24 citations · 27 across the 12 of their papers we have counts for
12 papers
Indirect Estimation of SINR via SSB and CSI-RS RSRP in 5G NR
Leonardo Spampinato, Mahamadou Togola, Matteo Bernabè +3
Predicting user equipment (UE) performance is essential for proactive network control, resource management, and digital twin sandboxes. However, the inherent flexibility and comple…
Decentralized Multi-Agent Urban Traffic Management via Spatio-Temporal Mobility Profile Planning
Lorenzo Mario Amorosa, Lorenzo Farina, Vittorio Todisco +1
As modern cities face increasingly severe traffic congestion, connected and autonomous vehicles (CAVs) have emerged as a crucial enabling technology for next-generation intelligent…
Proactive URLLC Adaptation for Connected Vehicles Through ML-Based Channel Prediction
Andrea Giovannini, Lorenzo Mario Amorosa, Vittorio Todisco +4
Connected and automated vehicles (CAVs) are expected to increasingly rely on 5G and future 6G ultra-reliable and low-latency communication (URLLC) services to support safety-critic…
Goal-Oriented Learning at the Edge: Graph Neural Networks Over-the-Air for Blockage Prediction
Lorenzo Mario Amorosa, Zhan Gao, Tony Chahoud +4
Sixth-generation (6G) wireless networks evolve from connecting devices to connecting intelligence. The focus turns to Goal-Oriented Communications, where the effectiveness of commu…
V2N-Based Algorithm and Communication Protocol for Autonomous Non-Stop Intersections
Lorenzo Farina, Lorenzo Mario Amorosa, Marco Rapelli +3
Intersections are critical areas for road safety and traffic efficiency, accounting for a significant portion of vehicle crashes and fatalities. While connected and autonomous vehi…
Multi-Agent Meta-Advisor for UAV Fleet Trajectory Design in Vehicular Networks
Leonardo Spampinato, Lorenzo Mario Amorosa, Enrico Testi +2
Future vehicular networks require continuous connectivity to serve highly mobile users in urban environments. To mitigate the coverage limitations of fixed terrestrial macro base s…