DSP and Communications

Fundamentals of differential and integral calculus.
Bachelor level understanding of electrical circuits, continuous-time electrical signals, linear systems and
analog signal transformations.
Introduction to communication systems welcomed.
Experience with C programming and simulation tools such as Matlab welcomed.

An expositive methodology will be used in the lectures, including the resolution of illustrative examples
explaining the fundamental concepts. The laboratory classes will be based on solving exercises applied to
real problems, reinforcing the concepts presented in lectures. The exercises will be addressed in order to
establish the link between the general theoretical concepts and their practical application. The resolution of
the exercises will have an analytical component and a component of simulation using Matlab. There will also
be a project component at the final part of the module, using DSP development hardware (TMS 320C6713
DSK) in order to accurately simulate a simple communication system, allowing students to integrate the
acquired knowledge, research and develop solutions when faced with new problems. The method of
assessment is a final written examination on the acquired knowledge and a laboratory report and
presentation on the developed project.

The generic objectives and learning results for this module are: understanding the digital representation of
analog signals and systems as well as the most representative signal transformations for continuous and
discrete time; modeling and simulation of simple communication techniques and systems using digital signal
processing concepts and specific mathematical and software tools.

For this purpose, the fundamental concepts and mathematical tools for signal processing and digital signal
processing are introduced. These refer to time and transform domain representation of signals and systems
including fundamental signal processing operations such as filtering and analog-to-digital conversion.
Building on this fundamental concepts and tools, simple specific communication systems and applications
are presented, studied and simulated, demonstrating the full relevance of these topics for the development,
implementation and operation of communication technologies.

The main focus is on the signal processing fundamentals needed to understand most electrical engineering
subjects such as non-sinusoidal power systems and the communication technologies that are fundamental
for both the low-level monitoring and control, as well as the high-level operation of the smart grids.

Competences: To understand the digital representation of communication signals in time and transform
domains; To understand and apply the most representative signal processing techniques in time and
transform domains; To understand and apply simple signal processing techniques for communication
systems; To implement and code program signal processing techniques in specific DSP development
hardware.

The Digital Signal Processing and Communications Subject aims at presenting and demonstrating the full
relevance of the fundamental signal processing topics for the development, implementation and operation
of communication technologies in the context of the master course. It is organized in the following
topics:Digital Signal Processing and Communications.
• Signal Representations;
• Fourier Series;
• Fourier Transform;
• Discrete Fourier Transform;
• Fast Fourier Transform;
• Z Transform;
• Digital Approximations of Analog Transfer Functions;
• Analog to Digital Conversion;
• Digital Filters;
• Digital Algorithms for Communication Systems.
• Introduction to PLC Communications.
• Signal Processing in Interference, Noise and Power Quality.

NAO