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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Journal ArticleDOI
RoFi: Rotation-Aware WiFi Channel Feedback
TL;DR: This paper proposes rotation-aware WiFi (RoFi) channel feedback to eliminate unnecessary CSI feedback while maintaining high throughput and shows the failure of existing mobility-aware methods, including CSI similarity, time-of-flight (ToF), and compression noise, in distinguishing the mobility status of rotation and mobile.
Proceedings ArticleDOI
WaveLoc: Wavelet Signatures for Ubiquitous Localization
TL;DR: This paper proposes WaveLoc, which effectively uses measurements from a trajectory as its fingerprint for localization, and demonstrates that WaveLoc is accurate and power efficient.
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DFPhaseFL: a robust device-free passive fingerprinting wireless localization system using CSI phase information
TL;DR: The proposed DFPhaseFL is the first device-free fingerprinting indoor localization system that purely uses CSI phase information and owns a better estimation precision compared with the other state of art, and maintain a stable localization accuracy for a long time without reacquiring the fingerprint database.
Proceedings ArticleDOI
WiFi-Based Activity Recognition using Activity Filter and Enhanced Correlation with Deep Learning
TL;DR: This paper develops a novel CSI compensation and enhancement method to compensate for the timing offset between the WiFi transmitter and receiver, enhance activity-related signals and reduce the dimension of inputs to DLN, and designs a novel activity filter to differentiate similar activities.
Journal ArticleDOI
WiFederated: Scalable WiFi Sensing Using Edge-Based Federated Learning
TL;DR: This work proposes WiFederated, a federated learning (FL) approach to train machine learning models for WiFi sensing tasks that provides a more accurate and time-efficient solution compared to existing transfer learning and adversarial learning solutions thanks to the parallel training ability at multiple clients.
References
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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.
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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).
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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.