Tao Deng , Bowen Zheng , Rui Du , Fan Liu , Tony Xiao Han
{"title":"A statistical sensing method by utilizing Wi-Fi CSI subcarriers: Empirical study and performance enhancement","authors":"Tao Deng , Bowen Zheng , Rui Du , Fan Liu , Tony Xiao Han","doi":"10.1016/j.jiixd.2024.05.002","DOIUrl":null,"url":null,"abstract":"<div><p>In modern Wi-Fi systems, channel state information (CSI) serves as a foundational support for various sensing applications. Currently, existing CSI-based techniques exhibit limitations in terms of environmental adaptability. As such, optimizing the utilization of subcarrier CSI stands as a critical avenue for enhancing sensing performance. Within the OFDM communication framework, this work derives sensing outcomes for both detection and estimation by harnessing the CSI from every individual measured subcarrier, subsequently consolidating these outcomes. When contrasted against results derived from CSI based on specific extraction protocols or those obtained through weighted summation, the methodology introduced in this study offers substantial improvements in CSI-based detection and estimation performance. This approach not only underscores the significance but also serves as a robust exemplar for the comprehensive application of CSI.</p></div>","PeriodicalId":100790,"journal":{"name":"Journal of Information and Intelligence","volume":"2 4","pages":"Pages 365-374"},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949715924000374/pdfft?md5=90504ae06b478f8e48c78218ff4dd240&pid=1-s2.0-S2949715924000374-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information and Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949715924000374","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In modern Wi-Fi systems, channel state information (CSI) serves as a foundational support for various sensing applications. Currently, existing CSI-based techniques exhibit limitations in terms of environmental adaptability. As such, optimizing the utilization of subcarrier CSI stands as a critical avenue for enhancing sensing performance. Within the OFDM communication framework, this work derives sensing outcomes for both detection and estimation by harnessing the CSI from every individual measured subcarrier, subsequently consolidating these outcomes. When contrasted against results derived from CSI based on specific extraction protocols or those obtained through weighted summation, the methodology introduced in this study offers substantial improvements in CSI-based detection and estimation performance. This approach not only underscores the significance but also serves as a robust exemplar for the comprehensive application of CSI.