Base Knowledge
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.
Teaching Methodologies
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.
Learning Results
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.
Program
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.
• Motivation for advanced signal processing techniques
Laboratory 1 – Fourier Series
Laboratory 2 – Discrete Fourier Transform
Laboratory 3 – The z Transform
Laboratory 4 – Finite Impulse Response (FIR) Filters
Laboratory 5 – Design of Infinite Impulse Response (IIR) Filters
Laboratory 6 – Evaluating Harmonic Distortion in Power Systems
Mini/Project A – Quadrature Phase Shift Keying Modulation (QPSK)
Mini/Project B – Frequency Shift Keying Modulation and Demodulation (FSK)
Grading Methods
- Laboratory work in group during laboratorial lessons: 25% of the evaluation
- Min-Project: 25% of the evaluation (Project A or Project B)
- Final written exam: 50% of the evaluation
Internship(s)
NAO
Bibliography
• A. Bruce Carlson, Communication Systems, An Introduction to Signals and Noise in Electrical
Communication
• Richard G. Lyons, Understanding Digital Signal Processing
• John G. Proakis, Dimitris K Manolakis, Digital Signal Processing
• John Proakis, Masoud Salehi, Digital Communications
• Marvin E. Frerking, Digital signal processing in communication systems
• John G. Proakis Masoud Salehi, Gerhard Bauch,
Contemporary Communication Systems Using MATLAB
• Dennis Silage, Digital Communication Systems Using MATLAB® and Simulink®
• Steven A.Tretter, Communication System Design Using DSP Algorithms
• Texas Instruments DSP Kits Documentation
• Allan V. Oppenheim, MIT “Signals and Systems” Open Course
• Allan V. Oppenheim, MIT “Digital Signal Processing” Open Course
• Hendrik C. Ferreira, Lutz Lampe, John Newbury, Theo G. Swart, Power Line Communications: Theory and
Applications for Narrowband and Broadband Communications over Power Lines
• Roman Kuc, Introduction to Digital Signal Processing, McGraw Hill, 1988
• “IEEE Recommended Practice and Requirements for Harmonic
Control in Electric Power Systems,” in IEEE Std 519-2014 (Revision
of IEEE Std 519-1992), vol., no., pp.1-29, 11 June 2014, doi:
10.1109/IEEESTD.2014.6826459.
• IEC 61000 4-7, Electromagnetic compatibility (EMC) – Part 4-7:
Testing and measurement techniques – General guide on harmonics
and interharmonics measurements and instrumentation, for power
supply systems and equipment connected thereto.
• Selected Youtube videos, webpages, IEEE SPSS and discussion fora on Signal Processing