Proceedings ArticleDOI
Free Your CSI: A Channel State Information Extraction Platform For Modern Wi-Fi Chipsets
Francesco Gringoli,Matthias Schulz,Jakob Link,Matthias Hollick +3 more
- pp 21-28
TLDR
The nexmon CSI Extractor Tool allows per-frame CSI extraction for up to four spatial streams using up toFour receive chains on modern Broadcom and Cypress Wi-Fi chips with up to 80MHz bandwidth in both the 2.4 and 5GHz bands.Abstract:
Modern wireless transmission systems heavily benefit from knowing the channel response. The evaluation of Channel State Information (CSI) during the reception of a frame preamble is fundamental to properly equalizing the rest of the transmission at the receiver side. Reporting this state information back to the transmitter facilitates mechanisms such as beamforming and MIMO, thus boosting the network performance. While these features are an integral part of standards such as 802.11ac, accessing CSI data on commercial devices is either not possible, limited to outdated chipsets or very inflexible. This hinders the research and development of innovative CSI-dependent techniques including localization, object tracking, and interference evaluation. To help researchers and practitioners, we introduce the nexmon CSI Extractor Tool. It allows per-frame CSI extraction for up to four spatial streams using up to four receive chains on modern Broadcom and Cypress Wi-Fi chips with up to 80MHz bandwidth in both the 2.4 and 5GHz bands. The tool supports devices ranging from the low-cost Raspberry Pi platform, over mobile platforms such as Nexus smartphones to state-of-the-art Wi-Fi APs. We release all tools and Wi-Fi firmware patches as extensible open source project. It includes our user-friendly smartphone application to demonstrate the CSI extraction capabilities in form of a waterfall diagram.read more
Citations
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From RSSI to CSI: Indoor Localization via Channel Response, A survey on indoor localization using PHY-layer information
Yang Zheng,Zhou Zimu,Yunhao Liu +2 more
TL;DR: This article surveys the new trend of channel response in localization and investigates a large body of recent works and classify them overall into three categories according to how to use CSI, highlighting the differences between CSI and RSSI.
Journal ArticleDOI
Wi-COVID: A COVID-19 Symptom Detection and Patient Monitoring Framework using WiFi.
TL;DR: This paper explores the possibility of monitoring respiration rates (RR) of COVID-19 patients using a widely-available technology at home – WiFi and proposes Wi-COVID, a non-invasive and non-wearable technology to monitor the patient and track RR for the healthcare provider.
Journal ArticleDOI
Deep Learning for Radio-Based Human Sensing: Recent Advances and Future Directions
TL;DR: A comprehensive review and taxonomy of recent research efforts on deep learning based RF sensing is provided, which identifies and compares several publicly released labeled RF sensing datasets that can facilitate such deep learning research.
Journal ArticleDOI
Differential Channel-State-Information-Based Human Activity Recognition in IoT Networks
TL;DR: This article recognizes multiple human activities in an Internet-of-Things (IoT) network using differential channel state information (CSI) of the available wireless fidelity (Wi-Fi) signals using long short-term memory (LSTM) model for automatic feature extraction and classification of human activities from the differential CSI.
Journal ArticleDOI
Estimating Indoor Occupancy Through Low-Cost BLE Devices
TL;DR: In this paper, a low-cost occupancy detection system based on detecting variations in Bluetooth Low Energy (BLE) signals related to the presence of humans is proposed, which can be used for automatically switching off the light, air conditioning, and ventilation, thereby saving significant amounts of energy in public buildings.
References
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Journal ArticleDOI
Tool release: gathering 802.11n traces with channel state information
TL;DR: The measurement setup comprises the customized versions of Intel's close-source firmware and open-source iwlwifi wireless driver, userspace tools to enable these measurements, access point functionality for controlling both ends of the link, and Matlab scripts for data analysis.
Journal ArticleDOI
From RSSI to CSI: Indoor localization via channel response
Zheng Yang,Zimu Zhou,Yunhao Liu +2 more
TL;DR: In this article, the authors survey the channel state information (CSI) in 802.11 a/g/n and highlight the differences between CSI and RSSI with respect to network layering, time resolution, frequency resolution, stability, and accessibility.
From RSSI to CSI: Indoor Localization via Channel Response, A survey on indoor localization using PHY-layer information
Yang Zheng,Zhou Zimu,Yunhao Liu +2 more
TL;DR: This article surveys the new trend of channel response in localization and investigates a large body of recent works and classify them overall into three categories according to how to use CSI, highlighting the differences between CSI and RSSI.
Journal ArticleDOI
Super-resolution TOA estimation with diversity for indoor geolocation
Xinrong Li,Kaveh Pahlavan +1 more
TL;DR: The measurement and simulation methods presented in this paper can be used to establish empirical performance bounds for real implementation of super-resolution indoor geolocation systems.
Proceedings ArticleDOI
Precise Power Delay Profiling with Commodity WiFi
Yaxiong Xie,Zhenjiang Li,Mo Li +2 more
TL;DR: Splicer, a software-based system that derives high-resolution power delay profiles by splicing the CSI measurements from multiple WiFi frequency bands is presented and a set of key techniques to separate the mixed hardware errors from the collected CSI measurements are proposed.