5 papers
OmniLoc: A Geometry-Aware Foundation Model for Anchor-Free UE Localization Across Diverse Indoor Environments
Lei Chu, Yuning Zhang, Omer Gokalp Serbetci +3
Indoor localization from wireless measurements remains challenging in large-scale deployments due to substantial variation in building geometry, the set of detectable access points…
WiLoc: Massive Measured Dataset of Wi-Fi Channel State Information with Application to Machine-Learning Based Localization
Yuning Zhang, Lei Chu, Omer Gokalp Serbetci +2
Localization is a key component of the wireless ecosystem. Machine learning (ML)-based localization using channel state information (CSI) is one of the most popular methods for ach…
Cognitive Radio for Asymmetric Cellular Downlink with Multi-User MIMO
Omer Gokalp Serbetci, Lei Chu, Andreas F. Molisch
Cognitive radio (CR) is an important technique for improving spectral efficiency, letting a secondary system operate in a wireless spectrum when the primary system does not make us…
Ultra-wideband Double-Directionally Resolved Channel Measurements of Line-of-Sight Microcellular Scenarios in the Upper Mid-band
Naveed A. Abbasi, Kelvin Arana, Jorge Gomez-Ponce +7
The growing demand for higher data rates and expanded bandwidth is driving the exploration of new frequency ranges, including the upper mid-band spectrum (6-24 GHz), which is a pro…
Wireless Channel Aware Data Augmentation Methods for Deep Learning-Based Indoor Localization
Omer Gokalp Serbetci, Daoud Burghal, Andreas F. Molisch
Indoor localization is a challenging problem that - unlike outdoor localization - lacks a universal and robust solution. Machine Learning (ML), particularly Deep Learning (DL), met…