collaborators

5 papers

eess.SP2025

Exploiting Age of Information in Network Digital Twins for AI-driven Real-Time Link Blockage Detection

Michele Zhu, Francesco Linsalata, Silvia Mura +3

The Line-of-Sight (LoS) identification is crucial to ensure reliable high-frequency communication links, especially those vulnerable to blockages. Network Digital Twins and Artific…

eess.SP2025

AI-empowered Real-Time Line-of-Sight Identification via Network Digital Twins

Michele Zhu, Silvia Mura, Francesco Linsalata +3

The identification of Line-of-Sight (LoS) conditions is critical for ensuring reliable high-frequency communication links, which are particularly vulnerable to blockages and rapid…

eess.SP2025

Low-Complexity CNN-Based Classification of Electroneurographic Signals

Arek Berc Gokdag, Silvia Mura, Antonio Coviello +3

Peripheral nerve interfaces (PNIs) facilitate neural recording and stimulation for treating nerve injuries, but real-time classification of electroneurographic (ENG) signals remain…

cs.IT2025

Semantic Communications via Features Identification

Federico Francesco Luigi Mariani, Michele Zhu, Maurizio Magarini

The development of the new generation of wireless technologies (6G) has led to an increased interest in semantic communication. Thanks also to recent developments in artificial int…

eess.SP2024

Toward Real-Time Digital Twins of EM Environments: Computational Benchmark of Ray Launching Software

Michele Zhu, Lorenzo Cazzella, Francesco Linsalata +3

Digital Twin has emerged as a promising paradigm for accurately representing wireless communication electromagnetic environments. The resulting virtual representation of reality fa…