Lorenzo Mario Amorosa

According to our database, Lorenzo Mario Amorosa authored at least 17 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Goal-Oriented Learning at the Edge: Graph Neural Networks Over-the-Air for Blockage Prediction.

Lorenzo Mario Amorosa, Zhan Gao, Tony Chahoud, Yiqun Wu, Lukas Eller, Marco Skocaj, Roberto Verdone

CoRR, March, 2026

V2N-Based Algorithm and Communication Protocol for Autonomous Non-Stop Intersections.

Lorenzo Farina, Lorenzo Mario Amorosa, Marco Rapelli, Barbara Mavi Masini, Claudio Casetti, Alessandro Bazzi

CoRR, March, 2026

Multi-Agent Meta-Advisor for UAV Fleet Trajectory Design in Vehicular Networks.

Leonardo Spampinato, Lorenzo Mario Amorosa, Enrico Testi, Chiara Buratti, Riccardo Marini

CoRR, February, 2026

2025

Learning a Decentralized Medium Access Control Protocol for Shared Message Transmission.

Lorenzo Mario Amorosa, Zhan Gao, Roberto Verdone, Petar Popovski, Deniz Gündüz

CoRR, November, 2025

Improving Outdoor Multi-cell Fingerprinting-based Positioning via Mobile Data Augmentation.

Tony Chahoud, Lorenzo Mario Amorosa, Riccardo Marini, Luca De Nardis

CoRR, September, 2025

Reconstruction of Sparse Urban Wireless Signals via Group Equivariant Non-Expansive Operators.

Lorenzo Mario Amorosa, Francesco Conti, Nicola Quercioli, Flavio Zabini, Tayebeh Lotfi Mahyari, Yiqun Ge, Patrizio Frosini

CoRR, July, 2025

5G Architectures Enabling Remaining Useful Life Estimation for Industrial IoT: A Holistic Study.

Nicolò Longhi, Lorenzo Mario Amorosa, Sara Cavallero, Enrico Buracchini, Roberto Verdone

IEEE Open J. Commun. Soc., 2025

Robust Physical-Layer Key Generation Using UWB in Industrial IoT: A Measurement-Based Analysis.

Lorenzo Mario Amorosa, Stefano Caputo, Lorenzo Mucchi, Gianni Pasolini

J. Sens. Actuator Networks, 2025

Path Selection Based on Network Service Quality for Infrastructure-Assisted Automated Driving.

Andrea Giovannini, Claudia Campolo, Vittorio Todisco, Antonella Molinaro, Lorenzo Mario Amorosa, Lu Lei, Alessandro Bazzi

Proceedings of the 2025 IEEE Wireless Communications and Networking Conference (WCNC), 2025

Efficient Dynamic Beamforming Activation for UAV-Enabled Vehicular Networks.

Leonardo Spampinato, Lorenzo Mario Amorosa, Marco Skocaj, Greta Vallero, Daniela Renga, Chiara Buratti

Proceedings of the 36th IEEE International Symposium on Personal, 2025

Distributed Beamforming with Incomplete Channel State Information in MISO Networks via GNNs.

Lorenzo Mario Amorosa, Tony Chahoud, Zhan Gao, Roberto Verdone, Deniz Gündüz

Proceedings of the 36th IEEE International Symposium on Personal, 2025

Goal-Oriented Uplink Scheduling Requests in Wireless Networks via Graph Neural Networks.

Lorenzo Mario Amorosa, Leonardo Spampinato, Chiara Buratti, Roberto Verdone

Proceedings of the 21st IEEE International Conference on Smart Technologies, 2025

On the Predictability of the Best V2X Path for Infrastructure-Assisted Automated Driving.

Andrea Giovannini, Claudia Campolo, Vittorio Todisco, Antonella Molinaro, Lorenzo Mario Amorosa, Lu Lei, Alessandro Bazzi

Proceedings of the IEEE Conference on Standards for Communications and Networking, 2025

2024

GUMBLE: Uncertainty-Aware Conditional Mobile Data Generation Using Bayesian Learning.

Marco Skocaj, Lorenzo Mario Amorosa, Michele Lombardi, Roberto Verdone

IEEE Trans. Mob. Comput., December, 2024

Multi-Agent Reinforcement Learning for Power Control in Wireless Networks via Adaptive Graphs.

Lorenzo Mario Amorosa, Marco Skocaj, Roberto Verdone, Deniz Gündüz

Proceedings of the IEEE International Conference on Communications, 2024

2023

An End-To-End Analysis of Deep Learning-Based Remaining Useful Life Algorithms for Satefy-Critical 5G-Enabled IIoT Networks.

Lorenzo Mario Amorosa, Nicolò Longhi, Giampaolo Cuozzo, Weronika Maria Bachan, Valerio Lieti, Enrico Buracchini, Roberto Verdone

Proceedings of the 34th IEEE Annual International Symposium on Personal, 2023

2022

Cellular Network Capacity and Coverage Enhancement with MDT Data and Deep Reinforcement Learning.

Marco Skocaj, Lorenzo Mario Amorosa, Giorgio Ghinamo, Giuliano Muratore, Davide Micheli, Flavio Zabini, Roberto Verdone

Comput. Commun., 2022