6 papers · 1 filter
Wireless Physical-Layer Foundation Models: Architectures, Learning Paradigms, Applications, and Deployment
Mohammad Cheraghinia, Davide Buffelli, Liu Li +6
Foundation models, i.e., large neural networks pretrained on broad unlabeled data and adapted to many downstream tasks, have reshaped natural language processing and computer visio…
Tracking the Turn: Mamba-Powered Human Orientation Detection using UWB
Mohammad Cheraghinia, Adnan Shahid, Jaron Fontaine +3
User orientation is crucial for many context-aware applications, including interactive museum experiences, smart door access, and intuitive human-environment interaction. However,…
Reasoning Meets Representation: Envisioning Neuro-Symbolic Wireless Foundation Models
Jaron Fontaine, Mohammad Cheraghinia, John Strassner +2
Recent advances in Wireless Physical Layer Foundation Models (WPFMs) promise a new paradigm of universal Radio Frequency (RF) representations. However, these models inherit critica…
Lightweight Foundation Model for Wireless Time Series Downstream Tasks on Edge Devices
Mohammad Cheraghinia, Eli De Poorter, Jaron Fontaine +3
While machine learning is widely used to optimize wireless networks, training a separate model for each task in communication and localization is becoming increasingly unsustainabl…
A Unified Foundation Model for Wireless Technology Recognition and Localization
Mohammad Cheraghinia, Eli De Poorter, Jaron Fontaine +2
Wireless Technology Recognition (WTR) and localization are essential in modern communication systems, enabling efficient spectrum management, seamless coexistence of diverse techno…
A Comprehensive Overview on UWB Radar: Applications, Standards, Signal Processing Techniques, Datasets, Radio Chips, Trends and Future Research Directions
Mohammad Cheraghinia, Adnan Shahid, Stijn Luchie +6
Due to their large bandwidth, relatively low cost, and robust performance, UWB radio chips can be used for a wide variety of applications, including localization, communication, an…