Related papers: Gesture Recognition with mmWave Wi-Fi Access Point…

This article presents mmHSense, a set of open labeled mmWave datasets to support human sensing research within Integrated Sensing and Communication (ISAC) systems. The datasets can be used to explore mmWave ISAC for various end applications…

Establishing and maintaining 5G mmWave vehicular connectivity poses a significant challenge due to high user mobility that necessitates frequent triggering of beam switching procedures. Departing from reactive beam switching based on the…

In reconfigurable intelligent surface (RIS) aided millimeter-wave (mmWave) communication systems, in order to overcome the limitation of the conventional channel state information (CSI) acquisition techniques, this paper proposes a location…

An end-to-end fiber-based network holds the potential to provide multi-gigabit fixed access to end-users. However, deploying fiber access, especially in areas where fiber is non-existent, can be time-consuming and costly, resulting in…

In massive multi-input multi-output (MIMO) systems, the main bottlenecks of location- and orientation-assisted beam alignment using deep neural networks (DNNs) are large training overhead and significant performance degradation. This paper…

High speed wireless access on 60 GHz spectrum relies on high-gain directional antennas to overcome the severe signal attenuation. However, perfect alignment between transmitting and receiving antenna beams is rare in practice and overheard…

Gesture awareness plays a crucial role in promoting human-computer interface. Previous works either depend on customized hardware or need a priori learning of wireless signal patterns, facing downsides in terms of the privacy concern,…

WiFi sensing has suffered from the limited bandwidths designated for its original communication purpose, leading to fundamental limits in multipath resolution and thus multi-user sensing. Unfortunately, it is practically prohibitive to…

In the last years, several machine learning-based techniques have been proposed to monitor human movements from Wi-Fi channel readings. However, the development of domain-adaptive algorithms that robustly work across different environments…

Due to its ubiquitous and contact-free nature, the use of WiFi infrastructure for performing sensing tasks has tremendous potential. However, the channel state information (CSI) measured by a WiFi receiver suffers from errors in both its…

Extended Reality (XR) enables a plethora of novel interactive shared experiences. Ideally, users are allowed to roam around freely, while audiovisual content is delivered wirelessly to their Head-Mounted Displays (HMDs). Therefore, truly…

Hand gesture recognition based on surface electromyographic (sEMG) signals is a promising approach for developing Human-Machine Interfaces (HMIs) with a natural control, such as intuitive robot interfaces or poly-articulated prostheses.…

Wi-Fi Channel State Information (CSI) has gained increasing interest for remote sensing applications. Recent studies show that Doppler velocity projections extracted from CSI can enable human activity recognition (HAR) that is robust to…

Recent advancements have showcased the potential of handheld millimeter-wave (mmWave) imaging, which applies synthetic aperture radar (SAR) principles in portable settings. However, existing studies addressing handheld motion errors either…

Deep learning is making a profound impact in the physical layer of wireless communications. Despite exhibiting outstanding empirical performance in tasks such as MIMO receive processing, the reasons behind the demonstrated superior…

Wi-Fi sensing has emerged as a powerful technology, leveraging channel state information (CSI) extracted from wireless data packets to enable diverse applications, ranging from human presence detection to gesture recognition and health…

This paper studies a WiFi indoor localisation technique based on using a deep learning model and its transfer strategies. We take CSI packets collected via the WiFi standard channel sounding as the training dataset and verify the CNN model…

Human Activity Recognition (HAR) is the identification and classification of static and dynamic human activities, which find applicability in domains like healthcare, entertainment, security, and cyber-physical systems. Traditional HAR…

Fast and precise beam alignment is crucial to support high-quality data transmission in millimeter wave (mmWave) communication systems. In this work, we propose a novel deep learning based hierarchical beam alignment method that learns two…

Touchscreen-based interaction on display devices are ubiquitous nowadays. However, capacitive touch screens, the core technology that enables its widespread use, are prohibitively expensive to be used in large displays because the cost…