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
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Journal ArticleDOI
Location- and Person-Independent Activity Recognition with WiFi, Deep Neural Networks, and Reinforcement Learning
Yongsen Ma,Sheheryar Arshad,Swetha Muniraju,Eric Torkildson,Enrico Rantala,Klaus Doppler,Gang Zhou +6 more
TL;DR: In this article, the authors proposed a deep learning design for location and person-independent activity recognition with WiFi, which consists of three deep neural networks (DNNs): a 2D Convolutional Neural Network (CNN) as the recognition algorithm, a 1D CNN as the state machine, and a reinforcement learning agent for neural architecture search.
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Jian Ding,Ranveer Chandra +1 more
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Direction Finding of rogue Wi-Fi access points using an off-the-shelf MIMO-OFDM receiver
TL;DR: The key contribution of the current work is an approach of employing the multiple receiving antennas jointly with OFDM Channel State Information (CSI) as the basis for implementing an interferometry DF tool.
Proceedings ArticleDOI
CSpy: finding the best quality channel without probing
TL;DR: CSpy is the first to reliably estimate the strongest channel by utilizing channel responses extracted from off-the-shelf wireless chipsets, without probing any additional channels.
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Gate-ID: WiFi-Based Human Identification Irrespective of Walking Directions in Smart Home
Jin Zhang,Bo Wei,Fuxiang Wu,Limeng Dong,Wen Hu,Salil S. Kanhere,Chengwen Luo,Shui Yu,Jun Cheng +8 more
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References
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Predictable 802.11 packet delivery from wireless channel measurements
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