Search Results for author: Mattia Rebato

Found 4 papers, 1 papers with code

Uplink Beam Management for Millimeter Wave Cellular MIMO Systems with Hybrid Beamforming

no code implementations18 Jan 2021 George C. Alexandropoulos, Ioanna Vinieratou, Mattia Rebato, Luca Rose, Michele Zorzi

Hybrid analog and digital BeamForming (HBF) is one of the enabling transceiver technologies for millimeter Wave (mmWave) Multiple Input Multiple Output (MIMO) systems.

Information Theory Information Theory

Machine Learning-aided Design of Thinned Antenna Arrays for Optimized Network Level Performance

no code implementations25 Jan 2020 Mattia Lecci, Paolo Testolina, Mattia Rebato, Alberto Testolin, Michele Zorzi

With the advent of millimeter wave (mmWave) communications, the combination of a detailed 5G network simulator with an accurate antenna radiation model is required to analyze the realistic performance of complex cellular scenarios.

BIG-bench Machine Learning

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

no code implementations29 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

Multi-Sector and Multi-Panel Performance in 5G mmWave Cellular Networks

6 code implementations14 Aug 2018 Mattia Rebato, Michele Polese, Michele Zorzi

The next generation of cellular networks (5G) will exploit the mmWave spectrum to increase the available capacity.

Networking and Internet Architecture Information Theory Information Theory

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