Course Source and Channel Coding

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Responsible: Prof.Dr.Dettmar

Course

Meets requirements of following modules(MID)

• in active programs
  • Ba ET2012 QK
  • BATIN2012 QK
  • Ba ET2010 QKC
  • BATIN2010 QKC

Course Organization

Version created 2011-11-25 VID 2 valid from WS 2012/13 valid to

Course identifiers Long name Source and Channel Coding CID F07_QK CEID (exam identifier)

Contact hours per week (SWS) Lecture 2 Exercise (unsplit) Exercise (split) 2 Lab 1 Project Seminar Tutorial(voluntary)

Total contact hours Lecture 30 Exercise (unsplit) Exercise (split) 30 Lab 15 Project Seminar Tutorial (voluntary)

Max. capacity Exercise (unsplit) Exercise (split) 40 Lab 18 Project Seminar

Total effort (hours): 150

Instruction language

• German

Study Level

• undergraduate

Prerequisites

• 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

Instructors

• Prof.Dr.Dettmar

Supporting Scientific Staff

• Dipl.-Ing. Seckler

Transcipt Entry

source and channel coding

Assessment

Type
oE	Regelfall (bei großer prüfungszahl sK)

Total effort [hours]
wE	10

Frequency: 2 per year

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Course components

Lecture/Exercise

Objectives

Contents

• 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

Lab

Objectives

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

Type
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