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.

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.

PREREQUISITES

This course does not require any prerequisites,

TEACHING METHODS

Lessons in presence and from remote on Teams channel communicated using aulaweb.

Interactive lessons including questions from students and answers on basic concepts introduced

Introductory labs on matlab to see implementation of basic concepts 

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

1. Course material on Aulaweb: copy of all lecture slides
2. A. B. Carlson, P. B. Crilly, Communications Systems (5th Edition), McGraw-Hill Education, 2009
3. J. F. Kurose, K. W. Ross, Computer Networking: A Top-Down Approach, 6th Edition, MacGraw-Hill, 2013.
4. 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

LESSONS

LESSONS START

https://easyacademy.unige.it/portalestudenti/index.php?view=easycourse&form-type=corso&include=corso&txtcurr=1+-+SMART+AND+SECURE+INTERNET%2C1+-+SPACE+AND+MULTIMEDIA&anno=2025&scuola=ScuolaPolitecnica&corso=11962&anno2%5B%5D=1%7C1&anno2%5B%5D=2%7C1&date=18-09-2025&periodo_didattico=&_lang=it&list=&week_grid_type=-1&ar_codes_=&ar_select_=&col_cells=0&empty_box=0&only_grid=0&highlighted_date=0&all_events=0&faculty_group=0#

The timetable for this course is available here:https://easyacademy.unige.it/portalestudenti/index.php?view=easycourse&_lang=en

Class schedule

The timetable for this course is available here: EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam consists of a written test and an oral test. Written tests consist of solving problems related to concepts discussed at lesson. It can include using Matlab tools introduced in the lab. Oral exam looks at validating the understanding of same concepts by interactive discussion with the examiner.The marks of the written and oral tests are considered both for the determination of the final grade, according to a non-mathematical criterion that holds account of the overall evaluation of the candidate.It will be necessary to pass both part of the exam toobtain the final grade. 

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 written exam is aimed to evaluate the problem solving skills of the students. The oral exam is aimed to evaluate the understanding of the theory.

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…).