Alessio FASCISTA

Alessio FASCISTA

Ricercatore Universitario

Dipartimento di Ingegneria dell'Innovazione

Centro Ecotekne Pal. O - S.P. 6, Lecce - Monteroni - LECCE (LE)

Ufficio, Piano terra

Area di competenza:

Settore Scientifico Disciplinare ING-INF/03 - Telecomunicazioni

Curriculum Vitae

Alessio Fascista received the Ph.D. degree in Engineering of Complex Systems (summa cum laude) from the University of Salento (Lecce, Italy) in 2019. He is currently an Assistant Professor of Telecommunications at the Department of Innovation Engineering, University of Salento. He has held a visiting position at the Department of Telecommunications and Systems Engineering of the Universitat Autonoma de Barcelona (UAB, Spain) in 2018, and at the Department of Electrical Engineering of the Chalmers University of Technology (Gothenburg, Sweden) in 2022. His main research interests are in the field of telecommunications with focus on statistical signal processing for detection, estimation, and localization in terrestrial wireless systems. Relevant application fields are wireless networks (including 5G and beyond), radars, and emerging network contexts (including intelligent cyber-physical systems, smart devices, and environmental monitoring systems). He is the recipient of the 2021 IEEE Intelligent Transportation Systems Society (ITSS, Italy Chapter) best Ph.D. dissertation award for the thesis: "Cooperative Positioning based on Array Processing and Information Fusion". He is Member of IEEE and serves as an Associate Editor for the IEEE Open Journal of the Communications Society (OJ-COMS).

Didattica

A.A. 2022/2023

LABORATORY OF WIRELESS COMMUNICATIONS AND RADAR

Degree course COMMUNICATION ENGINEERING AND ELECTRONIC TECHNOLOGIES

Course type Laurea Magistrale

Language INGLESE

Credits 6.0

Owner professor ALESSIO FASCISTA

Teaching hours Ore totali di attività frontale: 54.0

  Ore erogate dal docente ALESSIO FASCISTA: 27.0

Year taught 2022/2023

For matriculated on 2021/2022

Course year 2

Structure DIPARTIMENTO DI INGEGNERIA DELL'INNOVAZIONE

Subject matter Telecom Applications

Location Lecce

SEGNALI E SISTEMI

Corso di laurea INGEGNERIA DELL'INFORMAZIONE

Tipo corso di studio Laurea

Lingua ITALIANO

Crediti 9.0

Docente titolare Giuseppe RICCI

Ripartizione oraria Ore totali di attività frontale: 81.0

  Ore erogate dal docente ALESSIO FASCISTA: 27.0

Anno accademico di erogazione 2022/2023

Per immatricolati nel 2021/2022

Anno di corso 2

Struttura DIPARTIMENTO DI INGEGNERIA DELL'INNOVAZIONE

Percorso PERCORSO COMUNE

Sede Lecce

Torna all'elenco
LABORATORY OF WIRELESS COMMUNICATIONS AND RADAR

Degree course COMMUNICATION ENGINEERING AND ELECTRONIC TECHNOLOGIES

Subject area ING-INF/03

Course type Laurea Magistrale

Credits 6.0

Owner professor ALESSIO FASCISTA

Teaching hours Ore totali di attività frontale: 54.0

  Ore erogate dal docente ALESSIO FASCISTA: 27.0

For matriculated on 2021/2022

Year taught 2022/2023

Course year 2

Semestre Secondo Semestre (dal 01/03/2023 al 09/06/2023)

Language INGLESE

Subject matter Telecom Applications (A181)

Location Lecce

Prerequisites: statistical signal processing and learning, digital communications.

General Background:

 

- A brief introduction to Matlab programming.

                                                                     

Wireless Communications Module:

 

- Introduction to modeling and simulation of wireless communication systems.

 

List of potential laboratory experiences:

 

- Lab Experience #1: Simulation and Analysis of 5G Wireless Communication Systems

  1. Transmitted signal generation (single-carrier and multi-carrier technologies);
  2. Multiple-input multiple-output (MIMO) and Multiple-input single-output (MISO) radio channel modeling;
  3. Downlink and Uplink mmWave communications;
  4. Channel Estimation (LOS and NLOS) and Performance Analysis.

 

- Lab Experience #2: Use of Software-Defined-Radio (SDR) Platforms

  1. Signals acquisition and analysis using SDRAngel and RTL-SDR;
  2. Implementation of algorithms for spectrum sensing (energy detector vs machine learning);
  3. Other applications/examples with SDRAngel and RTL-SDR;
  4. Airplane Tracking using aviation signals ADS-B and RTL-SDR.

 

- Lab Experience #3: Prototype of a Real Wi-Fi Communication System using ESP-32 Development Boards

  1. Setup and configuration of the experimental testbed;
  2. Real-time data acquisition;
  3. Analysis and processing of Wi-Fi Channel State Information (CSI).

