Course Advanced Channel Coding

Responsible: Prof.Dr. Uwe Dettmar


Meets requirements of following modules(MID)

Course Organization

created 2013-04-25
valid from WS 2012/13
valid to
Course identifiers
Long name Advanced Channel Coding
CEID (exam identifier)

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

Total effort (hours): 150

Instruction language

  • Englisch

Study Level

  • Graduate


  • basics in linear algebra
  • basics in stochastics
  • basic programming capabilities

Textbooks, Recommended Reading

  • R. E. Blahut. Algebraic Codes for Data Transmission. Cambridge University Press, Cambridge, 2003.
  • S. Lin and D. J. Costello. Error Control Coding. ISBN 0-13-042672-5. Prentice-Hall, 2004
  • T. M. Cover and J. A. Thomas. Elements of Information Theory. Wiley, New Jersey, 2006
  • A. Neubauer. Kanalcodierung. Schlembach, Wilburgstetten, 2006.
  • R. Roth. Introduction to Coding Theory. Cambridge, second edition, 2006
  • B. Sklar. Digital Communications. Prentice Hall PTR, Upper Saddle River, New Jersey, 2001


  • Prof.Dr. Uwe Dettmar

Supporting Scientific Staff

  • Dipl.-Ing. Martin Seckler

Transcipt Entry

Advanced Channel Coding


oE 70% normal case (large number of assessments wE)
fAP 30% three eTests

Total effort [hours]
oE 3
fAP 7

Frequency: 2/Jahr

Course components



  • binary block and convolutional codes
    • definitions, fundamental principles
      • definition of error correction and detection
      • linear and non-linear codes
      • Hamming distance and Hamming weight
      • minimum distance
    • linear block codes
      • properities of linear codes
      • Generator and parity check matrix
      • systematic codes
      • simple coding and decoding examples
    • convolutional codes
      • definition
      • encoder, state diagram, trellis
      • distance properties, catastrophic codes
      • error probaiblities
      • Viterbi decoder, optimum metrics
  • basics of information theory
    • definitions, joined and conditional entropy
    • AEP theorem, channel capacity, channel coding theorem
    • channel capacity of the AWGN channel, waterfilling
  • finite fields and coding
    • review of basic theorems
    • primitive elements
  • cyclic codes
    • definition and properties
    • generator and check polynomial, syndrome
    • non algebraic decoding methods and structures
  • Reed-solomon codes
    • Definition and properties
    • classical decoding algorithm
  • codes for iterative decoding
    • concept of iterative decoding
    • Tanner graphs
    • BCJR algorithm
    • TURBO codes and decoding
    • LDPC codes and decoding
  • basics of Space-Time-Coding
    • definitions
    • Alamouti scheme

Acquired Skills
  • assess and compare methods for error control coding
    • choose coding schemes for given applications
    • define code properties and use coding bounds
    • characterize performance and complexity
  • analyse performance impacts of error correcting cods in communication systems
  • understand and and solve problems related to error control coding
  • achieve system trade-offs by using error correcting codes

Additional Component Assessment

fAP 3 midterm tests

Contribution to course grade
fAP 30%

Frequency: 1 per year



Acquired Skills
  • test theoretical results from lecture and tutorial
  • implement algorithms for error control coding
  • simulate BER

Operational Competences
  • adapt programs to solve equivalent problems
  • become acquainted with the Matlab Communications Toolbox
  • self-contained work with the provided simulation tools and programs
  • write own Matlab scripts
  • comparison of different technical solutions

Additional Component Assessment

fTP solve given problems in dyads

Contribution to course grade
fTP solve given problems in dyads

Frequency: 1 per year

Topic-Revision: r3 - 11 Jan 2016, GeneratedContent
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