Francesco Di Stasio

Ph.D. in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 33rd cycle (2017-2020)

Ph.D. obtained in 2021

Dissertation:

Link optimization considerations for 5G and beyond wireless communications (Abstract)

Tutors:

Roberto Garello Marina Mondin

Research presentation:

Video presentation Poster

Profile

Research topic

System level optimization of 5G communication link components at physical layer

Research interests

Antennas, electromagnetic devices, propagation and radars
Communication and Computer Networks

Biography

During the PhD, the research activity has been mainly focused on system level techniques for the next generation of wireless communications, the so called 5G networks. The first topic of the research regards the out-of-band interference rejection in post-OFDM systems, such as Filtered OFDM and Windowed OFDM. Results of this work have been published in the IEEE conference ISNCC 2018. Another research topic regards the beamforming algorithms for antenna array system of various type, such as circular, planar and cylindrical one. Results about this topic has been published for IEEE international workshops CAMAD 2019 and WPMC 2019. The paper presented for WPMC won the conference award as “Best paper”. The core of the research activity has been the study of many channels model for 5G wireless communications (which work in the millimetric-wave range) available in the literature, aiming to realize a full matlab channel simulator, following the 3GPP standardized rules, useful for system and link level simulations in the 5G frequency range which goes from 500 MHz to 100 GHz. More research has been conducted for analysis in cancellation of inter numerology interference, which is a prerequisite for 5G networks. They require to serve many kinds of users with very different quality of service among them.
Furthermore, research has been focused on machine learning algorithms. Firstly, in order to realize an automatic crack detection system using deep neural network for image processing to relieve the presence of cracks in urban tunnels. This work brought a pull paper publication in the international journal Transportation Research Record. Finally, the study has been focused on the applicability of machine learning techniques for wireless communications, especially for automatic modulation detection on the received signal for a user, in scenarios where information about system level modulation are not available.
Finally, the last topic of my research has been about Quantum communications focusing on QKD (Quantum Key Distribution) for transmission of secret encryption keys with very high reliability, in scenarios which is essential to not be intercepted by an eavesdropper.
During the PhD I spent three periods in California State University of Los Angeles (CA, USA) to carry out the research activity in the QKD and Machine learning topics. The research carried out in QKD field brought to many publications in different SPIE proceedings between 2018 and 2019. In these periods I taught in many classes for signal processing and wireless communications.

Publications

Works published during the Ph.D. View all publications in Porto@Iris