Related papers: Velocity-Based Channel Charting with Spatial Distr…
Fingerprinting techniques are widely used for localization because of their accuracy, especially in the presence of wireless channel noise. However, the fingerprinting techniques require significant storage and running time, which is a…
Accurate localization is an essential technology for the flexible navigation of robots in large-scale environments. Both SLAM-based and map-based localization will increase the computing load due to the increase in map size, which will…
Indoor position technology has become one of the research highlights in the Internet of Things (IoT), but there is still a lack of universal, low-cost, and high-precision solutions. This paper conducts research on indoor position technology…
The coexistence between active wireless communications and passive RF spectrum use becomes an increasingly important requirement for coordinated spectrum access supporting critical services. The ongoing research and technological progress…
User grouping based on geographic location in fifth generation (5G) New Radio (NR) systems has several applications that can significantly improve network performance, user experience, and service delivery. We demonstrate how Sounding…
Navigation signs and maps, such as floor plans and street maps, are widely available and serve as ubiquitous aids for way-finding in human environments. Yet, they are rarely used by robot systems. This paper presents SignLoc, a global…
Accurate mobile device localization is critical for emerging 5G/6G applications such as autonomous vehicles and augmented reality. In this paper, we propose a unified localization method that integrates model-based and machine learning…
Wireless communication systems can significantly benefit from the availability of spatially consistent representations of the wireless channel to efficiently perform a wide range of communication tasks. Towards this purpose, channel…
Autonomous navigation based on precise localization has been widely developed in both academic research and practical applications. The high demand for localization accuracy has been essential for safe robot planing and navigation while it…
We propose a method for predicting the location of user equipment (UE) using wireless fingerprints in dynamic indoor non-line-of-sight (NLoS) environments. In particular, our method copes with the challenges posed by the drift, birth, and…
The objective of channel charting is to learn a virtual map of the radio environment from high-dimensional CSI that is acquired by a multi-antenna wireless system. Since, in static environments, CSI is a function of the transmitter…
Location information will play a very important role in emerging wireless networks such as Intelligent Transportation Systems, 5G, and the Internet of Things. However, wrong location information can result in poor network outcomes. It is…
Channel state information (CSI)-based user equipment (UE) positioning with neural networks -- referred to as neural positioning -- is a promising approach for accurate off-device UE localization. Most existing methods train their neural…
Irregular propagation environments with complex scattering effects challenge traditional ray-tracing-based localization. However, the environment's complexity enables solutions based on wave fingerprints (WFPs). Yet, since WFPs rely on the…
In this paper, we propose a unified localization framework (called UNILocPro) that integrates model-based localization and channel charting (CC) for mixed line-of-sight (LoS)/non-line-of-sight (NLoS) scenarios. Specifically, based on…
This paper proposes a novel approach to map-based navigation system for unmanned aircraft. The proposed system attempts label-to-label matching, not image-to-image matching, between aerial images and a map database. The ground objects can…
Predicting where people can walk in a scene is important for many tasks, including autonomous driving systems and human behavior analysis. Yet learning a computational model for this purpose is challenging due to semantic ambiguity and a…
Channel charting (CC) is a self-supervised positioning technique whose main limitation is that the estimated positions lie in an arbitrary coordinate system that is not aligned with true spatial coordinates. In this work, we propose a novel…
Channel charting (CC) has become a key technology for RF-based localization, enabling unsupervised radio fingerprinting, even in non line of sight scenarios, with a minimum of reference position labels. However, most CC models assume…
Finding efficient means of fingerprinting microstructural information is a critical step towards harnessing data-centric machine learning approaches. A statistical framework is systematically developed for compressed characterisation of a…