6 papers
On-board AI-based Channel Estimation for LEO NTNs
Mahdi Abdollahpour, Bruno De Filippo, Carla Amatetti +1
Artificial Intelligence(AI) methods have shown strong channel estimation performance in terrestrial networks, but they typically rely on substantial computational resources. As 6G…
DRIFT: Joint Channel Estimation and Prediction Towards Pilotless 6G Non-Terrestrial Networks
Bruno De Filippo, Carla Amatetti, Alessandro Vanelli-Coralli
Non-terrestrial networks (NTNs) are expected to play a pivotal role in sixth-generation (6G) systems by enabling ubiquitous connectivity and massive communication. In this context,…
Attention-Based SINR Estimation in User-Centric Non-Terrestrial Networks
Bruno De Filippo, Alessandro Guidotti, Alessandro Vanelli-Coralli
The signal-to-interference-plus-noise ratio (SINR) is central to performance optimization in user-centric beamforming for satellite-based non-terrestrial networks (NTNs). Its asses…
Faster-Than-Nyquist Equalization with Convolutional Neural Networks
Bruno De Filippo, Carla Amatetti, Alessandro Vanelli-Coralli
Faster-than-Nyquist (FTN) signaling aims at improving the spectral efficiency of wireless communication systems by exceeding the boundaries set by the Nyquist-Shannon sampling theo…
An SCMA Receiver for 6G NTN based on Multi-Task Learning
Bruno De Filippo, Carla Amatetti, Riccardo Campana +2
Future 6G networks are envisioned to enhance the user experience in a multitude of different ways. The unification of existing terrestrial networks with non-terrestrial network (NT…
Uplink OFDM Channel Prediction with Hybrid CNN-LSTM for 6G Non-Terrestrial Networks
Bruno De Filippo, Carla Amatetti, Alessandro Vanelli-Coralli
Wireless communications are typically subject to complex channel dynamics, requiring the transmission of pilot sequences to estimate and equalize such effects and correctly receive…