- Docente: Anna Guerra
- Credits: 3
- SSD: IINF-03/A
- Language: Italian
- Teaching Mode: In-person learning (entirely or partially)
- Campus: Cesena
- Corso: Second cycle degree programme (LM) in Electronics and Information Engineering (cod. 6715)
Learning outcomes
The course focuses on the design and simulation of information processing and communication systems using numerical computation tools. Following an introduction to simulation methodologies, students develop models and algorithms for detection, estimation, and localization problems, with particular emphasis on performance evaluation through Monte Carlo simulations and on the fundamental theoretical performance bounds.
Course contents
The course focuses on the design and simulation of information processing and communication systems using numerical computation tools. Following an introduction to simulation methodologies, students develop models and algorithms for detection, estimation, and localization problems, with particular emphasis on performance evaluation through Monte Carlo simulations and on the fundamental theoretical performance bounds.
The main topics covered include:
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simulation methodologies for telecommunication systems and statistical analysis of simulation results;
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detection and estimation algorithms, optimal decision criteria, and theoretical performance bounds;
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localization and navigation systems, position estimation techniques, and accuracy assessment;
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tracking algorithms for dynamic systems based on Kalman filters and particle filtering methods;
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multi-antenna systems, beamforming techniques, diversity combining, and direction-of-arrival (DoA) estimation;
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modeling and simulation of wireless communication systems, with particular emphasis on fading channels, equalization techniques, OFDM systems, and communication system performance evaluation.
The laboratory activities involve the implementation and simulation of the algorithms presented during the course, performance analysis using numerical tools, and the comparison of alternative design solutions in realistic application scenarios.
Readings/Bibliography
Main References
- S. M. Kay, Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory, Prentice Hall.
- S. M. Kay, Fundamentals of Statistical Signal Processing, Volume II: Detection Theory, Prentice Hall.
- H. L. Van Trees, Detection, Estimation, and Time Series Analysis, Wiley.
- A. Goldsmith, Wireless Communications, Cambridge University Press.
- D. Tse and P. Viswanath, Fundamentals of Wireless Communication, Cambridge University Press.
Supplementary Material
- Lecture notes and slides provided by the instructor.
- Scientific papers and additional teaching material distributed during the course.
Teaching methods
The course consists of lectures and laboratory sessions.
The lectures introduce the theoretical models and design methodologies, while the laboratory sessions focus on the implementation and simulation of the algorithms using MATLAB. Particular emphasis is placed on the critical analysis of the obtained results, the comparison of alternative design solutions, and the performance evaluation of the simulated systems.
Assessment methods
The assessment consists of an oral examination and the submission of the laboratory assignments completed during the course.
The laboratory assignments require the implementation and simulation of the algorithms presented in the lectures and laboratory sessions, as well as the analysis and critical discussion of the obtained results.
The oral examination is intended to assess the students' understanding of the theoretical concepts, their ability to justify the design choices made in the laboratory assignments, and their mastery of the simulation and analysis methodologies covered in the course.
Students with specific learning disabilities (SLD) or temporary or permanent disabilities are encouraged to contact the University's dedicated support office well in advance (https://site.unibo.it/studenti-con-disabilita-e-dsa/it ). The office will propose any appropriate accommodations, which must be submitted to the course instructor for approval at least 15 days before the examination. The instructor will evaluate the proposed accommodations in relation to the intended learning outcomes of the course.
Teaching tools
Office hours
See the website of Anna Guerra