Wireless sensing based on Channel State Information (CSI) is rapidly spreading with the advent of 6G and newer Wi-Fi versions. Today, the CSI is regarded as one of the most promising elements for boosting service innovation on indoor device-free sensing. In addition, the wide adoption of the latest IEEE 802.11be standard, commonly known as Wi-Fi 7, might open up new possibilities for Wi-Fi sensing applications with even larger bandwidths, up to 320 MHz, and 4096 sub-carriers per spatial stream. However, researchers have still limited access to CSI extraction tools for such systems. In this work, we devise a framework based on software-defined radios to investigate the potential implications of the new Wi-Fi features, namely the wider channels and the higher number of sub-carriers, on a device-free positioning system based on position fingerprinting. In particular, we analyze the impact and the performance variations of this new technology across different bands in a position classification system, which has proven to be very accurate with previous versions of Wi-Fi. Our preliminary findings set some clear guidelines to direct future research efforts towards a better usage of newer Wi-Fi channels for sensing purposes. Furthermore, we publicly release our framework to the community of researchers and engineers for developing better Wi-Fi sensing solutions for smart homes, health care, and Internet-of- Things applications in general.

A Glimpse into IEEE 802.11be Channels: Can They Improve CSI-Based Sensing?

Cominelli, Marco;Raza, Shabbir;Lo Cigno, Renato;Gringoli, Francesco
2025-01-01

Abstract

Wireless sensing based on Channel State Information (CSI) is rapidly spreading with the advent of 6G and newer Wi-Fi versions. Today, the CSI is regarded as one of the most promising elements for boosting service innovation on indoor device-free sensing. In addition, the wide adoption of the latest IEEE 802.11be standard, commonly known as Wi-Fi 7, might open up new possibilities for Wi-Fi sensing applications with even larger bandwidths, up to 320 MHz, and 4096 sub-carriers per spatial stream. However, researchers have still limited access to CSI extraction tools for such systems. In this work, we devise a framework based on software-defined radios to investigate the potential implications of the new Wi-Fi features, namely the wider channels and the higher number of sub-carriers, on a device-free positioning system based on position fingerprinting. In particular, we analyze the impact and the performance variations of this new technology across different bands in a position classification system, which has proven to be very accurate with previous versions of Wi-Fi. Our preliminary findings set some clear guidelines to direct future research efforts towards a better usage of newer Wi-Fi channels for sensing purposes. Furthermore, we publicly release our framework to the community of researchers and engineers for developing better Wi-Fi sensing solutions for smart homes, health care, and Internet-of- Things applications in general.
File in questo prodotto:
File Dimensione Formato  
a329-cominelli stamped-e.pdf

accesso aperto

Descrizione: Articolo
Tipologia: Documento in Post-print
Licenza: Copyright dell'editore
Dimensione 612.97 kB
Formato Adobe PDF
612.97 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/640225
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact