scispace - formally typeset
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.

read more

Content maybe subject to copyright    Report

Citations
More filters
Posted Content

Wi-Fi Gesture Recognition on Existing Devices

TL;DR: The first wireless gesture recognition system that operates using existing Wi-Fi signals and devices is introduced, and can achieve a classification accuracy of 91% while classifying four gestures across six participants, without the need for per-participant training.
Proceedings Article

WiFi-Based Human Identification via Convex Tensor Shapelet Learning

TL;DR: A new optimization-based shapelet learning framework for tensors, namely Convex Clustered Concurrent Shapelet Learning (CSL), which formulates the learning problem as a convex optimization, can be obtained efficiently with a generalized gradient-based algorithm.
Journal ArticleDOI

Writing in the Air with WiFi Signals for Virtual Reality Devices

TL;DR: This paper attempts to utilize channel state information (CSI) derived from wireless signals to realize the device-free air-write recognition called Wri-Fi, and uses the Hidden Markov model for character modeling and classification.
Journal ArticleDOI

Low Human-Effort, Device-Free Localization with Fine-Grained Subcarrier Information

TL;DR: LIFS, a Low human-effort, device-free localization system with fine-grained subcarrier information, which can localize a target accurately without offline training, outperforming the state-of-the-art systems.
Proceedings ArticleDOI

DeepSense: Device-Free Human Activity Recognition via Autoencoder Long-Term Recurrent Convolutional Network

TL;DR: A device-free human activity recognition scheme that can automatically identify common activities via deep learning using only commodity WiFi-enabled IoT devices is proposed, and an innovative deep learning framework, Autoencoder Long-term Recurrent Convolutional Network (AE-LRCN), is proposed.
References
More filters
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.
Related Papers (5)