Nicola Piovesan

Giovanni Geraci

CoRR, 2024

Hermes: A Large Language Model Framework on the Journey to Autonomous Networks.

[BibT_eX]

[DOI]

CoRR, 2024

Optimal SSB Beam Planning and UAV Cell Selection for 5G Connectivity on Aerial Highways.

[BibT_eX]

[DOI]

CoRR, 2024

Modelling the 5G Energy Consumption using Real-world Data: Energy Fingerprint is All You Need.

[BibT_eX]

[DOI]

CoRR, 2024

Telco-RAG: Navigating the Challenges of Retrieval-Augmented Language Models for Telecommunications.

[BibT_eX]

[DOI]

Andrei-Laurentiu Bornea

CoRR, 2024

Data-driven Energy Efficiency Modelling in Large-scale Networks: An Expert Knowledge and ML-based Approach.

[BibT_eX]

[DOI]

CoRR, 2024

High Altitude Platform Stations: the New Network Energy Efficiency Enabler in the 6G Era.

[BibT_eX]

[DOI]

Proceedings of the IEEE Wireless Communications and Networking Conference, 2024

Telecom Language Models: Must They Be Large?

[BibT_eX]

[DOI]

Antonio De Domenico

Fadhel Ayed

Proceedings of the 35th IEEE International Symposium on Personal, 2024

Linguistic Intelligence in Large Language Models for Telecommunications.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications Workshops, 2024

2023

Rate, Power, and Energy Efficiency Trade-Offs in Massive MIMO Systems With Carrier Aggregation.

[BibT_eX]

[DOI]

IEEE Trans. Green Commun. Netw., September, 2023

Modeling User Transfer During Dynamic Carrier Shutdown in Green 5G Networks.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., August, 2023

FlexTrain: A Dynamic Training Framework for Heterogeneous Devices Environments.

[BibT_eX]

[DOI]

CoRR, 2023

TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge.

[BibT_eX]

[DOI]

CoRR, 2023

Energy efficient cell-free massive MIMO on 5G deployments: sleep modes strategies and user stream management.

[BibT_eX]

[DOI]

CoRR, 2023

Sleep Mode Strategies for Energy Efficient Cell-Free Massive MIMO in 5G Deployments.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

Power Consumption Modeling of 5G Multi-Carrier Base Stations: A Machine Learning Approach.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

A Novel Metric for mMIMO Base Station Association for Aerial Highway Systems.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

2022

A Survey on 5G Radio Access Network Energy Efficiency: Massive MIMO, Lean Carrier Design, Sleep Modes, and Machine Learning.

[BibT_eX]

[DOI]

IEEE Commun. Surv. Tutorials, 2022

Machine Learning and Analytical Power Consumption Models for 5G Base Stations.

[BibT_eX]

[DOI]

IEEE Commun. Mag., 2022

Carrier Aggregation for Improved Rate versus Power trade-off in Massive MIMO Systems.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2022

2021

Deep Reinforcement Learning for Autonomous Mobile Networks in Micro-grids.

[BibT_eX]

[DOI]

Dagnachew Azene Temesgene

Proceedings of the Deep Learning for Unmanned Systems, 2021

Joint Load Control and Energy Sharing for Renewable Powered Small Base Stations: A Machine Learning Approach.

[BibT_eX]

[DOI]

IEEE Trans. Green Commun. Netw., 2021

A Survey on 5G Energy Efficiency: Massive MIMO, Lean Carrier Design, Sleep Modes, and Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Forecasting Mobile Traffic to Achieve Greener 5G Networks: When Machine Learning is Key.

[BibT_eX]

[DOI]

Proceedings of the 22nd IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2021

Mobile Traffic Forecasting for Green 5G Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2021

Energy Efficiency of Multi-Carrier Massive MIMO Networks: Massive MIMO Meets Carrier Aggregation.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2021

2020

Network resource allocation policies with energy transfer capabilities.

[BibT_eX]

[DOI]

PhD thesis, 2020

Coordinated Load Control of Renewable Powered Small Base Stations Through Layered Learning.

[BibT_eX]

[DOI]

IEEE Trans. Green Commun. Netw., 2020

Modeling the Environment in Deep Reinforcement Learning: The Case of Energy Harvesting Base Stations.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Joint Load Control and Energy Sharing for Autonomous Operation of 5G Mobile Networks in Micro-Grids.

[BibT_eX]

[DOI]

Dagnachew Azene Temesgene

IEEE Access, 2019

2018

Cooperative Localization in WSNs: A Hybrid Convex/Nonconvex Solution.

[BibT_eX]

[DOI]

Tomaso Erseghe

IEEE Trans. Signal Inf. Process. over Networks, 2018

Optimal direct load control of renewable powered small cells: A shortest path approach.

[BibT_eX]

[DOI]

Internet Technol. Lett., 2018

Energy sustainable paradigms and methods for future mobile networks: A survey.

[BibT_eX]

[DOI]

Ángel Fernández Gambín

Michele Rossi

Comput. Commun., 2018

Optimal direct load control of renewable powered small cells: Performance evaluation and bounds.

[BibT_eX]

[DOI]

Dagnachew Azene Temesgene

Proceedings of the 2018 IEEE Wireless Communications and Networking Conference, 2018

Optimal Placement of Baseband Functions for Energy Harvesting Virtual Small Cells.

[BibT_eX]

[DOI]

Proceedings of the 88th IEEE Vehicular Technology Conference, 2018

Unsupervised Learning of Representations from Solar Energy Data.

[BibT_eX]

[DOI]

Proceedings of the 29th IEEE Annual International Symposium on Personal, 2018

2016

Data Analytics for Smart Parking Applications.

[BibT_eX]

[DOI]

Sensors, 2016

Cooperative Localization in WSNs: a Hybrid Convex/non-Convex Solution.

[BibT_eX]

[DOI]