Related papers: Through-Wall Imaging based on WiFi Channel State I…
Accurate channel state information (CSI) is critical to the performance of wireless communication systems, especially with the increasing scale and complexity introduced by 5G and future 6G technologies. While artificial intelligence (AI)…
To achieve higher throughput in next-generation Wi-Fi systems, a station (STA) needs to efficiently compress channel state information (CSI) and feed it back to an access point (AP). In this paper, we propose a novel deep learning…
Different technologies have been proposed to provide indoor localisation: magnetic field, bluetooth , WiFi, etc. Among them, WiFi is the one with the highest availability and highest accuracy. This fact allows for an ubiquitous accurate…
Ground-based Whole Sky Imagers (WSIs) are increasingly being used for various remote sensing applications. While the fundamental requirements of a WSI are to make it climate-proof with an ability to capture high resolution images, cost also…
In this paper, we explore the use of channel state information (CSI) from a WiFi system to estimate the breathing rate of a person in a room. In order to extract WiFi CSI components that are sensitive to breathing, we propose to consider…
Indoor localization is getting increasing demands for various cutting-edged technologies, like Virtual/Augmented reality and smart home. Traditional model-based localization suffers from significant computational overhead, so fingerprint…
We study the state-dependent (SD) wiretap channel (WTC) with non-causal channel state information (CSI) at the encoder. This model subsumes all other instances of CSI availability as special cases, and calls for an efficient utilization of…
Ambient intelligence, continuously understanding human presence, activity, and physiology in physical spaces, is fundamental to smart environments, health monitoring, and human-computer interaction. WiFi infrastructure provides a…
In modern wireless communication systems, the effective processing of Channel State Information (CSI) is crucial for enhancing communication quality and reliability. However, current methods often handle different tasks in isolation,…
Semantic Image Synthesis (SIS) is a subclass of image-to-image translation where a photorealistic image is synthesized from a segmentation mask. SIS has mostly been addressed as a supervised problem. However, state-of-the-art methods depend…
Recently, deep learning-based compressive imaging (DCI) has surpassed the conventional compressive imaging in reconstruction quality and faster running time. While multi-scale has shown superior performance over single-scale, research in…
With the development of computer-aided diagnosis (CAD) and image scanning technology, Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis. Therefore, WSI analysis has become the key to modern digital…
In this letter, we characterize the performance of broadcast approach with continuum of transmission layers in random wireless networks where the channel state information (CSI) is assumed to be known only at the receiver. By modeling the…
The detection of multiple targets in an enclosed scene, from its outside, is a challenging topic of research addressed by Through-the-Wall Radar Imaging (TWRI). Traditionally, TWRI methods operate in two steps: first the removal of wall…
The air interface technology plays a crucial role in optimizing the communication quality for users. To address the challenges brought by the radio channel variations to air interface design, this article proposes a framework of wireless…
In this paper, a review of indirect microwave holography for through-wall imaging is presented. Indirect microwave holography is an imaging technique, enabling the complex object scattered fields (amplitude and phase) to be mathematically…
High-throughput biological imaging is often constrained by a trade-off between acquisition speed and image quality. Fast imaging modalities, such as wide-field fluorescence microscopy, enable large-scale data acquisition but suffer from…
We introduce a self-supervised framework for learning predictive and structured representations of wireless channels by modeling the temporal evolution of channel state information (CSI) in a compact latent space. Our method casts the…
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…
Wireless imaging has become a vital function in future integrated sensing and communication (ISAC) systems. However, traditional model-based and data-driven deep learning imaging methods face challenges related to multipath extraction,…