CODE 104631 ACADEMIC YEAR 2026/2027 CREDITS 3 cfu anno 1 INTERNET AND MULTIMEDIA ENGINEERING 11962 (LM-27) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR IINF-03/A LANGUAGE English TEACHING LOCATION GENOVA SEMESTER 1° Semester TEACHING MATERIALS AULAWEB OVERVIEW The class aims at giving the students a review of the basic knowledge about signal theory, random phenomena, analog modulations and digital signal processing. The specific objective is to enhance the initial preparation of the students on basic topics of fundamental relevance for the master course, increasing their opportunity to effectively exploit the advanced content of the other courses. AIMS AND CONTENT LEARNING OUTCOMES The class aims at giving the students a review of the basic knowledge about signal theory, random phenomena, analog modulations, digital signal processing, and telecommunication networks. The specific objective is to enhance the initial preparation of the students on basic topics of fundamental relevance for the master course, increasing their opportunity to effectively exploit the advanced content of the other courses of study. AIMS AND LEARNING OUTCOMES The main goal of the classes is to enhance the initial preparation of the students on basic topics about signal theory, random phenomena, analog modulations, digital signals and digital signal processing. The class involves three parts. The first part is dedicated to the signal theory: characteristics of electric signals, signal classifications, time and frequency domain, linear time invariant system, sampling theory and hints of pulse modulation coding (PCM), pulse amplitude modulation (PAM), multiplexing. The second part introduces and describes the random phenomena, starting with a review of probability concept, following with random variables and random signals theory. The third part is focused on analog modulations, from generic band-pass signal properties to linear (AM - DSB) and angular (PM - FM) modulations, with hints to SSB and VSB. At the end of theteaching unit students must show to have acquired knowledge in such topics so do be capable to use it in the understanding of more complex concepts introduced in the Master course. The should have aqcquired the capability to understand and read mathematical formulas used and to be able to relate concepts in different parts when this is necessary to describe more complex concepts. PREREQUISITES This course does not require any prerequisites, TEACHING METHODS Lessons in presence and with synchronous connection from remote on Teams channel communicated using aulaweb. All lessons will be recorded and made available on a dedicated channel in Teams. A interactive task will be assigned on aulaweb for preparing lessons consisting of a set of quiz for self assessment to be completed by each student before the lesson is presented. Quiz results outcomes will be discussed before lesson. Video recordings will be made available after the lesson on Teams channel communicated in aulaweb page of the course. Quizzes related to the topic of lessons will be made available on aulaweb. A Interactive part of lessons will include questions from students and answers on basic concepts introduced Introductory labs on matlab with same modality will be provided to see implementation of basic concepts . Students with valid certifications for Specific Learning Disorders (SLDs), disabilities or other educational needs are invited to contact the teacher and the School's contact person for disability at the beginning of teaching to agree on possible teaching arrangements that, while respecting the teaching objectives, take into account individual learning patterns. Contacts of the teacher and the School's disability contact person can be found at the following link Comitato di Ateneo per l’inclusione delle studentesse e degli studenti con disabilità o con DSA | UniGe | Università di Genova SYLLABUS/CONTENT Analog electrical signal properties: voltage, current, power, available power of a signal source Fundamentals of transmission line theory Linear time invariant systems: pulse response, convolution, transfer function The Fourier transform: definition and property, bandwidth, energy and power spectrum Hints about memoryless non linear systems Sampling theory, Nyquist theorem, aliasing, reconstruction, real sampling (sample&hold, chopper) Uniform (withy hints about non uniform) quantization Hints of PAM, PCM and multiplexing (TDM, FDM) Probability: definitions, conditioned probability, Bayes theorem, Bernoulli trials, Gauss and Poisson approximations, law of large numbers Random variables: definition and properties (mean, variance), probability distribution and density functions, uniform, Gaussian, Rayleigh random variables, functions of random variables, two random variables properties (joint density and distribution, covariance, correlation), conditioned averages and distributions, central limit theory Random processes: definition and properties, mean, self-correlation, self-covariance, white noise, power spectrum, Wiener Khinchin theorem, superposition and modulation, thermal noise Analog modulations: bandpass to lowpass decomposition, Rice decomposition, linear modulations (AM – DSB, hints of SSB and VSB), angular modulations (PM, FM) RECOMMENDED READING/BIBLIOGRAPHY Course material on Aulaweb: copy of all lecture slides A. B. Carlson, P. B. Crilly, Communications Systems (5th Edition), McGraw-Hill Education, 2009 J. F. Kurose, K. W. Ross, Computer Networking: A Top-Down Approach, 6th Edition, MacGraw-Hill, 2013. Alan V. Oppenheim, Ronald W. Schafer, and John R. Buck. Discrete-Time Signal Processing. Prentice Hall, Upper Saddle River, New Jersey, 1999. TEACHERS AND EXAM BOARD CARLO REGAZZONI Ricevimento: Students can define appointments online or by remote writing e-mail at Carlo.Regazzoni@unige.it or using Aulaweb and Teams LESSONS LESSONS START Lessons in presence will follow timetable described in; https://corsi.unige.it/corsi/10378/studenti-orario The timetable for this course is available also here: https://easyacademy.unige.it/portalestudenti/ Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION The exam consists of oral exam. Oral exam consists on showing the acquired knowledge by means of writing/commenting formulas that describe concepts discussed at lesson by answering to questions. It can include knowledge about using Matlab tools introduced in the lab. Oral exam looks at validating the understanding of concepts by interactive discussion with the examiner. Students with learning disorders ("disturbi specifici di apprendimento", DSA) will be allowed to use specific modalities and supports that will be determined on a case-by-case basis in agreement with the delegate of the Engineering courses in the Committee for the Inclusion of Students with Disabilities. ASSESSMENT METHODS The oral exam is aimed to evaluate the level at which the syudent has understood concepts and is able to relate them each other in order to evaluate problem solving skills of the students. The oral exam aims at evaluating the understanding of the theory and to assess the capability of the student and will consist of questions on a random couple of topics. The student is required to reach a minimum level of knowledge in all asked subsjects to pass exam. Answers are evaluated based on the level of capability to describe main aspects of related concepts, meaning and interpretation of mathematical formulas, as well as time required to answer to questions. Typically an exam can take up to half an hour of time. The exam is on presence and the student cannot use any support tool during exam. FURTHER INFORMATION Students with disabilities or learning disorders can use specific modalities and supports that will be determined on a case-by-case basis in agreement with the Delegate of the Engineering courses in the Committee for the Inclusion of Students with Disabilities. Students are invited to contact the teacher of this course and copy the Delegate (https://unige.it/commissioni/comitatoperlinclusionedeglistudenticondisa…).
