IA/0076 - CODES
Academic Year 2021/2022
Free text for the University
DANIELE GIUSTO (Tit.)
- Teaching style
- Lingua Insegnamento
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The teaching activity of Coding course aims at providing the knowledge for the analysis, design and evaluation of digital transmission systems.
The course is based on standard lectures, with frequent discussions and collaborative works on real aspects of technologies.
The learning outcomes of this teaching activity, expressed in terms of the Dublin Descriptors, are the following:
1) Knowledge and understanding. After the completion of this teaching activity, the student should know and understand: each module of a system for information processing and transmission; how to evaluate its performance. The student will also know the basic methods to design a system for information processing and transmission.
2) Applying knowledge and understanding. After the completion of this teaching activity, the student should be able to: evaluate the performance of a system for information processing and transmission against given requirements and operating constraints; identify each module in order to design a global system that satisfy the requirements; chose the best technologies in order to design each module.
3) Making judgements. The student will be able to evaluate the design process and results.
4) Communication skills. After the completion of this teaching activity, the student should be able to explain in an organic way the dependences among the different modules of an information processing and transmission system, and the dependences of these modules on the device where they have been deployed.
5) Lifelong learning skills. The student will be able to follow and understand the technology updates, understand the technical documentation, and to integrate all different information in order to have a broad view of problems and solutions relevant to information processing and transmission systems.
The student should have a good knowledge of:
understanding and usage of the scientific-technical language (in particular, physics and mathematics);
understanding and usage of basic instruments and software;
present and discuss concepts and information, in oral, written or graphic way;
study organization, day-by-day, and to make mid-term plans;
basic Signal Theory and Probability Theory (anyway, at the beginning of the course, the necessary background will be illustrated with significant examples);
ability to identify and use links between phenomena, their properties and their representations.
In other terms, the knowhow that usually is gained during a BSc course in engineering or computer science.
1) Information theory: Information. Entropy. Compression. Channels. Channel capacity. (30 hours in total: lessons (20 hours); practice (10 hours)
2) Error control coding: FEC and ARQ systems. Repetition codes. Parity codes. Block codes. Cyclic codes. Syndrome decoding. Convolutional codes. Viterbi decoding. (30 hours in total: lessons (20 hours); practice (10 hours)).
This teaching unit is organized on a single semester, with:
- lectures with electronic presentations (PowerPoint) (40 hours);
- practice (individual and group) (20 hours);
- talks/discussions by visiting experts from industry;
- company lab visits.
During lessons, participation is stimulated with questions, analysis of practical aspects of systems, discussion on the application scenario and on links to other subjects.
The teacher is available to answer questions either by email/social networks, or during the contact hours, or directly in class, during the lecture or during the break between consecutive teaching hours.
Verification of learning
Each student is evaluated by weekly assessment tests (2 points per week), and a final assessment written exam on Information Theory and Coding topics.
For the final assessment, the score is given by weighting the answers to different exercises.
For each exercise/question, a maximum score is assigned. The answer provided for each exercise/question is evaluated with a score from 0 to the max assigned score. The maximum score is assigned in the case of a correct answer, while a smaller score is assigned according to the severity of the errors. In particular, conceptual errors, and errors caused by lack of knowledge have a larger weight than errors due to misunderstandings or inaccuracies.
All these assessments contribute to reach the final mark; 32 points or more are necessary to achieve a “30 e lode” mark.
It is possible to increase the final mark of the written test with a short oral test.
If the final mark is not sufficient (i.e. 18 or more), the student may ask for an oral assessment, where he should prove his knowledge of methodology and technology and their application in real world environment.
B.Carlson, Communication Systems, McGraw-Hill.
R.Gray, Entropy and Information Theory, Stanford University Press.
Copies of the slides as well as all the material used in classes are available in a cloud directory.