11 papers
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,…
Toward Autonomous O-RAN: A Multi-Scale Agentic AI Framework for Real-Time Network Control and Management
Hojjat Navidan, Mohammad Cheraghinia, Jaron Fontaine +5
Open Radio Access Networks (O-RAN) promise flexible 6G network access through disaggregated, software-driven components and open interfaces, but this programmability also increases…
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…
Towards a Wireless Physical-Layer Foundation Model: Challenges and Strategies
Jaron Fontaine, Adnan Shahid, Eli De Poorter
Artificial intelligence (AI) plays an important role in the dynamic landscape of wireless communications, solving challenges unattainable by traditional approaches. This paper disc…
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…