 

Radar Module:

 

- Review of pulsed radars and brief introduction to continuous wave (CW) and frequency-modulated CW (FMCW) radars.

 

List of potential laboratory experiences:

 

- Lab Experience #1: CFAR Radar Detection using Matlab

  1. CFAR detection techniques: motivation and basic strategies;
  2. Coherent and Incoherent detection;
  3. Implementation of different CFAR detection schemes: cell averaging (CA) CFAR, greatest of (GO) CFAR and smallest of (SO) CFAR, censored CA-CFAR, and ordered statistic (OS);
  4. Analysis under ideal and non-ideal conditions (clutter edges and multiple targets).

 

- Lab Experience #2: Target Detection using Real Radar Data

  1. Statistical analysis and processing of real radar data;
  2. Estimation of the power spectral density and model fitting;
  3. Design and implementation of detection algorithms to reveal the presence of targets embedded in real clutter.

 

- Lab Experience #3: CW and FMCW Radars

  1. Design of algorithms for target detection and parameter(s) estimation;
  2. Performance analysis based on synthetic and real data.

Overview.

This laboratory course offers to students the possibility to deepen and put in practice the knowledge on the design and analysis of wireless communication systems and radars. The lab sessions will be preceded by lectures to describe the experiments that will be performed and the procedure to implement them. 

Learning Outcomes.

Knowledge and understanding

After the course the student should know the tools necessary 1) to fit a statistical model to data and 2) to design algorithms to retrieve information chosen according to the adopted model.

Applying knowledge and understanding

After the course the student should be able to

*fit a statistical model to data in terms of first order distribution and autocorrelation function;

*solve detection and estimation problems for the selected applications.

*Evaluate the performance parameters and discuss complexity issues associated with different solutions.

Making judgements

Students should acquire the ability to compare pros and cons of different approaches to the solution of a specific problem (laboratory experiences).

Communication

The ability to communicate on technical topics should be acquired by reporting on laboratory experiences.

Learning skills

Laboratory experiences will require elaborating on techniques introduced in previous courses, also with the help of selected readings suggested by the instructor. Identifying solutions to non trivial problems will be  important to be ready for autonomous lifelong learning.

Lectures and computer/experimental projects. Most of the activity is performed in the laboratory, where students can setup experiments regarding radar signal processing and wireless transmissions in Matlab and/or using Software Defined Radio (SDR) platforms. To attend the course, the student is NOT required to have knowledge of these tools in advance.

The exam will be composed of an oral part (30%) and a practical part (70%), where some modifications to the software and experiments developed during the course will be required; the objective of the practical part is not to focus on programming skills, but to verify the knowledge level of the discussed topics.

By appointment; contact the instructor by email or at the end of class meetings.

1) Handouts (in progress).

2) M. C. Jeruchim, P. Balaban, K. S. Shanmugan, "Simulation of Communication Systems," Plenum Press, 1992.

3) R. B. D'Agostino and M. A. Stephens, "Goodness of Fit Techniques," Marcel Dekker, 1986.

4) J. Proakis: "Digital Communications", McGraw Hill, 2000.

5) D. Tse and P. Viswanath: "Fundamentals of Wireless Communication" Cambridge University Press, 2005.

6) R. W. Stewart, K. W. Barlee, D. S. Atkinson, and L. H. Crockett: "Software defined radio using MATLAB & Simulink and the RTL-SDR", University of Strathclyde Engineering (free ebook), 2015.

LABORATORY OF WIRELESS COMMUNICATIONS AND RADAR (ING-INF/03)
SEGNALI E SISTEMI

Corso di laurea INGEGNERIA DELL'INFORMAZIONE

Settore Scientifico Disciplinare ING-INF/03

Tipo corso di studio Laurea

Crediti 9.0

Docente titolare Giuseppe RICCI

Ripartizione oraria Ore totali di attività frontale: 81.0

  Ore erogate dal docente ALESSIO FASCISTA: 27.0

Per immatricolati nel 2021/2022

Anno accademico di erogazione 2022/2023

Anno di corso 2

Semestre Secondo Semestre (dal 01/03/2023 al 09/06/2023)

Lingua ITALIANO

Percorso PERCORSO COMUNE (999)

Sede Lecce

Si faccia riferimento alla parte generale (pagina personale del Prof. Giuseppe Ricci).

Si faccia riferimento alla parte generale (pagina personale del Prof. Giuseppe Ricci).

Si faccia riferimento alla parte generale (pagina personale del Prof. Giuseppe Ricci).

Lezione frontale, esercitazioni, attività al calcolatore.

Si faccia riferimento alla parte generale (pagina personale del Prof. Giuseppe Ricci).

Si faccia riferimento alla parte generale (pagina personale del Prof. Giuseppe Ricci).

SEGNALI E SISTEMI (ING-INF/03)