Goal-Oriented and Semantic Communication in 6G AI-Native Networks: The 6G-GOALS Approach

no code implementations • 12 Feb 2024 • Emilio Calvanese Strinati, Paolo Di Lorenzo, Vincenzo Sciancalepore, Adnan Aijaz, Marios Kountouris, Deniz Gündüz, Petar Popovski, Mohamed Sana, Photios A. Stavrou, Beatriz Soret, Nicola Cordeschi, Simone Scardapane, Mattia Merluzzi, Lanfranco Zanzi, Mauro Boldi Renato, Tony Quek, Nicola di Pietro, Olivier Forceville, Francesca Costanzo, Peizheng Li

Recent advances in AI technologies have notably expanded device intelligence, fostering federation and cooperation among distributed AI agents.

Transferable and Distributed User Association Policies for 5G and Beyond Networks

no code implementations • 4 Jun 2021 • Mohamed Sana, Nicola di Pietro, Emilio Calvanese Strinati

We study the problem of user association, namely finding the optimal assignment of user equipment to base stations to achieve a targeted network performance.

Management Multi-agent Reinforcement Learning +1

Energy Efficient Edge Computing: When Lyapunov Meets Distributed Reinforcement Learning

no code implementations • 31 Mar 2021 • Mohamed Sana, Mattia Merluzzi, Nicola di Pietro, Emilio Calvanese Strinati

Then, based on Lyapunov stochastic optimization tools, we decouple the formulated problem into a CPU scheduling problem and a radio resource allocation problem to be solved in a per-slot basis.

Edge-computing Multi-agent Reinforcement Learning +4

Discontinuous Computation Offloading for Energy-Efficient Mobile Edge Computing

no code implementations • 8 Aug 2020 • Mattia Merluzzi, Nicola di Pietro, Paolo Di Lorenzo, Emilio Calvanese Strinati, Sergio Barbarossa

We propose a novel strategy for energy-efficient dynamic computation offloading, in the context of edge-computing-aided beyond 5G networks.

Edge-computing Stochastic Optimization