Department of Electrical and Electronics Engineering

Course Details

ELE 638 Fundamentals of Coding Theory 2021-2022 Fall term information

The course is open this term
Place Day Hours Supervisor(s): Dr. Berkan Dülek SS Friday 09:00 - 11:45

Timing data are obtained using weekly schedule program tables. To make sure whether the course is cancelled or time-shifted for a specific week one should consult the supervisor and/or follow the announcements.

Course definition tables are extracted from the ECTS Course Catalog web site of Hacettepe University (http://akts.hacettepe.edu.tr) in real-time and displayed here. Please check the appropriate page on the original site against any technical problems. Course data last updated on 24/01/2022.

ELE638 - FUNDAMENTALS of CODING THEORY

Course Name Code Semester Theory
(hours/week)
Application
(hours/week)
Credit ECTS
FUNDAMENTALS of CODING THEORY ELE638 Any Semester/Year 3 0 3 8
Prerequisite(s)
Course languageTurkish
Course typeElective
Mode of DeliveryFace-to-Face
Learning and teaching strategiesLecture
Problem Solving

Instructor (s)Department Faculty
Course objectiveThe objective of the course is to introduce ? the notion of channel coding ? conventional and modern channel codes ? fundamentals of graph theory and codes on graphs
Learning outcomes
1. Learn and use the main algebraic tools utilized in coding theory
2. Learn coding and decoding methods for fundamental block and convolutional codes
3. Learn analysis tools for fundamental block and convolutional codes
4. Learn message passing algorithms defined on graphs
5. Learn codes on graphs, coding and iterative decoding methods for codes on graphs
Course Content? Introduction to algebra
? Linear block codes,
? Convolutional codes
? Concatenated codes
? Elements of graph theory
? Algorithms on graphs
? Turbo decoding
? Low density parity check codes

ReferencesWicker and Kim, Fundamentals of codes, graphs, and iterative decoding, 2003.
Lin and Costello, Error control coding, second ed. 2004.
Richardson and Urbanke, Modern coding theory, 2008.

Course outline weekly

WeeksTopics
Week 1Source and channel coding basics, complexity, bounds
Week 2Algebra review
Week 3Polynomials over Galois fields
Week 4Linear block codes structure, Hamming codes
Week 5BCH codes
Week 6Reed-Solomon codes
Week 7Convolutional codes
Week 8Midterm Exam
Week 9Concatenated codes
Week 10Elements of graph theory
Week 11Algorithms on graphs
Week 12Turbo decoding
Week 13Low-density parity check codes
Week 14Project presentations
Week 15Final exam
Week 16Final exam

Assesment methods

Course activitiesNumberPercentage
Attendance00
Laboratory00
Application00
Field activities00
Specific practical training00
Assignments110
Presentation110
Project00
Seminar00
Midterms130
Final exam150
Total100
Percentage of semester activities contributing grade succes050
Percentage of final exam contributing grade succes050
Total100

Workload and ECTS calculation

Activities Number Duration (hour) Total Work Load
Course Duration (x14) 14 3 42
Laboratory 0 0 0
Application000
Specific practical training000
Field activities000
Study Hours Out of Class (Preliminary work, reinforcement, ect)14798
Presentation / Seminar Preparation11010
Project12525
Homework assignment11010
Midterms (Study duration)000
Final Exam (Study duration) 12525

Matrix Of The Course Learning Outcomes Versus Program Outcomes

D.9. Key Learning OutcomesContrubition level*
12345
1. Has general and detailed knowledge in certain areas of Electrical and Electronics Engineering in addition to the required fundamental knowledge.    X
2. Solves complex engineering problems which require high level of analysis and synthesis skills using theoretical and experimental knowledge in mathematics, sciences and Electrical and Electronics Engineering.    X
3. Follows and interprets scientific literature and uses them efficiently for the solution of engineering problems.  X
4. Designs and runs research projects, analyzes and interprets the results.   X
5. Designs, plans, and manages high level research projects; leads multidiciplinary projects.  X
6. Produces novel solutions for problems.   X
7. Can analyze and interpret complex or missing data and use this skill in multidiciplinary projects.    X
8. Follows technological developments, improves him/herself , easily adapts to new conditions.    X
9. Is aware of ethical, social and environmental impacts of his/her work.X
10. Can present his/her ideas and works in written and oral form effectively; uses English effectivelyX

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest