Course Source and Channel Coding

Responsible: Prof.Dr.Dettmar


Meets requirements of following modules(MID)

Course Organization

created 2011-11-25
valid from WS 2012/13
valid to
Course identifiers
Long name Source and Channel Coding
CEID (exam identifier)

Contact hours per week (SWS)
Lecture 2
Exercise (unsplit)
Exercise (split) 2
Lab 1
Total contact hours
Lecture 30
Exercise (unsplit)
Exercise (split) 30
Lab 15
Tutorial (voluntary)
Max. capacity
Exercise (unsplit)
Exercise (split) 40
Lab 18

Total effort (hours): 150

Instruction language

  • German

Study Level

  • undergraduate


  • Linear Algebra
  • Stochastics
  • basics in digital communications
  • Matlab basics

Textbooks, Recommended Reading

  • B. Sklar Digital Communications, Prentice Hall, 2001
  • Proakis: Digital Communications, Mc Graw Hill, 2000
  • Roppel, Grundlagen der digitalen Kommunikationstechnik, Hanser, 2006
  • Neubauer, Informationstheorie und Quellencodierung, Schlembach, 2006
  • Neubauer, Kanalcodierung, Schlembach, 2006
  • Lin, Costello, Error Control Coding, Prentice Hall 2004


  • Prof.Dr.Dettmar

Supporting Scientific Staff

  • Dipl.-Ing. Seckler

Transcipt Entry

source and channel coding


oE Regelfall (bei großer prüfungszahl sK)

Total effort [hours]
wE 10

Frequency: 2 per year

Course components



  • Introduction to information theory
    • information, entropy, redundancy
    • source coding theorem
    • channal capacity, transinformation
    • channel coding theorem
    • performance, potential
  • bascis on source coding
    • sources with and without memory
      • entropie computation
      • Markov sources
    • practical source codes
      • Huffman Codes
      • Lempel-Ziv Codes
      • arithmetical Codes
    • Irrelevance reduction
      • Overview
      • Quantisation
      • PCM
        • DPCM
        • ADPCM
        • Delta Modulation
        • Sigma Delta Modulator
  • basics on channel coding
    • basics, finite fields
    • binary linear block codes
      • basics and definitions
      • Hamming Codes
      • Reed Muller Codes
      • Repetition and parity check codes
    • convolutional codes
      • basics, definitions
      • encoder
      • state diagram and trellis
      • distance profile
      • catastrophical codes
    • decoding
      • standard array
      • majority logic decoding
      • Viterbi decoding
  • coded modulation
    • trellis coded modulation
    • block coded modulation
  • link budget
    • link budget computation
    • estimate the functionality of a link
    • System Trade-offs
  • spread spectrum
    • basic principles
    • DS-SS
    • FH-SS
    • applications related to signal seperation, signal suppression, time and location, multiuser-communications
  • diversity
    • antenna diversity
    • interleaving
    • Alamouti STC

Acquired Skills
  • analyse telecom systems
  • discuss and understand performance parameters of transmission systems
  • apply and compare algorithms for data compression and error control coding
  • apply theoretical knowledge to practical problems
  • understand and solve problems self-contained

Additional Component Assessment



Acquired Skills
  • analyze and simulate telecom systems and methods
  • evaluate the performance of standard algorithms in source and channel coding
  • discuss and interprete simulation results

Operational Competences
  • adapt SW to similar problems
  • use the Matlab Communications Toolbox, write own scripts
  • experiment with SW tools
  • compare different technical solutions

Additional Component Assessment

bK 3 eTests each 15 min
fIN interview on specific topics

Contribution to course grade
fAP assessed problem solving
fIN interview on specific topics
o prerequisite to course exam

Frequency: 1/year

Topic-Revision: r3 - 11 Jan 2016, GeneratedContent
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