Journal ArticleDOI
Tool release: gathering 802.11n traces with channel state information
Daniel Halperin,Wenjun Hu,Anmol Sheth,David Wetherall +3 more
- Vol. 41, Iss: 1, pp 53-53
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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.read more
Citations
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Interpreting Convolutional Neural Networks for Device-Free Wi-Fi Fingerprinting Indoor Localization via Information Visualization
TL;DR: This paper quantifies and visualizes CNN in comparison with the fully-connected feedforward deep neural network (DNN) (or multilayer perceptron), and observes that each model can automatically identify location-specific patterns, which are however different across models and are linked to the respective performance of each model.
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A CSI-Based Human Activity Recognition Using Deep Learning.
TL;DR: In this article, a 2D Convolutional Neural Network (CNN) classifier was used to recognize seven different human daily activities using channel state information (CSI) data collected from a Raspberry Pi 4.
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Semi-Sequential Probabilistic Model for Indoor Localization Enhancement
TL;DR: This paper proposes a semi-sequential probabilistic model (SSP) that applies an additional short term memory to enhance the performance of the probabilism indoor localization and demonstrates that SSP reduces the maximum error and boosts theperformance of existing Probabilistic approaches by 25% – 30%.
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APFNet: Amplitude-Phase Fusion Network for CSI-Based Action Recognition
TL;DR: In this paper, a novel action recognition model based on amplitude-phase fusion is proposed, where the phase error is first corrected before information extraction, and a lightweight multi-data fusion network is then designed and applied to fuse amplitude and phase information before extracting features for action recognition.
Book ChapterDOI
Wi-Dog: Monitoring School Violence with Commodity WiFi Devices
TL;DR: Wi-Dog, a non-invasive physical violence monitoring scheme based on commodity WiFi infrastructures, is presented and a wavelet-entropy-based segmentation method is proposed to detect movement transitions in the distance and the complete local-global analysis is further adopted to improve overall performance.
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
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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.