Fundamentals of Telecommunication

Fundamentals of Telecommunication
3 YEAR2 semester9 CREDITS
Prof. Michele Luglio2019-20
LUGLIO MICHELE 2020-21
2021-22
Code: 8039512
SSD: ING-INF/03

OBJECTIVES

LEARNING OUTCOMES: To provide basic knowledge on deterministic analogic signals, linear time invariant systems, analogic random processes, noise and signal to noise ratio, analogic modulation concepts. To allow practical experience on Matlab.
KNOWLEDGE AND UNDERSTANDING: Obtain capability to apply the acquired knowledge in the field of elementary analogue signal processing to approach and solve problems concerning more complex processing in the field of digital signals. Obtain capabilities to understand problem to approach the job in professional manner.
APPLYING KNOWLEDGE AND UNDERSTANDING: Obtain and demonstrate to understand problems of university degree of complexity both during the class and on books of equivalent level.
MAKING JUDGEMENTS: Acquire the capability to collect and analyse data on the analogue signal processing to carry out and express opinion autonomously and independently.
COMMUNICATION SKILLS: Acquire capability to explain what learnt to both skilled and not skilled people.
LEARNING SKILLS: Acquire such a capability to learn to be able to approach the following courses with high degree of autonomy.

SYLLABUS

Deterministic continuous-time signals
Introduction, telecommunication systems and services, definition of signals, ideal transmission of signals, time domain signals, complex notation, basic operations on signals, classification, duration, Dirac impulse, energy and power. Affinity: cross correlation and autocorrelation between energy and power signals. Time domain series representation of signals: Fourier series for periodic signals, representation with series of orthogonal functions,
Fourier series for time limited signals, representation with samples interpolation. Representation in the signal domain, Gram- Schmidt orthogonalization. Linear transformation: Fourier transform. Examples of Fourier transform, affinity for frequency represented signals, energy and power spectrum, sampling theorem in time and frequency domain. Representation in the complex domain: analytic signal and complex envelope. Basics of source signals: analogue and digital signals. Multilevel source signals, binary signals, synchronous and asynchronous signals. Linear transformation between signals, linear and time invariant transformations in one port systems and in two port systems. Ideal two port system, perfect two port systems. Fundamentals of transmission, ideal transmission, perfect transmission systems, perfect linear channels, time continuous linear processing, filters, processing and reverse processing of step signals, total processing. Multiplexing, analogue digital conversion, basics on channel coding, basics on modulation.
Time continuous random variables and stochastic processes. Random variables theory, probability distribution and density functions, conditional probability distribution. Moments, characteristic and generating function of a random variable. Functions of random variables, distribution and density functions computation, sequences of random variables, transformation of random variables, independence of random variables. Expected value, variance and covariance. Conditional density functions, complex random variables. Stochastic processes, generalities, properties and moments. Classification, spectral theory, transformation of stochastic processes. The Gaussian process. Stationary processes, cross correlation, sum of processes and complex process, ciclostationary processes of first and second order, processes represented by the complex envelope, stationary process not in base band, processes represented in time series, real processes with random factors, processes sampled in base band, complex processes with random factors. Gaussian processes: noise, Gaussian stationary noise not in base band, white Gaussian noise in the signal space. Markov processes: properties, continuous and discrete time.
Imperfect transmission Imperfect connection. Undesirable additive affect at the output. Imperfect transmission over linear time variant channel. Imperfect transmission over linear time invariant channel. Imperfect transmission over non linear channel. Imperfect transmission with independent disturbs. Generalities on independent disturbs. Reduction of effects from independent disturbs. System additive Gaussian noise. Power analysis of a transmission system. Single two port system. Power analysis of noisy linear two port system chain. Noisy linear two port systems. Receiver sensitivity.
Signals utilized in transmission systems Harmonic signals modulation. Transmitter and receiver general schemes for modulated harmonic signals. Analogue harmonic modulation. Amplitude modulations (AM). Angle modulations: phase (PM) and frequency (FM). Performance analysis of harmonic modulation systems with analogue signals. Performance of AM systems. Signal to noise ratio for PM and FM systems.
Signals lab Introduction to Matlab and its use to graphically represent signals. Execution of operations among signals (also periodic). Study of signal properties (energy and power) and correlations.

Networking and Internet

Networking and Internet
3 YEAR2 semester9 CREDITS
Prof. Luca Chiaraviglio2019-20
CHIARAVIGLIO LUCA 2020-21
2021-22
Code: 8039511
SSD: ING-INF/03

OBJECTIVES

LEARNING OUTCOMES: Understand and master the architecture of the Internet.

KNOWLEDGE AND UNDERSTANDING: Understanding of the Internet architecture to: i) learn the economic, technological, historical and research pillars that stimulated the Internet growth, ii) acquire skills about the management of fixed, WiFi and cellular networks, iii) touch through a ground-truth approach about the relationship between security aspects and networking.

APPLYING KNOWLEDGE AND UNDERSTANDING: Practical aspects, such as: network dimensioning problems, performance evaluation, configuration of devices at application and networking levels.

MAKING JUDGEMENTS: The students will learn the building blocks of the current Internet. The students will also understand the current limitations and the possible future research topics.

COMMUNICATION SKILLS: The student will improve its communications skills thanks to the oral examination. Moreover, the adoption of laboratory experiences allows improving the team working skills to solve complex problems.

LEARNING SKILLS: The students will improve its learning skills, thanks to a step by step approach, in which the laboratory experiences support and strengthen the concepts detailed during the lessons. Moreover, the classroom proposes different practical research topics, which can be used as material for further investigations of Bachelor thesis.

SYLLABUS

ECxopree rTimopeinctsal Part with Netkit
– Introduction to the Internet
– Application Layer (HTTP, DHCP, DNS, email)
– Transport Layer (TCP, UDP)
– Network Layer (RIP, OSPF, BGP, SDN, IP, ICMP)
– Link Layer

Additional Topics
– Wireless and Mobile Networks (WiFi, 2G, 3G, 4G)
– Multimedia Networking (Streaming)
– Security (principles of criptography, SSL, WEP, secured email, certification autorithies)

Digital Signal Processing

Digital Signal Processing
3 YEAR2 semester6 CREDITS
Prof. Marina Ruggieri2019-20
RUGGIERI MARINA 2020-21
2021-22
Code: 8039514
SSD: ING-INF/03

OBJECTIVES

LEARNING OUTCOMES: The course aims at providing to the students the theoretical and practical tools for the development of design capabilities and implementation awareness of Digital Signal Processing (DSP) systems and applications.

KNOWLEDGE AND UNDERSTANDING: Students are envisaged to understand the DSP theoretical, design and algorithm elements and to be able to apply them in design exercises.

APPLYING KNOWLEDGE AND UNDERSTANDING: Students are envisaged to apply broadly and, if applicable, to personalize the design techniques and algorithm approaches taught during the lessons.

MAKING JUDGEMENTS: Students are envisaged to provide a reasoned description of the design and algorithm techniques and tools, with proper integrations and links.

COMMUNICATION SKILLS: Students are envisaged to describe analytically the theoretical elements and to provide a description of the design techniques and the algorithm steps, also providing eventual examples.

LEARNING SKILLS: Students are envisaged to deal with design tools and manuals. The correlation of topics is important, particularly when design trade-offs are concerned.

SYLLABUS

PART 1- Discrete-time signals and systems; representation in the time domain; sampling process; Discrete-time Fourier transform (DTFT); Z-transform; Discrete Time Fourier Series (DTFS).
PART 2 – Processing algorthms: introduction to processing; Discrete Fourier Transform (DFT); finite and long processing; DFT-based Processing; Fast Fourier Transform (FFT); processing with FFT.
PART 3 – Filter Design: introduction to digital filters: FIR and IIR classification; structures, design and implementation of IIR and FIR filters; analysis of finite word length effects; DSP system design and applications; VLAB and applications (Dr. Tommaso Rossi) with design examples and applications of IIR and FIR filters, Matlab-based lab and exercises (optional).

