Energy Minimization for Participatory Federated Learning in IoT Analyzed via Game Theory

no code implementations • 27 Mar 2025 • Alessandro Buratto, Elia Guerra, Marco Miozzo, Paolo Dini, Leonardo Badia

We investigate the simultaneous implementation of both, through a distributed approach based on empowering local nodes with game theoretic decision making.

Decision Making Federated Learning

SAGE: Semantic-Driven Adaptive Gaussian Splatting in Extended Reality

no code implementations • 20 Mar 2025 • Chiara Schiavo, Elena Camuffo, Leonardo Badia, Simone Milani

3D Gaussian Splatting (3DGS) has significantly improved the efficiency and realism of three-dimensional scene visualization in several applications, ranging from robotics to eXtended Reality (XR).

3DGS Semantic Segmentation

Downlink Clustering-Based Scheduling of IRS-Assisted Communications With Reconfiguration Constraints

no code implementations • 23 May 2023 • Alberto Rech, Matteo Pagin, Leonardo Badia, Stefano Tomasin, Marco Giordani, Jonathan Gambini, Michele Zorzi

Intelligent reflecting surfaces (IRSs) are being widely investigated as a potential low-cost and energy-efficient alternative to active relays for improving coverage in next-generation cellular networks.

Clustering Quantization +1

Downlink TDMA Scheduling for IRS-aided Communications with Block-Static Constraints

no code implementations • 25 Jan 2023 • Alberto Rech, Matteo Pagin, Stefano Tomasin, Federico Moretto, Leonardo Badia, Marco Giordani, Jonathan Gambini, Michele Zorzi

In the literature, these surfaces are often studied by idealizing their characteristics.

Scheduling

Game-Theoretic Mode Scheduling for Dynamic TDD in 5G Systems

no code implementations • 26 Apr 2021 • Chandan Kumar Sheemar, Leonardo Badia, Stefano Tomasin

We propose a low-complexity and decentralized solution, where power allocation and scheduling are decoupled.

Scheduling