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Journal ArticleDOI

Tool release: gathering 802.11n traces with channel state information

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TLDR
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.
Abstract
We are pleased to announce the release of a tool that records detailed measurements of the wireless channel along with received 802.11 packet traces. It runs on a commodity 802.11n NIC, and records Channel State Information (CSI) based on the 802.11 standard. Unlike Receive Signal Strength Indicator (RSSI) values, which merely capture the total power received at the listener, the CSI contains information about the channel between sender and receiver at the level of individual data subcarriers, for each pair of transmit and receive antennas.Our toolkit uses the Intel WiFi Link 5300 wireless NIC with 3 antennas. It works on up-to-date Linux operating systems: in our testbed we use Ubuntu 10.04 LTS with the 2.6.36 kernel. The measurement setup comprises our 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 (or Octave) scripts for data analysis. We are releasing the binary of the modified firmware, and the source code to all the other components.

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Citations
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WiEps: Measurement of Dielectric Property with Commodity WiFi Device -- An application to Ethanol/Water Mixture

TL;DR: By measuring the dielectric property, this technique is promising to be applied to new IoT applications using ubiquitous WiFi signals, such as food engineering, material manufacturing process monitoring, and security check.
Journal ArticleDOI

Placement Matters

TL;DR: A new metric named SSNR (sensing-signal-to-noise-ratio) is proposed to quantify the sensing capability of WiFi systems and it is demonstrated that by properly placing the transmitter and receiver, the coverage of human walking sensing can be expanded by around 200%.
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Person-in-WiFi: Fine-grained Person Perception using WiFi

TL;DR: In this article, the authors used two sets of off-the-shelf WiFi antennas to acquire signals, i.e., one transmitter set and one receiver set, each set contains three antennas lined-up as a regular household WiFi router.
Proceedings ArticleDOI

A fine-grained indoor localization using multidimensional Wi-Fi fingerprinting

TL;DR: This paper proposes a new localization approach based on multidimensional Wi-Fi fingerprint that employs RSS, transmitted power, and channel information to construct an integrated fingerprint and uses a cosine similarity based matching algorithm and enhanced particle filter mechanism to achieve accurate localization and tracking.
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A CNN-LSTM Quantifier for Single Access Point CSI Indoor Localization.

TL;DR: This paper proposes a combined network structure between convolutional neural network (CNN) and long-short term memory (LSTM) quantifier for WiFi fingerprinting indoor localization and analyzes the instability of CSI and demonstrates a mitigation solution using a comprehensive filter and normalization scheme.
References
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Proceedings ArticleDOI

Predictable 802.11 packet delivery from wireless channel measurements

TL;DR: It is shown that, for the first time, wireless packet delivery can be accurately predicted for commodity 802.11 NICs from only the channel measurements that they provide, and the rate prediction is as good as the best rate adaptation algorithms for 802.
Journal ArticleDOI

ACM SIGCOMM computer communication review

TL;DR: The Internet is going mobile and wireless, perhaps quite soon, with a number of diverse technologies leading the charge, including, 3G cellular networks based on CDMA technology, a wide variety of what is deemed 2.5G cellular technologies (e.g., EDGE, GPRS and HDR), and IEEE 802.11 wireless local area networks (WLANs).
Journal ArticleDOI

802.11 with multiple antennas for dummies

TL;DR: This tutorial provides a brief introduction to multiple antenna techniques, and describes the two main classes of those techniques, spatial diversity and spatial multiplexing.
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