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

Enabling Simulation-Based Optimization Through Machine Learning: A Case Study on Antenna Design

no code implementations • 29 Aug 2019 • Paolo Testolina, Mattia Lecci, Mattia Rebato, Alberto Testolin, Jonathan Gambini, Roberto Flamini, Christian Mazzucco, Michele Zorzi

Therefore, it is possible to perform a global numerical optimization over the vast multi-dimensional parameter space, in a fraction of the time that would be required by a simple brute-force search.

BIG-bench Machine Learning