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Journal ArticleDOI

Tool release: gathering 802.11n traces with channel state information

22 Jan 2011-Vol. 41, Iss: 1, pp 53-53
TL;DR: 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.

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Citations
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Journal ArticleDOI
18 Jun 2020-Sensors
TL;DR: A foreign object intrusion detection method based on WiFi technology, which uses radio frequency (RF) signals to sense environmental changes and is suitable for lightless tunnel environments and a method combining the MUSIC algorithm and static clutter suppression is proposed.
Abstract: With continuous development in the scales of cities, the role of the metro in urban transportation is becoming more and more important. When running at a high speed, the safety of the train in the tunnel is significantly affected by any foreign objects. To address this problem, we propose a foreign object intrusion detection method based on WiFi technology, which uses radio frequency (RF) signals to sense environmental changes and is suitable for lightless tunnel environments. Firstly, based on extensive experiments, the abnormal phase offset between the RF chains of the WiFi network card and its offset law was observed. Based on this observation, a fast phase calibration method is proposed. This method only needs the azimuth information between the transmitter and the receiver to calibrate the the phase offset rapidly through the compensation of the channel state information (CSI) data. The time complexity of the algorithm is lower than the existing algorithm. Secondly, a method combining the MUSIC algorithm and static clutter suppression is proposed. This method utilizes the incoherence of the dynamic reflection signal to improve the efficiency of foreign object detection and localization in the tunnel with a strong multipath effect. Finally, experiments were conducted using Intel 5300 NIC in the indoor environment that was close to the tunnel environment. The performance of the detection probability and localization accuracy of the proposed method is tested.

3 citations

Proceedings ArticleDOI
17 Jun 2019
TL;DR: The study presented a maximum likehood angle estimation algorithm for OFDM Wi-Fi signals and multi-antenna receivers and compared two models: a model of independent zero-size antennas and a finite-size model of mutual coupled antennas.
Abstract: A convenient indoor navigation is still an unsolved problem. The solution is in high demand: advertising, goods promotion, subway navigation and so on need a cheap and reliable positioning method. WiFi-based positioning looks like a promising candidate: it doesn't require an additional complex local infrastructure, user devices (mobile phones) can process Wi-Fi signals right now, Wi-Fi signals are wideband and strong. Wi-Fi positioning methods can be divided into categories: fingerprinting, received signal strength indication, time-of-flight and triangulation based. In the study we considered a triangulation method. Several methods to form signal angle-of-arrival measurements are known: MUSIC, generalized cross-correlation and others. In addition, in the study we presented a maximum likehood angle estimation algorithm for OFDM Wi-Fi signals and multi-antenna receivers. The algorithms have differences. Proposed one allows to measure angle-of-arrival and anlge-of-departure, it has low estimation noise. The MUSIC algorithm can determine multipath propagation. The generalized algorithm is simple enough. But all the algorithms utilize the antenna mathematical model. The model provides the relationship between signal phase differences for antennas and the angle-of-arrival. The algorithms need the appropriate model to get good positioning accuracy. We compared two models: a model of independent zero-size antennas and a finite-size model of mutual coupled antennas. The first one is simple enough and is described by trigonometric formulas. The second one is complex, and we used electromagnetic simulation into CST Studio to get phase-to-angle relations. The electromagnetic simulation predicts up 5–10 degree corrections to angle-of-arrival in comparison with simple independent antennas model. To approve simulation results we created Wi-Fi receiver and transmitter prototypes based on COTS Intel 5300 modules and custom drivers CSITool. It is shown by the experiments that the antennas mutual coupling offsets the angle of arrival estimations about 5–10 degrees. We performed the experiments in our laboratory room and got from 3 to 10 degrees AoA estimation error profile. The error profile was used for a triangulation positioning simulation, as result we achieved about 1 m localization error.

3 citations


Cites methods from "Tool release: gathering 802.11n tra..."

  • ...CSITool utilities and Intel 5300 WiFi boards were used for experiments both indoors and outdoors....

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  • ...CSITool provides 8 bits for both real and imagine parts of CSI....

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  • ...The values are presented by CSITool as channel state information (CSI) complex numbers....

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  • ...We used commercial off-the-shelf WiFi modules from Intel with custom drivers CSITool [9]....

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  • ...To approve simulation results we created Wi-Fi receiver and transmitter prototypes based on COTS Intel 5300 modules and custom drivers CSITool....

    [...]

