activity
20162021
collaborators

11 papers

cs.IT2021

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

George C. Alexandropoulos, Ioanna Vinieratou, Mattia Rebato +2

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

cs.NI2020

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

Mattia Lecci, Paolo Testolina, Mattia Rebato +2

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 r…

cs.IT2019

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

Paolo Testolina, Mattia Lecci, Mattia Rebato +5

Complex phenomena are generally modeled with sophisticated simulators that, depending on their accuracy, can be very demanding in terms of computational resources and simulation ti…

cs.IT2019

Performance Assessment of MIMO Precoding on Realistic mmWave Channels

Mattia Rebato, Luca Rose, Michele Zorzi

In this paper, the performance of multi-user Multiple-Input Multiple-Output (MIMO) systems is evaluated in terms of SINR and capacity. We focus on the case of a downlink single-cel…

cs.NI2018

A Spectrum Sharing Solution for the Efficient Use of mmWave Bands in 5G Cellular Scenarios

Mattia Rebato, Michele Zorzi

Regulators all around the world have started identifying the portions of the spectrum that will be used for the next generation of cellular networks. A band in the mmWave spectrum…

cs.NI2018

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

Mattia Rebato, Michele Polese, Michele Zorzi

The next generation of cellular networks (5G) will exploit the mmWave spectrum to increase the available capacity. Communication at such high frequencies, however, suffers from hig…