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Alessandro Bazzi

3 papers indexed

arxivcs.NI2026-07-15

Proactive URLLC Adaptation for Connected Vehicles Through ML-Based Channel Prediction

Andrea Giovannini, Lorenzo Mario Amorosa, Vittorio Todisco, Claudia Campolo, Antonella Molinaro, Su Hongjia, et al.

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-critical and time-sensitive applications. Since wireless link conditions can vary rapidly in urban vehicul…

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arxivcs.NI2026-06-29

A Practical Implementation of Day-3 Cooperative Intersection with Automated Connected Mini-Cars

Lorenzo Farina, Vittorio Todisco, Federico Gavioli, Salvatore Iandolo, Francesco Moretti, Giuseppe Perrone, et al.

Cooperative driving enabled by connected and automated vehicles is expected to improve traffic efficiency and safety, particularly at intersections where traditional control mechanisms such as traffic lights introduce delays and unnecessary stops. Although cooperative intersectio…

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crossrefSensors2025-08-21Cited by 4

Dynamic Allocation of C-V2X Communication Resources Based on Graph Attention Network and Deep Reinforcement Learning

Zhijuan Li, Guohong Li, Zhuofei Wu, Wei Zhang, Alessandro Bazzi

Vehicle-to-vehicle (V2V) and vehicle-to-network (V2N) communications are two key components of intelligent transport systems (ITSs) that can share spectrum resources through in-band overlay. V2V communication primarily supports traffic safety, whereas V2N primarily focuses on inf…

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