VLSI Circuit and System Design

VLSI Circuit and System Design
3 YEAR2 semester9 CREDITS
Prof. Marco Re2019-20
RE MARCO 2020-21
2021-22
Code: 8039166
SSD: ING-INF/01

FORMATIVE OBJECTIVE: …..

KNOWLEDGE AND UNDERSTANDING:

The student will be able to analyze and design microprocessor systems and SW for microprocessors. Starting from these topics the student will be able to write a program in LC3 assembler and to interface the microprocessor with external devices.

APPLYING KNOWLEDGE AND UNDERSTANDING:

The student will apply the knowledge and understanding developed to the analysis of practical problems. This would imply a critical knowledge in terms of silicon real estate and speed for microprocessor based systems.

MAKING JUDGEMENTS:

The student will have to prove his critical awareness with respect to the simplifying assumptions useful to describe and analyze microprocessor systems as well as his critical awareness of the correct order of magnitude of performance parameters while dealing or designing microprocessor systems.

COMMUNICATION SKILLS: The student will prove, mostly during the oral test, his capacity of describing the operation and functioning of microprocessor based digital systems.

LEARNING SKILLS: The student will get familiar with the schematization of practical problems, mostly during the development of his skills for the written test. This mainly concerns microprocessor systems.

SYLLABUS

Introduction
Basics of digital electronics
Data structures for microprocessor systems
The Von Neumann Architecture
The LC3 Architecture
Machine language programming of the LC3
LC3 Assembly programming
LC3 I/O
LC3 Traps e subroutines
Basics of C language programming
Instrumentation and measurements for microprocessor systems

Manufacturing Technologies

Manufacturing Technologies
3 YEAR2 semester9 CREDITS
Prof. Fabrizio Quadrini2019-20
QUADRINI FABRIZIO 2020-21
Code: 8037968
SSD: ING-IND/16

LEARNING OUTCOMES:
Basic knowledge about manufacturing processes for metals.

KNOWLEDGE AND UNDERSTANDING:
Conventional technologies for metals are studied. In order to stimulate student’s knowledge, the interaction between material and tools is always highlighted. The student is able to analyse and evaluate any manufacturing process with a proper technical language.

APPLYING KNOWLEDGE AND UNDERSTANDING:
Thanks to the interaction between frontal lessons and laboratory activities, the student is stimulated to have an own technical profile. He will be able to manage technologies with technical language and sketch capabilities.

MAKING JUDGEMENTS:
The student develops own skills and capabilities in describing transformation processes by taking example from the frontal lessons.

COMMUNICATION SKILLS:
Students are invited to describe technologies in a proper technical way and with an adequate technical speech.

LEARNING SKILLS:
Learning skills are continuously improved thanks to the applied methodology for technology description. This methodology can be translated to any other technological process. Capabilities increase because of the number of described technologies and their correlation. Examples from the industrial world and laboratory experiments crystallize the knowledge about new technologies.

SYLLABUS:

Materials structure and properties: structure of metals, crystals, thermal stresses, solid solution, material properties, mechanical behavior, testing, and manufacturing properties of materials, metal alloys: structure and strengthening by heat treatment

Manufacturing of metals: fundamental of metal-casting, metal-casting processes and equipment, bulk forming (rolling, forging, extrusion and drawing), sheet-metal forming, sintering, fundamentals of machining, cutting-tools, machining processes (turning, drilling, milling).

Joining processes and advanced machining: fusion-welding, solid-state welding, adhesive-bonding, fastening, rapid-prototyping processes and operations, additive manufacturing.

Laboratory lessons: mechanical tests, surface engineering, hardness of metals, microscopy.

