389.032 Information theory for communications engineers
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2020W, VO, 2.0h, 3.0EC

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VO Lecture
  • Format: Presence

Learning outcomes

After successful completion of the course, students are able to understand important concepts and fundamental relations of information theory as well as their application to source coding and channel coding. A further outcome is an improvement of English language skills.

Subject of course

* Fundamentals of information theory:  Entropy, mutual information, typical sequences, fundamental relations and inequalities, interpretations

* Lossless source coding:  Optimal codes, Huffman code, significance of entropy, universal codes, Lempel-Ziv code

* Lossy source coding:  Rate-distortion theory, quantization, rate-distortion function, Shannon's rate-distortion theorem

* Channel coding:  Channel capacity, Shannon's channel coding theorem, Gaussian channel, parallel Gaussian channels, feedback channels, separability of source coding and channel coding

Teaching methods

The prof (Hlawatsch) verbally presents the class material, discusses the material with his students, and answers the students' questions. For this, he uses a blackboard, on which he writes certain characters and draws simple figures with a piece of chalk (also using different colors if helpful). He also uses a tablecloth to erase the board every now and then. Finally, he uses an overhead projector to project more complicated figures and tables on a screen. The prof's presentation is supported by detailed lecture notes.

Mode of examination

Oral

Additional information

First class: Thursday, October 8. 2020, 3.15 p.m., in Seminar Room 389 (formerly 118) of the Institute of Telecommunications

Because of the limited capacity of the classroom, the first class (on October 8) will be additionally offered in distance mode. The subsequent classes will be held only in presence mode (if possible).

This course is an optional part of the "Wahlmodul Advanced Digital Communications."

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Thu15:15 - 17:0008.10.2020 - 28.01.2021Sem 389 Information theory for communications engineers
Information theory for communications engineers - Single appointments
DayDateTimeLocationDescription
Thu08.10.202015:15 - 17:00Sem 389 Information theory for communications engineers
Thu15.10.202015:15 - 17:00Sem 389 Information theory for communications engineers
Thu22.10.202015:15 - 17:00Sem 389 Information theory for communications engineers
Thu29.10.202015:15 - 17:00Sem 389 Information theory for communications engineers
Thu05.11.202015:15 - 17:00Sem 389 Information theory for communications engineers
Thu12.11.202015:15 - 17:00Sem 389 Information theory for communications engineers
Thu19.11.202015:15 - 17:00Sem 389 Information theory for communications engineers
Thu26.11.202015:15 - 17:00Sem 389 Information theory for communications engineers
Thu03.12.202015:15 - 17:00Sem 389 Information theory for communications engineers
Thu10.12.202015:15 - 17:00Sem 389 Information theory for communications engineers
Thu17.12.202015:15 - 17:00Sem 389 Information theory for communications engineers
Thu07.01.202115:15 - 17:00Sem 389 Information theory for communications engineers
Thu14.01.202115:15 - 17:00Sem 389 Information theory for communications engineers
Thu21.01.202115:15 - 17:00Sem 389 Information theory for communications engineers
Thu28.01.202115:15 - 17:00Sem 389 Information theory for communications engineers

Examination modalities

Oral exam

Course registration

Registration modalities

Bei der ersten Vorlesung

Curricula

Study CodeObligationSemesterPrecon.Info
066 507 Telecommunications Not specified
710 FW Elective Courses - Electrical Engineering Elective

Literature

Lecture notes for this course are available at the "Grafisches Zentrum" of TU Wien, Wiedner Hauptstraße 8-10, 1040 Wien.

Previous knowledge

Working knowledge of probability theory and random variables

Language

English