Related papers: Sensor-Aided Learning for Wi-Fi Positioning with B…

This work reports experiences on using radio ranging to position sensors in a grid topology. The implementation is simple, efficient, and could be practically distributed. The paper describes an implementation and experimental result based…

An indoor localization approach uses Wi-Fi Access Points (APs) to estimate the Direction of Arrival (DoA) of the WiFi signals. This paper demonstrates FIND, a tool for Fine INDoor localization based on a software-defined radio, which…

As Wireless Sensor Networks are penetrating into the industrial domain, many research opportunities are emerging. One such essential and challenging application is that of node localization. A feed-forward neural network based methodology…

Position-aided beam selection methods have been shown to be an effective approach to achieve high beamforming gain while limiting the overhead and latency of initial access in millimeter wave (mmWave) communications. Most research in the…

Monitoring Wireless Sensor Networks (WSNs) are composed of sensor nodes that report temperature, relative humidity, and other environmental parameters. The time between two successive measurements is a critical parameter to set during the…

This paper presents a method to improve the localization accuracy of robots operating in a range-based localization network. The method is favorable especially when the robots operate in harsh environments where the access to a robust and…

With the growing integration of location based services (LBS) such as GPS in mobile devices, indoor position systems (IPS) have become an important role for research. There are several IPS methods such as AOA, TOA, TDOA, which use…

This paper presents an end-to-end deep learning framework using passive WiFi sensing to classify and estimate human respiration activity. A passive radar test-bed is used with two channels where the first channel provides the reference WiFi…

This paper aims at detecting an accurate position of the main entrance of the buildings. The proposed approach relies on the fact that the GPS signals drop significantly when the user enters a building. Moreover, as most of the public…

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…

With millimeter wave wireless communications, the resulting radiation reflects on most visible objects, creating rich multipath environments, namely in urban scenarios. The radiation captured by a listening device is thus shaped by the…

Integrated Sensing and Communications (ISAC) is emerging as a foundational paradigm for next-generation wireless networks, enabling communication infrastructures to simultaneously support data transmission and environment sensing. By…

Movable antenna (MA) has emerged as a promising technology for future wireless systems. Compared with traditional fixed-position antennas, MA improves system performance by antenna movement to optimize channel conditions. For multiuser…

We propose a new approach towards RSS (Received Signal Strength) based wireless localisation for scenarios where, instead of absolute positioning of an object, only the information whether an object is inside or outside of a specific area…

Millimeter wave signals and large antenna arrays are considered enabling technologies for future 5G networks. Despite their benefits for achieving high data rate communications, their potential advantages for tracking of the location of the…

Autonomous robotic systems have gained a lot of attention, in recent years. However, accurate prediction of robot motion in indoor environments with limited visibility is challenging. While vision-based and light detection and ranging…

Location-based services in a wireless network require nodes to know their locations accurately. Conventional solutions rely on contention-based medium access, where only one node can successfully transmit at any time in any neighborhood. In…

WiFi sensing is an emerging technology that utilizes wireless signals for various sensing applications. However, the reliance on supervised learning, the scarcity of labelled data, and the incomprehensible channel state information (CSI)…

We propose a WiFi Channel State Information (CSI) sensing framework for multi-station deployments that addresses two fundamental challenges in practical CSI sensing: station-wise feature missingness and limited labeled data. Feature…

We present a neural network architecture for jointly learning user locations and environment mapping up to isometry, in an unsupervised way, from channel state information (CSI) values with no location information. The model is based on an…