相关论文: Geo2SigMap: High-Fidelity RF Signal Mapping Using …

Radio Frequency (RF) sensing is attracting interest in research, standardization, and industry, especially for its potential in Internet of Things (IoT) applications. By leveraging the properties of the ElectroMagnetic (EM) waves used in…

The analysis of Synthetic Aperture Radar (SAR) imagery is an important step in remote sensing applications, and it is a challenging problem due to its inherent speckle noise. One typical solution is to model the data using the $G_I^0$…

Fifth generation (5G) network and beyond envision massive Internet of Things (IoT) rollout to support disruptive applications such as extended reality (XR), augmented/virtual reality (AR/VR), industrial automation, autonomous driving, and…

Radio resource management in cellular networks is typically based on device measurements reported to the serving base station. Frequent measuring of signal quality on available frequencies would allow for highly reliable networks and…

Vision-aided wireless sensing is emerging as a cornerstone of 6G mobile computing. While data-driven approaches have advanced rapidly, establishing a precise geometric correspondence between ego-centric visual data and radio propagation…

High reliability guarantees for Ultra-Reliable Low-Latency Communications (URLLC) require accurate knowledge of channel statistics, used as an input for rate selection. Exploiting the spatial consistency of channel statistics arises as a…

Novel radio map estimation in optical wireless communications is proposed based on ML prediction rather than simulation techniques. ML training is performed on simulation and experimentally generated synthetic data and in both cases,…

Radio map estimation (RME) is the problem of inferring the value of a certain metric (e.g. signal power) across an area of interest given a collection of measurements. While most works tackle this problem from a purely non-Bayesian…

Accurate indoor pathloss prediction is crucial for optimizing wireless communication in indoor settings, where diverse materials and complex electromagnetic interactions pose significant modeling challenges. This paper introduces…

In wireless networks, radio-map based locating techniques are commonly used to cope the complex fading feature of radio signal, in which a radio-map is built by calibrating received signal strength (RSS) signatures at training locations in…

The high demand for fabricating microresonators with desired optical properties has led to various techniques to optimize geometries, mode structures, nonlinearities and dispersion. Depending on applications, the dispersion in such…

In this study, we present a method to predict the Received signal strength indication (RSSI) in an area of the base station. Traditional attenuated wave propagation models are often time consuming as well as computationally complex,…

Low-altitude wireless networks (LAWN) are rapidly expanding with the growing deployment of unmanned aerial vehicles (UAVs) for logistics, surveillance, and emergency response. Reliable connectivity remains a critical yet challenging task…

Radio maps are essential for enhancing wireless communications and localization. However, existing methods for constructing radio maps typically require costly calibration processes to collect location-labeled channel state information…

Enriching information of spectrum coverage, radiomap plays an important role in many wireless communication applications, such as resource allocation and network optimization. To enable real-time, distributed spectrum management,…

Precise aerial radio environment characterization is vital for low-altitude planning. However, existing datasets and estimation methods lack the high-resolution granularity required for complex aerial spaces. Additionally, current schemes…

Accurate RF propagation modeling in urban environments is critical for developing digital spectrum twins and optimizing wireless communication systems. We introduce OpenGERT, an open-source automated Geometry Extraction tool for Ray…

Incorporating artificial intelligence and machine learning (AI/ML) methods within the 5G wireless standard promises autonomous network behavior and ultra-low-latency reconfiguration. However, the effort so far has purely focused on learning…

Due to the Internet of Things (IoT) proliferation, Radio Frequency (RF) channels are increasingly congested with new kinds of devices, which carry unique and diverse communication needs. This poses complex challenges in modern digital…

The design and deployment of fifth-generation (5G) wireless networks pose significant challenges due to the increasing number of wireless devices. Path loss has a landmark importance in network performance optimization, and accurate…