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Third-Cycle Courses

Faculty of Engineering | Lund University

Details for the Course Syllabus for Course EITN45F valid from Spring 2018

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General
Aim
  • The aim of this course is to give the students knowledge of principles for information storage and transmission of information, and the use of binary representation of information. The course also gives knowledge of the prestanda and fundamental boundaries of todays and tomorrows communication systems.
Contents
  • The definition of information goes back to Shannons landmark paper in 1948. His theory of how information can be processed is the basis of all efficient digital communication systems both today and tomorrow. This course provides an up-to-date introduction to topic information theory. The course emphasizes both the formal development of the theory and the engineering implications for the design of communication systems and other information handling systems. The course includes:
    * Shannon's information measure and its relatives, both for the discrete and continuous case.
    * Three fundamental information theorems: Typical sequences, Source coding theorem and Channel coding theorem.
    * Source coding: Optimal coding and construction of Huffman codes, as well as universal souce coding such as Ziv-Lempel coding (zip, etc.).
    * Channel coding: Principles of error detection and correction on a noisy channel, mainly illustrated by Hamming codes.
    * Gaussian channel: Continuous sources and additive white noise over both band limited and frequency selective channels, as wellas the multi-dimensional Gauss channel for MIMO systems. Derivation of the fundamental Shanon limit.
    * Discrete input Gaussian channel: Maximum achievable rates for PAM and QAM, Coding and Shaping gain, and SNR gap.
Knowledge and Understanding
  • For a passing grade the doctoral student must
  • be able to identify and formulate problems within the area of Information Theory
    be able to classify the level of difficulty of problems related to the his/her own level of knowledge
Competences and Skills
  • For a passing grade the doctoral student must
  • be able to show ability to handle new methods and results.
    be able to set up requirements on implementation of algoritms in the course.
    be able to realize systems for the algorithms presented in the course.
Judgement and Approach
  • For a passing grade the doctoral student must
  • be able to classify the level of difficulty of problems related to the his/her own level of knowledge
    be aware of what parameters set up the boundaries for reliable communicationa as well as the compression ratio of a source.
Types of Instruction
  • Lectures
  • Exercises
Examination Formats
  • Written exam
  • Written assignments
  • The examonations is done thrhrough hand in problems and take home exam.
  • Failed, pass
Admission Requirements
Assumed Prior Knowledge
  • Knowledge corresponding to a basic course in Probability theory and a course in Digital Communications.
Selection Criteria
Literature
  • Höst, S.: Kompendie: Information Theory and Communication Engineering.
Further Information
  • Course Coordinator: Stefan Höst, stefan.host@eit.lth.se
Course code
  • EITN45F
Administrative Information
  • 2017-09-26
  • Professor Thomas Johansson

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