A Software-Defined and Distributed Wi-Fi Channel-State Information Acquisition Testbed

We propose a software-defined testbed for Wi-Fi channel-state information (CSI) acquisition. This testbed features distributed software-defined radios (SDRs) and a custom IEEE 802.11a software stack that enables the passive collection of CSI data from commercial off-the-shelf (COTS) devices that connect to an existing Wi-Fi network. Unlike commodity Wi-Fi sniffers or channel sounders, our software-defined testbed enables a quick exploration of advanced CSI estimation algorithms in real-world scenarios from naturally-generated Wi-Fi traffic. We explore the effectiveness of two advanced algorithms that denoise CSI estimates, and we demonstrate that CSI-based positioning of COTS Wi-Fi devices with a multilayer perceptron is feasible in an indoor office/lab space in which people are moving.

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Publication Details

Published
2024-10-27
DOI
https://doi.org/10.1109/ieeeconf60004.2024.10942693
Citations
1
Primary Topic
Wireless Networks and Protocols
Type
article
Field-Weighted Citation Impact
0.35
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article

A Software-Defined and Distributed Wi-Fi Channel-State Information Acquisition Testbed

Christoph Studer, Frederik Zumegen
1 citations
Wireless Networks and Protocols
0.35
article

A Software-Defined and Distributed Wi-Fi Channel-State Information Acquisition Testbed

Christoph Studer, Frederik Zumegen
article en
1 citations

Abstract

We propose a software-defined testbed for Wi-Fi channel-state information (CSI) acquisition. This testbed features distributed software-defined radios (SDRs) and a custom IEEE 802.11a software stack that enables the passive collection of CSI data from commercial off-the-shelf (COTS) devices that connect to an existing Wi-Fi network. Unlike commodity Wi-Fi sniffers or channel sounders, our software-defined testbed enables a quick exploration of advanced CSI estimation algorithms in real-world scenarios from naturally-generated Wi-Fi traffic. We explore the effectiveness of two advanced algorithms that denoise CSI estimates, and we demonstrate that CSI-based positioning of COTS Wi-Fi devices with a multilayer perceptron is feasible in an indoor office/lab space in which people are moving.

ETH Zurich (CH)
Openalex Percentile: Top 33%
Wireless Networks and Protocols
0.35
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