83 citations · 176 across the 9 of their papers we have counts for
11 papers
Linguistic Intelligence in Large Language Models for Telecommunications
Tasnim Ahmed, Nicola Piovesan, Antonio De Domenico +1
Large Language Models (LLMs) have emerged as a significant advancement in the field of Natural Language Processing (NLP), demonstrating remarkable capabilities in language generati…
FlexTrain: A Dynamic Training Framework for Heterogeneous Devices Environments
Mert Unsal, Ali Maatouk, Antonio De Domenico +2
As deep learning models become increasingly large, they pose significant challenges in heterogeneous devices environments. The size of deep learning models makes it difficult to de…
TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge
Ali Maatouk, Fadhel Ayed, Nicola Piovesan +3
We introduce TeleQnA, the first benchmark dataset designed to evaluate the knowledge of Large Language Models (LLMs) in telecommunications. Comprising 10,000 questions and answers,…
Energy efficient cell-free massive MIMO on 5G deployments: sleep modes strategies and user stream management
F. Riera-Palou, G. Femenias, D. López-Pérez +2
This paper proposes the utilization of cell-free massive MIMO (CF-M-MIMO) processing on top of the regular micro/macrocellular deployments typically found in current 5G networks. T…
A Novel Metric for mMIMO Base Station Association for Aerial Highway Systems
Matteo Bernabè, David López Pérez, Nicola Piovesan +2
In this article, we introduce a new metric for driving the serving cell selection process of a swarm of cellular connected unmanned aerial vehicles (CCUAVs) located on aerial highw…
Power Consumption Modeling of 5G Multi-Carrier Base Stations: A Machine Learning Approach
Nicola Piovesan, David Lopez-Perez, Antonio De Domenico +2
The fifth generation of the Radio Access Network (RAN) has brought new services, technologies, and paradigms with the corresponding societal benefits. However, the energy consumpti…