Course Syllabus for

Fundamentals of Information Theory
Grunderna inom informationsteori

EIT145F, 7.5 credits

Valid from: Spring 2016
Decided by: Professor Thomas Johansson
Date of establishment: 2016-11-02

General Information

Division: Electrical and Information Technology
Course type: Third-cycle course
Teaching language: English


Information theory studies the fundamental limits of information transmission and storage. The course is divided into two parts. The aim of Part I is to introduce the fundamental concepts of information theory, focusing on classical point-to-point transmission scenarios. This part is based on selected chapters of the book by Cover/Thomas, which has been widely used as graduate level entry into information theory. In Part II the perspective is extended to multi-user communication scenarios, following selected parts of the book by El Gamal/Kim, which provides an excellent overview of current state-of-art in the field. Using these two books makes the course both up-to-date and self-contained so that no prior background in information theory is required.


Knowledge and Understanding

For a passing grade the doctoral student must

Competences and Skills

For a passing grade the doctoral student must

Judgement and Approach

For a passing grade the doctoral student must

Course Contents

Part I: entropy, mutual information and their properties, typical sequences, data compression, source coding theorem, channel capacity, channel coding theorem, continuous random variables, differential entropy, Gaussian channels Part II: multiple access channels, broadcast channels, interference channels, channels with state: writing on dirty paper, distributed compression: Slepian-Wolf theorem, Gaussian vector channels, wireless fading channels, relay channels

Course Literature

Instruction Details

Types of instruction: Lectures, exercises. The aim of the exercise classes is to discuss the home assignments. The doctoral students should present and discuss ways to solve the problems.

Examination Details

Examination formats: Oral exam, written assignments. Attendance of at least 80% of the lectures and exercise lessons are a requirement to pass the course.
Grading scale: Failed, pass

Admission Details

Assumed prior knowledge: Solid skills in engineering mathematics, including probability theory, linear algebra and calculus.

Further Information

Course Coordinator: Michael Lentmaier

Course Occasion Information

Contact and Other Information

Course coordinator: Michael Lentmaier <>

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