Machine Design

Machine Design
3 YEAR2 semester9 CREDITS
Prof. Luciano Cantone2019-20
CANTONE LUCIANO 2020-21
Code: 8037969
SSD: ING-IND/14

OBJECTIVES

LEARNING OUTCOMES: Designing mechanical components considering the need to save weight, material and energy while respecting safety, to promote the usefulness and social impact of the designed product.
KNOWLEDGE AND UNDERSTANDING: The design of mechanical systems; in particular, basic knowledge of the design methodologies of important machine components.
APPLYING KNOWLEDGE AND UNDERSTANDING: Knowing how to recognise, distinguish and use the main techniques and tools for the design of mechanical components.
MAKING JUDGEMENTS: Students must assume the missing data of a problem and be able to independently formulate basic hypotheses (such as that on safety coefficients) based on the operational and functional context of the system/component they have to design.
COMMUNICATION SKILLS: Transfer information, ideas and solutions to specialist and non-specialist interlocutors through intensive use of English terminology.
LEARNING SKILLS: Students, by learning the basics of design, acquire the tools to learn the necessary design techniques of systems/components not directly addressed during the course.

COURSE SYLLABUS

The first part of the course is addressed to the consolidation of basic knowledge to put the student in the right conditions to face a generic machine design problem: Mechanical Engineering design in Broad, Perspective, Load Analysis, Materials, Static Body Stresses, Elastic strain, Deflection, Stability (Eulerian buckling), Vibrations (beam Eigen-modes), Failure Theories, Safety Factors, Reliability, High cycles Fatigue, Low cycles Fatigue, Surface Damage, Contact and impact problems.

The second part will cover specific design activities: Threaded Fasteners and Power Screws, Rivets, Welding, Bonding, Springs, Lubrication and Sliding Bearings, Rolling-Element Bearings, Spur and Helical Gears, Shafts and Associated Parts. During the course, several design activities will be demonstrated by exercises and by real-life applications.

Kinematics and Dynamics of Mechanisms

Kinematics and Dynamics of Mechanisms
3 YEAR1 semester9 CREDITS
Prof. Marco Ceccarelli2019-20
CECCARELLI MARCO 2020-21
Code: 8037957
SSD: ING-IND/13

OBJECTIVES

LEARNING OUTCOMES: The course aims to teach students the knowledge and tools that are needed to address the issues that are related to the identification, modeling, analysis, design of multi-body planar systems, and in particular some transmission organs in English language and terminology

KNOWLEDGE AND UNDERSTANDING: modeling and procedures to recognize the structure and characteristics of mechanisms and machines

APPLYING KNOWLEDGE AND UNDERSTANDING: acquisition of analysis procedures for the understanding of kinematic and dynamic characteristics of mechanisms and machines

MAKING JUDGEMENTS: possibility of judging the functionality of mechanisms and machines with their own qualitative and quantitative assessments

COMMUNICATION SKILLS: learning of technical terminology and procedures for presenting the performance of mechanisms

LEARNING SKILLS: learning of technical terminology and procedures for the presentation of the performance of mechanisms

COURSE SYLLABUS

  • Structure and classification of planar mechanical systems, kinematic modeling, mobility analysis, graphical approaches of kinematics analysis, kinematic analysis with computer-oriented algorithms, fundamentals of mechanism synthesis, trajectory generation; dynamics and statics modeling, graphical approaches of dynamics analysis, dynamic analysis with computer-oriented algorithms, performance evaluation; elements of mechanical transmissions with gears, belts, brakes, and flywheels.

Digital Electronics

Digital Electronics
3 YEAR1 semester9 CREDITS
Prof. Marco Re2019-20
RE MARCO 2020-21
Code: 8037956
SSD: ING-INF/01

OBJECTIVES

LEARNING OUTCOMES

This course aims at providing the fundamentals of DIGITAL ELECTRONICS. More in detail, it deals with the characterization and design of combinational circuits starting from gates. The target technology is CMOS. Starting from the study of the CMOS circuits and the implementation of memory cells the course will face the design and characterization of sequential circuits.

KNOWLEDGE AND UNDERSTANDING

The student will be able to analyze and design combinational and sequential circuits.
Starting from these blocks the student will be able to write a high-level description of a complex digital system based on a computational unit and a control unit.

APPLYING KNOWLEDGE AND UNDERSTANDING

The student will apply the knowledge and understanding developed to the analysis of practical problems. This would imply critical knowledge in terms of silicon real estate and speed for both combinational and sequential systems.
MAKING JUDGEMENTS: The student will have to prove his critical awareness with respect to the simplifying assumptions useful to describe and analyze combinational and sequential systems as well as his critical awareness of the correct order of magnitude of performance parameters while dealing or designing digital circuits.

