Related papers: Meta-Learning-Based People Counting and Localizati…
Accurate and robust wireless localization is a key enabler for a wide range of mobile computing applications. Fingerprint-based localization using channel state information (CSI) has attracted significant attention due to its high accuracy…
Given the rapid advancements in wireless communication and terminal devices, high-speed and convenient WiFi has permeated various aspects of people's lives, and attention has been drawn to the location services that WiFi can provide.…
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…
In the field of artificial intelligence, self-supervised learning has demonstrated superior generalization capabilities by leveraging large-scale unlabeled datasets for pretraining, which is especially critical for wireless communication…
Today's societies are enveloped in an ever-growing telecommunication infrastructure. This infrastructure offers important opportunities for sensing and recording a multitude of human behaviors. Human mobility patterns are a prominent…
Huge overhead of beam training poses a significant challenge to mmWave communications. To address this issue, beam tracking has been widely investigated whereas existing methods are hard to handle serious multipath interference and…
This paper presents, for the first time, a method to extract both range and Doppler information from commercial Wi-Fi Channel State Information (CSI) using a monostatic (single transceiver) setup. Utilizing the CSI phase in Wi-Fi sensing…
With the growing demand for device-free and privacy-preserving sensing solutions, Wi-Fi sensing has emerged as a promising approach for human pose estimation (HPE). However, existing methods often process vast amounts of channel state…
We present experimental results and theoretical methods for the precise determination of the presence and the number of persons in an observed area by using Wi-Fi signals. Our setup does not require active cooperation of persons present in…
In recent years WiFi became the primary source of information to locate a person or device indoor. Collecting RSSI values as reference measurements with known positions, known as WiFi fingerprinting, is commonly used in various positioning…
Channel charting is a data-driven baseband processing technique consisting in applying self-supervised machine learning techniques to channel state information (CSI), with the objective of reducing the dimension of the data and extracting…
Indoor localization becomes a raising demand in our daily lives. Due to the massive deployment in the indoor environment nowadays, WiFi systems have been applied to high accurate localization recently. Although the traditional model based…
It has been shown that the channel state information (CSI) of a Wi-Fi system can be exploited to localize Wi-Fi devices or track trajectory of a moving target. In the existing literature, both sensing tasks are treated separately and some…
Channel state information (CSI)-based fingerprinting via neural networks (NNs) is a promising approach to enable accurate indoor and outdoor positioning of user equipments (UEs), even under challenging propagation conditions. In this paper,…
Wi-Fi fingerprinting remains one of the most practical solutions for indoor positioning, however, its performance is often limited by the size and heterogeneity of fingerprint datasets, strong Received Signal Strength Indicator variability,…
The accuracy of channel state information (CSI) is critical for improving the capacity of wireless networks. In this paper, we introduce a training protocol for wireless relay networks that uses channel estimation and feedforwarding…
Appropriate allocation of system resources is essential for meeting the increased user-traffic demands in the next generation wireless technologies. Traditionally, the system relies on channel state information (CSI) of the users for…
Locating the persons moving through an environment without the necessity of them being equipped with special devices has become vital for many applications including security, IoT, healthcare, etc. Existing device-free indoor localization…
Research has shown that counting WiFi packets called probe requests (PRs) implicitly provides a proxy for the number of people in an area. In this paper, we discuss a crowd counting system involving WiFi sensors detecting PRs over the air,…
The millimeter-wave (mmWave) communication is envisioned to provide orders of magnitude capacity improvement. However, it is challenging to realize a sufficient link margin due to high path loss and blockages. To address this difficulty, in…