Project Description

Learning objectives

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.

Course content

Deterministic continuous-time signalsIntroduction, 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.


0 credits
90 hours
0 year
Bachelor Degree
0 semester