Course: 2021/2022

Advanced techniques in signal processing and communications

(14315)

The student must adquire the following competences:
- Knowledge to apply information theory methods, adaptive modulation, and channel coding, as well as digital signal processing advanced techniques applied to communication systems.
- Knowledge to apply analytic and algorithmic tools to deal with estimation adn classification problems and,
in general, with information processing problems.

Skills and learning outcomes

Description of contents: programme

- Communications: advanced receivers and modulation techniques
- Introduction to Information Theory
- Channel coding
- Distributed signal processing
- Dynamic models

Learning activities and methodology

Three teaching activities are proposed: Theoretical classes, exercise classes and laboratory exercises. ECTS credits account for the time the student must work on his own or as part of a team.
THEORETICAL CLASS AND EXAMPLES
The theoretical class will be given in the blackboard, with slides or by any other means to illustrate the concepts learnt. In these classes the explanation will be completed with examples. In these sessions the student will acquire the basic concepts of the course. It is important to highlight that these classes require the initiative and the personal and group involvement of the students (there will be concepts that the student himself should develop).
CLASS EXERCISES
Before the exercise class, the student will have available the exercise formulation. The student should solve the exercises proposed in order to assimilate the concepts obtained in the theoretical class in a more complex environment and to self-evaluate his knowledge.
LABORATORY EXERCISES
Basic concepts learnt during the course are applied in the laboratory and by means of simulation. The student should participate actively in the exercise implementation.
TUTORIAL SESSIONS
The student can request a tutorial session to solve any difficulty that might arise during the course.

Assessment System

- % end-of-term-examination 0
- % of continuous assessment (assigments, laboratory, practicals...) 100

Basic Bibliography

- Artés, A., Pérez González, F., Cid, J., López, R., Mosquera, C., Pérez Cruz, F.. Comunicaciones digitales. Peason.
- Cover, T.M., Thomas, J.A.. Elements of Information Theory. Wiley-Interscience.
- Theodoridis, S. Machine Learning - Learning From Data. Elsevier. 2015

Additional Bibliography

- Loeliger, H.A.. An Introduction to Factor Graphs, Signal Processing Magazine, Jan 2004. IEEE.
- . Communications Magazine. IEEE.
- . Communications of the ACM. ACM.
- . Proceedings of the IEEE. IEEE.
- . Signal Processing Magazine. IEEE.

The course syllabus may change due academic events or other reasons.