Institute of Communications Engineering

Channel Coding

Announcements

In the winter semester 2020/21 the lecture will be organized as an online lecture via Moodle . Please registrate in Moodle for this course.

We provide lecture recordings from last year, exercise sheets and their solutions and also offer a question time for lecture and exercises via the Big Blue Button room on demand.

Learning Lounge (CT)

The Learning Lounge is available for Communications Technology students. The Learning Lounge is an optional tutorial-style offered by UULM PRO MINT & MED, which helps students to improve their learning strategies and offers help in subject-related questions (with a focus on mandatory subjects within the CT MSc program). For questions, please contact Dr. Ulrich Galster.

 

Contents

Channel coding has become an essential part in communication and storage systems. Block and convolutional codes are used in all digital standards. The aim of channel coding is to protect the information against disturbances during transmission or write/read. Thereby redundancy is added for error correction and for error detection. This course is about the basic methods in channel coding and gives an introduction to the more advanced methods of coded modulation.

The course is intended for Master students in electrical engineering with major in communication engineering. In addition it may be suited for students in computer science and mathematics.

Topics

Linear block-codes

  • Generator and parity-check matrix
  • Cosets
  • Principles of decoding
  • Hamming codes
  • Bounds for code parameters (Hamming-, Singleton-, Gilbert-Varshamov-Bounds)
  • Trellis representation of block-codes
  • Plotkin construction, Reed-Muller (RM) codes (relationship to binary PN- and Walsh-Hadamard sequences)
  • APP and ML decoding (sequence and symbol based)

Algebraic coding

  • Prime fields, primitive elements, component- and exponent representation
  • Reed-Solomon (RS) codes as cyclic codes with generator- and check-polynomials
  • Algebraic error and erasure correction with the Euclidean algorithm
  • BCH codes (as subfield subcodes of RS codes)
  • The perfect Golay-code as non-primitive BCH-code
  • Decoding of algebraic codes (key equation, Euclidean- and Berlekamp-Massey algorithm)

Convolutional codes

  • Algebraic properties
  • State Diagram
  • Trellis representation
  • Error correction capabilities of convolutional codes
  • Viterbi- and BCJR algorithm (flow in graphs)

Further coding and decoding techniques

  • LDPC codes
  • Permutations-, Majority- and Information-Set decoding
  • Dorsch algorithm (ordered statistics decoding)
  • Parallel (Turbo)- and serial concatenated codes and their iterative decoding

Introduction to generalized code concatenation and coded modulation

Downloads

Introductory Lecture

Lab 1 ( Unique Decoding of Reed–Solomon Codes with the Extended Euclidean Algorithm  | Templates )

Lab 2 ( Decoding of Convolutional Codes using the Viterbi Algorithm | Template )

Relevant chapters


Handout 1 (relevant topics)

Handout 2 (further topics)

Literature

References

  • Main book of the course (German/English)
    • Bossert M., Kanalcodierung, 3. Auflage, Oldenbourg, 2013
    • Bossert M., Channel Coding for Telecommunications, John Wiley & Sons, 1999
    • Johannesson, Zigangirov: Fundamentals of Convolutional Coding , IEEE Press
    • Lin, Costello: Error Control Coding, 2nd Edition, Prentice Hall, 2004
  • Further reading Coding Theory
    • Blahut R. E., Algebraic Codes for Data Transmission, Cambridge University Press, 2003
    • Roth R., Introduction to Coding Theory, Cambridge University Press, 2006
    • Justesen J. and Hoeholdt, T., A Course In Error Correcting Codes, EMS Publishing House, 2004
    • MacWilliams F. J. and Sloane N. J. A., The Theory of Error-Correcting Codes, Elsevier, 1977
  • Further reading Finite Fields/Algebra
    • McEliece R. J., Finite Fields for Computer Scientists and Engineers, Kluwer, 1987
    • Lidl R. and Niederreiter H., Introduction to Finite Fields and their Applications, Cambridge, 2002
    • Menezes A. and Blake I. F., Applications of Finite Fields, Kluwer, 1993
    • Lipson J. D., Elements of Algebra and Algebraic Computing, Addison-Wesley, 1981
  • Further reading Stochastics and Probability
    • Gubner J. A., Probability and Random Processes for Electrical and Computer Engineers, Cambridge, 2006

Semesterapparat

Additionally, the "Semesterapparat" to this Lecture may be of interest.

Winter Term 2020/21

Question Hour: on demand

Language

English

Requirements

Bachelor

Exams

Oral exam

Further Information

Hours per Week:  3V + 2Ü + 1P
8 ECTS Credits
LSF - ENGJ 70426