Precise Power Delay Profiling with Commodity Wi-Fi

Xie, Yaxiong; Li, Zhenjiang; Li, Mo

doi:10.1109/tmc.2018.2860991

Cited by 239 publications

(140 citation statements)

References 39 publications

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“…The detailed parameters adopted in the evaluation are summarized in Table II. 1 PSNR is commonly adopted in the machine learning area for SR recovery, as shown in [7] 2 In order to emulate the MIMO-OFDM scenario, both two desktops are equipped with Qualcomm Atheros AR9380 WiFi netwowrk interface cards, and on top of that, a open source tool Atheros CSI Tool [27] is installed to obtain the real time channel coefficients. Figure 5.…”

Section: Resultsmentioning

confidence: 99%

Channel Estimation for WiFi Prototype Systems with Super-Resolution Image Recovery

Shi

Liu

Zhang

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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Channel estimation is crucial for modern WiFi system and becomes more and more challenging with the growth of user throughput in multiple input multiple output configuration. Plenty of literature spends great efforts in improving the estimation accuracy, while the interpolation schemes are overlooked. To deal with this challenge, we exploit the super-resolution image recovery scheme to model the non-linear interpolation mechanisms without pre-assumed channel characteristics in this paper. To make it more practical, we offline generate numerical channel coefficients according to the statistical channel models to train the neural networks, and directly apply them in some practical WiFi prototype systems. As shown in this paper, the proposed super-resolution based channel estimation scheme can outperform the conventional approaches in both LOS and NLOS scenarios, which we believe can significantly change the current channel estimation method in the near future.

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Section: Resultsmentioning

confidence: 99%

Channel Estimation for WiFi Prototype Systems with Super-Resolution Image Recovery

Shi

Liu

Zhang

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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“…As a result, short-range radio waves such as Wi-Fi are actively studied as alternative methods. In these methods, a target device receives a signal from each AP (access point) with known position of the AP, detects signal propagation distance and AoA (angle of arrival) from information, such as signal strength/phase, and on this basis computes its own position [13][14][15][16]. In addition, device-free methods [17][18][19][20] for detecting a person without any wearable device are also proposed, which monitor the changes in signal reception status between pairs of preset devices.…”

Section: Indoor Positioning Via Radio Wavesmentioning

confidence: 99%

Radiation Angle Estimation and High-Precision Pedestrian Positioning by Tracking Change of Channel State Information

Komamiya

Tang

Obana

2020

Sensors

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P2V (pedestrian-to-vehicle) communication, in which a pedestrian’s mobile device notifies its position to nearby vehicles in order to prevent pedestrian accidents, has attracted much research interest recently, but its performance largely depends on the precision of pedestrians’ positioning. Pedestrian positioning is generally performed by using GPS (Global Positioning System), and its precision may greatly degrade in urban canyons. To improve positioning precision of pedestrians, it was proposed that vehicles around pedestrians be used as anchors beside satellites. In this method, a pedestrian device overhears V2V (vehicle-to-vehicle) communication signals which carry the vehicle position and calculates a pedestrian’s position using pedestrian–vehicle distance/angle information estimated from CSI (channel state information) of the V2V signals. However, angle estimation typically depends on the number of antennas of the pedestrian device. In this paper, we propose a new method to estimate signal radiation angle by tracking temporal change of CSI caused by vehicle movement during signal transmission and investigate its application to precise pedestrian positioning. Three-dimensional ray tracing simulations confirm that compared to the base method using eight antennas, the proposed method with a single antenna reduces average angle error from 13 degrees to 3.9 degrees, and reduces average positioning error from 2.49 m to 0.78 m.

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“…The PLL phase offset θ l is fixed after the devices are started. The SFO phase offset θ s is caused by the offset of the sampling frequencies of Tx and Rx [34]. The PBD phase offset is caused by the time shift from the packet boundary uncertainty and follows a Gaussian distribution with the zero mean.…”

Section: A Csi Ratio: a Better Base Signalmentioning

confidence: 99%

WiMorse: A Contactless Morse Code Text Input System Using Ambient WiFi Signals

Niu

Zhang

Jiang

et al. 2019

IEEE Internet Things J.

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Recent years have witnessed advances of Internet of Things (IoT) technologies and their applications to enable contactless sensing and human-computer interaction in smart homes. For people with Motor Neurone Disease (MND), their motion capabilities are severely impaired and they have difficulties interacting with IoT devices and even communicating with other people. As the disease progresses, most patients lose their speech function eventually which makes the widely adopted voicebased solutions fail. In contrast, most patients can still move their fingers slightly even after they have lost the control of their arms and hands. Thus we propose to develop a Morse code based text input system, called WiMorse, which allows patients with minimal single-finger control to input and communicate with other people without attaching any sensor to their fingers. WiMorse leverages ubiquitous commodity WiFi devices to track subtle finger movements contactlessly and encode them as Morse code input. In order to sense the very subtle finger movements, we propose to employ the ratio of the Channel State Information (CSI) between two antennas to enhance the Signal to Noise Ratio. To address the severe location dependency issue in wireless sensing with accurate theoretical underpinning and experiments, we propose a signal transformation mechanism to automatically convert signals based on the input position, achieving stable sensing performance. Comprehensive experiments demonstrate that WiMorse can achieve higher than 95% recognition accuracy for finger generated Morse code, and is robust against input position, environment changes, and user diversity.

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Precise Power Delay Profiling with Commodity Wi-Fi

Cited by 239 publications

References 39 publications

Channel Estimation for WiFi Prototype Systems with Super-Resolution Image Recovery

Channel Estimation for WiFi Prototype Systems with Super-Resolution Image Recovery

Radiation Angle Estimation and High-Precision Pedestrian Positioning by Tracking Change of Channel State Information

WiMorse: A Contactless Morse Code Text Input System Using Ambient WiFi Signals

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