着重要作用。要利用无处不在的 WiFi 信号进行被动跟踪,从 WiFi CSI(信道状态信息)中提取的多普勒速度是关键信息。尽管取得了进展,但现有方法仍需要大量样本才能实现准确的多普勒速度估计。为了在WiFi通信受到最小干扰的情况下实现WiFi传感,使用较少的CSI样本进行精确的多普勒速度估计至关重要。为此,我们建立了一个无源 WiFi 跟踪系统,该系统采用了一种新颖的 CSI 差分范例来代替 CSI 进行多普勒速度估计。在本文中,我们首次深入探讨了 CSI 差分在细粒度多普勒速度估计方面的潜力。从理论上讲,我们的新设计只需三个样本就能估计多普勒速度。传统方法仅采用相位信息进行多普勒估计,而我们创造性地融合了相位和振幅信息,从而提高了多普勒估计的准确性。广泛的实验表明,我们的解决方案优于最先进的方法,以更少的 CSI 样本实现了更高的精度。基于所提出的 WiFi-CSI 差分范例,我们构建了一个原型无源跟踪系统,该系统可以精确跟踪一个人,中位误差低于 34 厘米,与最先进的系统相比达到了类似的精确度,同时将所需的样本数量大幅减少到仅 5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
WiFi-CSI Difference Paradigm
Passive tracking plays a fundamental role in numerous applications such as elderly care, security surveillance, and smart home. To utilize ubiquitous WiFi signals for passive tracking, the Doppler speed extracted from WiFi CSI (Channel State Information) is the key information. Despite the progress made, existing approaches still require a large number of samples to achieve accurate Doppler speed estimation. To enable WiFi sensing with minimum amount of interference on WiFi communication, accurate Doppler speed estimation with fewer CSI samples is crucial. To achieve this, we build a passive WiFi tracking system which employs a novel CSI difference paradigm instead of CSI for Doppler speed estimation. In this paper, we provide the first deep dive into the potential of CSI difference for fine-grained Doppler speed estimation. Theoretically, our new design allows us to estimate Doppler speed with just three samples. While conventional methods only adopt phase information for Doppler estimation, we creatively fuse both phase and amplitude information to improve Doppler estimation accuracy. Extensive experiments show that our solution outperforms the state-of-the-art approaches, achieving higher accuracy with fewer CSI samples. Based on this proposed WiFi-CSI difference paradigm, we build a prototype passive tracking system which can accurately track a person with a median error lower than 34 cm, achieving similar accuracy compared to the state-of-the-art systems, while significantly reducing the required number of samples to only 5%.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Computer Science-Computer Networks and Communications
CiteScore
9.10
自引率
0.00%
发文量
154
期刊最新文献
Talk2Care: An LLM-based Voice Assistant for Communication between Healthcare Providers and Older Adults A Digital Companion Architecture for Ambient Intelligence Waving Hand as Infrared Source for Ubiquitous Gas Sensing PPG-Hear: A Practical Eavesdropping Attack with Photoplethysmography Sensors User-directed Assembly Code Transformations Enabling Efficient Batteryless Arduino Applications
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1