no code implementations • 14 Sep 2022 • Reza Aghazadeh Ayoubi, Dario Tagliaferri, Filippo Morandi, Luca Rinaldi, Laura Resteghini, Christian Mazzucco, Umberto Spagnolini
The surging capacity demands of 5G networks and the limited coverage distance of high frequencies like millimeter wave (mmW) and sub-terahertz (THz) bands have led to consider the upper 6GHz (U6G) spectrum for radio access.
no code implementations • 3 Apr 2022 • Francesco Linsalata, Dario Tagliaferri, Luca Rinaldi, Lorenzo Bezzetto, Marouan Mizmizi, Davide Scazzoli, Damiano Badini, Christian Mazzucco, Maurizio Magarini, Umberto Spagnolini
Moreover, there is not a winning technology for BM between BS-mounted radar and VE's onboard positioning systems.
no code implementations • 25 Jan 2022 • Marco Manzoni, Dario Tagliaferri, Marco Rizzi, Stefano Tebaldini, Andrea Virgilio Monti-Guarnieri, Claudio Maria Prati, Monica Nicoli, Ivan Russo, Sergi Duque, Christian Mazzucco, Umberto Spagnolini
With the advent of self-driving vehicles, autonomous driving systems will have to rely on a vast number of heterogeneous sensors to perform dynamic perception of the surrounding environment.
no code implementations • 28 Oct 2021 • Marco Manzoni, Marco Rizzi, Stefano Tebaldini, Andrea Virgilio Monti-Guarnieri, Claudio Maria Prati, Dario Tagliaferri, Monica Nicoli, Ivan Russo, Christian Mazzucco, Sergi Duque Biarge, Umberto Spagnolini
This paper deals with the analysis, estimation, and compensation of trajectory errors in automotive-based Synthetic Aperture Radar (SAR) systems.
no code implementations • 28 Oct 2021 • Marco Rizzi, Marco Manzoni, Stefano Tebaldini, Andrea Virgilio Monti-Guarnieri, Claudio Maria Prati, Dario Tagliaferri, Monica Nicoli, Ivan Russo, Christian Mazzucco, Simón Tejero Alfageme, Umberto Spagnolini
Automotive synthetic aperture radar (SAR) systems are rapidly emerging as a candidate technological solution to enable a high-resolution environment mapping for autonomous driving.
no code implementations • 31 Aug 2021 • Lorenzo Cazzella, Dario Tagliaferri, Marouan Mizmizi, Damiano Badini, Christian Mazzucco, Matteo Matteucci, Umberto Spagnolini
Algebraic Low-rank (LR) channel estimation exploits space-time channel sparsity through the computation of position-dependent MIMO channel eigenmodes leveraging recurrent training vehicle passages in the coverage cell.
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.