Related papers: Validation of Practicality for CSI Sensing Utilizi…
Multiple-input multiple-output (MIMO) is an enabling technology to meet the growing demand for faster and more reliable communications in wireless networks with a large number of terminals, but it can also be applied for position estimation…
Machine learning techniques have shown remarkable accuracy in localization tasks, but their dependency on vast amounts of labeled data, particularly Channel State Information (CSI) and corresponding coordinates, remains a bottleneck.…
Advances in computer vision and machine learning techniques have led to significant development in 2D and 3D human pose estimation from RGB cameras, LiDAR, and radars. However, human pose estimation from images is adversely affected by…
This research presents a novel application of computer vision (CV) and deep learning methods for real-time sea state recognition, aiming to contribute to improving the operational safety and energy efficiency of seagoing vessels, key…
Recently Convolutional Neural Networks (CNNs) have been shown to achieve state-of-the-art performance on various classification tasks. In this paper, we present for the first time a place recognition technique based on CNN models, by…
Human behavior recognition has been considered as a core technology that can facilitate variety of applications. However, accurate detection and recognition of human behavior is still a big challenge that attracts a lot of research efforts.…
Passive indoor localization, integral to smart buildings, emergency response, and indoor navigation, has traditionally been limited by a focus on single-target localization and reliance on multi-packet CSI. We introduce a novel Multi-target…
Humans' ability to detect and locate salient objects on images is remarkably fast and successful. Performing this process by using eye tracking equipment is expensive and cannot be easily applied, and computer modeling of this human…
Utilizing deep learning (DL) techniques for radio-based positioning of user equipment (UE) through channel state information (CSI) fingerprints has demonstrated significant potential. DL models can extract complex characteristics from the…
Sensing using cellular infrastructure may be one of the defining feature of sixth generation (6G) wireless systems. Wideband 6G communication channels operating at higher frequency bands (upper mmWave bands) are better modeled using…
Wireless communication networks rely heavily on channel state information (CSI) to make informed decision for signal processing and network operations. However, the traditional CSI acquisition methods is facing many difficulties:…
Knowledge of information about the propagation channel in which a wireless system operates enables better, more efficient approaches for signal transmissions. Therefore, channel state information (CSI) plays a pivotal role in the system…
Knowledge of channel state information (CSI) is fundamental to many functionalities within the mobile wireless communications systems. With the advance of machine learning (ML) and digital maps, i.e., digital twins, we have a big…
The first step of a secure communication is authenticating legible users and detecting the malicious ones. In the last recent years, some promising schemes proposed using wireless medium network's features, in particular, channel state…
This paper presents an end-to-end deep learning framework in a movable antenna (MA)-enabled multiuser communication system. In contrast to the conventional works assuming perfect channel state information (CSI), we address the practical CSI…
Taking advantage of the rich information provided by Wi-Fi measurement setups, Wi-Fi-based human behavior sensing leveraging Channel State Information (CSI) measurements has received a lot of research attention in recent years. The…
In a wireless network, gathering information at the base station about mobile users based only on uplink channel measurements is an interesting challenge. Indeed, accessing the users locations and predicting their downlink channels would be…
Modern indoor localization techniques are essential to overcome the weak GPS coverage in indoor environments. Recently, considerable progress has been made in Channel State Information (CSI) based indoor localization with signal…
Human pose estimation based on Channel State Information (CSI) has emerged as a promising approach for non-intrusive and precise human activity monitoring, yet faces challenges including accurate multi-person pose recognition and effective…
Deep learning (DL) methods have been recently proposed for user equipment (UE) localization in wireless communication networks, based on the channel state information (CSI) between a UE and each base station (BS) in the uplink. With the CSI…