COMMUNICATION SKILLS

The student will prove, mostly during the oral test, his capacity of describing the operation and functioning of digital systems.

LEARNING SKILLS

The student will get familiar with the schematization of practical problems, mostly during the development of his skills for the written test. This mainly concerns combinational systems and sequential systems

COURSE SYLLABUS

  • This course constitutes an introduction to the engineering of digital systems.
  • Starting with data representation in digital form, it goes on to provide students with the ability to design a circuit for a given algorithmic information processing task. For this purpose, Boolean functions and combinational design are covered, followed by sequential logic design through Finite State Machines. Moreover standard MSI blocks (sequential and combinational are illustrated) up the description of algorithmic state machines.
  • The student should be able to understand the structure of a complex digital system and able to design the architecture and the internal blocks of the system. In the course, a brief introduction to the electrical measurements for digital systems is given (oscilloscope, Logic State Analyzer, Pattern Generator).

Thermodynamics and Heat Transfer

Thermodynamics and Heat Transfer
2 YEAR2 semester9 CREDITS
Prof. Paolo Coppa2019-20
BOVESECCHI GIANLUIGI 2020-21
Michela Gefulsa2021-22
Code: 8039146
SSD: ING-IND/10

OBJECTIVES

LEARNING OUTCOMES: The course aims to provide students with the basic principles, physical laws, and applications of thermodynamics, thermo-fluid dynamics and heat transfer, with the dual purpose of preparing them to afford more applicative courses, and use the acquired knowledge for design and sizing simple components and thermal systems.

KNOWLEDGE AND UNDERSTANDING

Students will have to understand the physical laws of applied thermodynamics and heat transfer, and understand the structure and operation of the simplest components and systems. They will also demonstrate that they have acquired the basic methodologies for verifying and designing the studied devices.

APPLYING KNOWLEDGE AND UNDERSTANDING

Students must be able to afford courses for which this course is preparatory (for example Thermotechnique, or Machines) and to size or verify simple components and systems, topics covered by the course, such as air conditioning systems, engine systems, fins and heat exchangers.

MAKING JUDGEMENTS

Students must assume the autonomous capacity to face the subsequent studies for which this course is preparatory and to draw up simple projects of thermal systems that use the studied components. They will also need to be able to evaluate projects written by other parties, checking that the project requirements are satisfied.

COMMUNICATION SKILLS

Students must be able to illustrate in a complete and exhaustive way the acquired information, the results of their study and of their project activity, also through the normally used means of communication (discussion of the results obtained, report on the performed activity, PowerPoint presentations, etc.).

LEARNING SKILLS

Students must be able to apply the physical laws underlying the studied phenomena, and to face further studies that use the acquired knowledge. They will have to be able to expand the already owned information through the analysis of technical-scientific literature and to modify their curricula choosing future knowledge to be acquired on the base of their knowledge and tendency.

COURSE SYLLABUS

  • Fundamental laws of thermodynamics: zeroth law, first law for open and closed systems, second law, entropy definition and Clausius integral, Maxwell equations, Claperyron equation
  • Thermodynamic diagrams: P-v, T-s, H-s, P-h
  • Thermodynamic cycles for close and open systems: engine cycles: Otto Cycle, Diesel cycle, Joule Brighton cycle, Rankine and Hirn cycle, refrigeration cycle
  • Air and steam mixtures, design of conditioning air systems
  • Basic laws of fluid dynamics: Bernoulli equation, the motion of fluids in ducts, major and minor pressure drops, dimensional analysis for turbulent flow friction factor.
  • Heat transfer mechanisms. Conduction: Fourier law, basic conduction heat transfer equation, solution for simple geometries with and without heat generation, lumped parameter problems, cooling fins. Convection: dimension analysis for forced and free convection. Radiation heat transfer: basic laws of radiation, radiation exchanges between black bodies and grey bodies, configuration factors, electric analogy. Heat exchangers: types, size problem and rate problem.