Course Advanced Channel Coding
Responsible: Prof.Dr. Uwe Dettmar
Course
Meets requirements of following modules(MID)
Course Organization
Version |
created |
2013-04-25 |
VID |
2 |
valid from |
WS 2012/13 |
valid to |
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|
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Course identifiers |
Long name |
Advanced Channel Coding |
CID |
F07_ACC |
CEID (exam identifier) |
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|
Contact hours per week (SWS) |
Lecture |
2 |
Exercise (unsplit) |
1 |
Exercise (split) |
|
Lab |
1 |
Project |
|
Seminar |
|
Tutorial(voluntary) |
|
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Total contact hours |
Lecture |
30 |
Exercise (unsplit) |
15 |
Exercise (split) |
|
Lab |
15 |
Project |
|
Seminar |
|
Tutorial (voluntary) |
|
|
|
Max. capacity |
Exercise (unsplit) |
15 |
Exercise (split) |
|
Lab |
15 |
Project |
|
Seminar |
|
|
Total effort (hours): 150
Instruction language
Study Level
Prerequisites
- 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
Instructors
Supporting Scientific Staff
- Dipl.-Ing. Martin Seckler
Transcipt Entry
Advanced Channel Coding
Assessment
Type |
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
Lecture/Exercise
Objectives
Contents
- 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
Contribution to course grade |
fAP |
30% |
Frequency: 1 per year
Lab
Objectives
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
Type |
fTP |
solve given problems in dyads |
Contribution to course grade |
fTP |
solve given problems in dyads |
Frequency: 1 per year
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