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Journal ArticleDOI

Tool release: gathering 802.11n traces with channel state information

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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Journal ArticleDOI

WiGeR: WiFi-Based Gesture Recognition System

TL;DR: A novel device-free WiFi-based gesture recognition system (WiGeR) by leveraging the fluctuations in the channel state information (CSI) of WiFi signals caused by hand motions to classify gestures with high accuracy.
Proceedings ArticleDOI

KEEP: Fast Secret Key Extraction Protocol for D2D Communication

TL;DR: KEEP uses a validation-recombination mechanism to obtain consistent secret keys from CSI measurements of all subcarriers and achieves high security level of the keys and fast key-generation rate.
Journal ArticleDOI

Towards occupant activity driven smart buildings via WiFi-enabled IoT devices and deep learning

TL;DR: DeepHare is proposed, a deep learning-based human activity recognition scheme that can automatically identify common activities using only commodity WiFi-enabled IoT devices and an innovative deep learning framework, Autoencoder Long-term Recurrent Convolutional Network (AE-LRCN), is proposed.
Journal ArticleDOI

Towards a Diffraction-based Sensing Approach on Human Activity Recognition

TL;DR: It is argued that a deep understanding of radio signal propagation in wireless sensing is needed, and it may be possible to develop a deterministic sensing model to make the signal variation patterns predictable, and this model is proposed to quantitatively determine the signal change with respect to a target's motions.
Posted Content

FreeSense:Indoor Human Identification with WiFi Signals

TL;DR: Experimental results indicate that the identification accuracy is about 88.9% to 94.5% when the candidate user set changes from 6 to 2, showing that the proposed human identification method is effective in domestic environments.
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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