| KEYWORD |
Machine Learning for 5G/6G
keywords 5G, 6G NETWORKS, SIMULATION, ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, MACHINE LEARNING, DEEP LEARNING, OPTIMIZATION
Reference persons CARLA FABIANA CHIASSERINI
Research Groups Telecommunication Networks Group
Thesis type EXPERIMENTAL - DESIGN
Description A new trend is emerging in 5G/6G communication networks, aiming at developing new solutions for the support of mobile services that leverage Machine Learning. In particular, the policies and strategies to apply will be the result of a decision-making process performed through Machine Learning (ML) models. By adopting an ML (Deep Neural Network - DNN) model provided by NVIDIA, the goal of the thesis work is to assess the DNN performance in terms of decision quality and energy efficiency. The ultimate objective is indeed to make ML for 5G/6G sustainable.
Required skills Good Python programming skills
Deadline 08/03/2024
PROPONI LA TUA CANDIDATURA