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
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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WiPass: 1D-CNN-based smartphone keystroke recognition Using WiFi signals
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WiFi based Multi-User Gesture Recognition
TL;DR: The results show that WiMU recognizes 2, 3, 4, 5, 6, 7, and 8 simultaneously performed gestures with accuracies of 95.6, 94.9, 93.7, 91.0, and 90.1 percent, respectively.
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Wireless non-invasive motion tracking of functional behavior
Heng Zhang,Jan David Smeddinck,Rainer Malaka,Yao Shu,Chong Chen,Bo He,Zengjun Fu,Michael Lawo +7 more
TL;DR: A tracking technology for everyday activities that consists of recognizing general physical activity, as well as the activities of common classes, and measuring the statistical duration of these recognized categories, which suggests a high reliability of the automatic detection outcomes.
Proceedings ArticleDOI
AdaComm: Tracing Channel Dynamics for Reliable Cross-Technology Communication
TL;DR: AdaComm is proposed, a generic framework to achieve self-adaptive CTC in dynamic channels that adopts online learning mechanism to adaptively adjust the decoding model at the CTC receiver and automatically learns the effective features directly from the raw received signals that are embedded with the current channel state.
Proceedings ArticleDOI
Triangular Antenna Layout Facilitates Deployability of CSI Indoor Localization Systems
TL;DR: This paper presents an autonomous self-calibrating method to significantly facilitate site survey for deploying CSI localization systems, and proposes a systematical evaluation mechanism to show the fundamental reason why linear antenna layout usually leads to serious errors and why non-linear antenna layout is better off.
References
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