Journal ArticleDOI
TL;DR: In this article , a generative model is used as a reconstruction prior and the search manifold for the sensor fusion tasks, and the method also handles cases where observations are accessed only via subsampling i.e. compressed sensing.
Abstract: Abstract A new method for multimodal sensor fusion is introduced. The technique relies on a two-stage process. In the first stage, a multimodal generative model is constructed from unlabelled training data. In the second stage, the generative model serves as a reconstruction prior and the search manifold for the sensor fusion tasks. The method also handles cases where observations are accessed only via subsampling i.e. compressed sensing. We demonstrate the effectiveness and excellent performance on a range of multimodal fusion experiments such as multisensory classification, denoising, and recovery from subsampled observations.

3 citations

Proceedings ArticleDOI
01 Sep 2016
TL;DR: This paper presents a procedure with uses channel state information of an IEEE 802.11 High Throughput wireless link to reliably detect the presence of moving items, such as people crossing a room.
Abstract: Ubiquitous wireless local networks which use channel transfer function estimation to compensate for echoes on the wireless channel are uniquely suited for motion detection as a secondary use. In this way, added value can be provided without additional hardware. This paper presents a procedure with uses channel state information of an IEEE 802.11 High Throughput wireless link to reliably detect the presence of moving items, such as people crossing a room. By leveraging CSI instead of RSSI, the frequency-selective fading characteristic of indoor wireless channels can be taken into account while eliminating the effect of power level fluctuations in consumer-grade wireless hardware.

3 citations


Cites methods from "Tool release: gathering 802.11n tra..."

  • ...In order to evaluate the use of commercial wireless LAN hardware, a laptop computer has been outfitted with a wireless card compatible with the csitool software suite [7], which reports the coefficients for individual subcarriers....

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Journal ArticleDOI
TL;DR: The WiPOS, a password inference system based on wireless signals, is put forward, a device-free system that uses two commercial off-the-shelf (COTS) devices to collect WiFi signals and achieves improvement on both keystroke recognition and password prediction.
Abstract: WiFi access points are sources of considerable security risks as the wireless signals have the potential to leak important private information such as passwords. This article examines the security issues posed by point-of-sale (POS) terminals which are widely used in WiFi-covered environments, such as restaurants, banks, and libraries. In particular, we envisage an attack model on passwords entered on POS terminals. We put forward the WiPOS, a password inference system based on wireless signals. Specifically, the WiPOS is a device-free system that uses two commercial off-the-shelf (COTS) devices to collect WiFi signals. Implementing a new keystroke segmentation algorithm and adopting support vector machine (SVM) classifiers with global alignment kernel (GAK), the WiPOS achieves improvement on both keystroke recognition and password prediction. The experimental results show that the WiPOS can achieve more than 73% accuracy for 6-digit password with the top 100 candidates. This article calls the community to take a closer look at the risks posed by the current ubiquitous WiFi devices.

3 citations


Cites methods from "Tool release: gathering 802.11n tra..."

  • ...The WiPOS adopts a modifier driver developed by [5] to capture the CSI values from the Intel 5300 NIC....

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References
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Proceedings ArticleDOI
30 Aug 2010
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.
Abstract: RSSI is known to be a fickle indicator of whether a wireless link will work, for many reasons. This greatly complicates operation because it requires testing and adaptation to find the best rate, transmit power or other parameter that is tuned to boost performance. We show 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. Our model uses 802.11n Channel State Information measurements as input to an OFDM receiver model we develop by using the concept of effective SNR. It is simple, easy to deploy, broadly useful, and accurate. It makes packet delivery predictions for 802.11a/g SISO rates and 802.11n MIMO rates, plus choices of transmit power and antennas. We report testbed experiments that show narrow transition regions (

697 citations


"Tool release: gathering 802.11n tra..." refers methods in this paper

  • ...It works on up-to-date Linux operating systems: in our testbed we use Ubuntu 10.04 LTS with the 2.6.36 kernel....

    [...]

Journal ArticleDOI
01 Oct 2001
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).
Abstract: At some point in the future, how far out we do not exactly know, wireless access to the Internet will outstrip all other forms of access bringing the freedom of mobility to the way we access the we...

615 citations

Journal ArticleDOI
07 Jan 2010
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.
Abstract: The use of multiple antennas and MIMO techniques based on them is the key feature of 802.11n equipment that sets it apart from earlier 802.11a/g equipment. It is responsible for superior performance, reliability and range. In this tutorial, we provide a brief introduction to multiple antenna techniques. We describe the two main classes of those techniques, spatial diversity and spatial multiplexing. To ground our discussion, we explain how they work in 802.11n NICs in practice.

89 citations