相关论文: Gesture Recognition with mmWave Wi-Fi Access Point…

The accuracy of channel state information (CSI) acquisition directly affects the performance of millimeter wave (mmWave) communications. In this article, we provide an overview on CSI acquisition, including beam training and channel…

The lack of adequate training data is one of the major hurdles in WiFi-based activity recognition systems. In this paper, we propose Wi-Fringe, which is a WiFi CSI-based device-free human gesture recognition system that recognizes named…

As low frequency band becomes more and more crowded, millimeter-wave (mmWave) has attracted significant attention recently. IEEE has released the 802.11ad standard to satisfy the demand of ultra-high-speed communication. It adopts…

Due to the advance of technologies, machines are increasingly present in people's daily lives. Thus, there has been more and more effort to develop interfaces, such as dynamic gestures, that provide an intuitive way of interaction.…

The use of millimeter-wave (mmWave) bandwidth is one key enabler to achieve the high data rates in the fifth-generation (5G) cellular systems. However, mmWave signals suffer from significant path loss due to high directivity and sensitivity…

WiFi sensing is an important part of the new WiFi 802.11bf standard, which can detect motion and measure distances. In recent years, some machine learning methods have been proposed for human activity recognition from WiFi signals. However,…

Device-free Wi-Fi sensing has numerous benefits in practical settings, as it eliminates the requirement for dedicated sensing devices and can be accomplished using current low-cost Wi-Fi devices. With the development of Wi-Fi standards,…

Millimeter-wave (mmWave) networks offer the potential for high-speed data transfer and precise localization, leveraging large antenna arrays and extensive bandwidths. However, these networks are challenged by significant path loss and…

Wireless signal recognition (WSR) is a crucial technique for intelligent communications and spectrum sharing in the next six-generation (6G) wireless communication networks. It can be utilized to enhance network performance and efficiency,…

Millimeter-wave (mmWave) technology is increasingly recognized as a pivotal technology of the sixth-generation communication networks due to the large amounts of available spectrum at high frequencies. However, the huge overhead associated…

When operated in the mmWave band, user channels get highly correlated which can be exploited in mmWave-NOMA systems to cluster a set of "correlated" users together. Identifying the set of users to cluster greatly affects the viability of…

The millimeter wave (mmWave) bands have attracted considerable attention for high precision localization applications due to the ability to capture high angular and temporal resolution measurements. This paper explores mmWave-based…

Enabling highly-mobile millimeter wave (mmWave) and terahertz (THz) wireless communication applications requires overcoming the critical challenges associated with the large antenna arrays deployed at these systems. In particular, adjusting…

In this paper, we develop a deep learning (DL)-guided hybrid beam and power allocation approach for multiuser millimeter-wave (mmWave) networks, which facilitates swift beamforming at the base station (BS). The following persisting…

This paper presents a new radiometric fingerprint that is revealed by micro-signals in the channel state information (CSI) curves extracted from commodity Wi-Fi devices. We refer to this new fingerprint as "micro-CSI". Our experiments show…

Human gesture recognition has drawn much attention in the area of computer vision. However, the performance of gesture recognition is always influenced by some gesture-irrelevant factors like the background and the clothes of performers.…

Can we distinguish between two wireless transmitters sending exactly the same message, using the same protocol? The opportunity for doing so arises due to subtle nonlinear variations across transmitters, even those made by the same…

One strategy to obtain user location information in a wireless network operating at millimeter wave (mmWave) is based on the exploitation of the geometric relationships between the channel parameters and the user position. These…

WiFi sensing has been evolving rapidly in recent years. Empowered by propagation models and deep learning methods, many challenging applications are realized such as WiFi-based human activity recognition and gesture recognition. However, in…

Gestures form an important medium of communication between humans and machines. An overwhelming majority of existing gesture recognition methods are tailored to a scenario where humans and machines are located very close to each other. This…