ACADEMICS
Course Details

ELE638 - Fundamentals of Coding Theory

2024-2025 Fall term information
The course is not open this term
ELE638 - Fundamentals of Coding Theory
Program Theoretıcal hours Practical hours Local credit ECTS credit
MS 3 0 3 8
Obligation : Elective
Prerequisite courses : -
Concurrent courses : -
Delivery modes : Face-to-Face
Learning and teaching strategies : Lecture, Question and Answer, Problem Solving
Course objective : The 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 : Learn and use the main algebraic tools utilized in coding theory Learn coding and decoding methods for fundamental block and convolutional codes Learn analysis tools for fundamental block and convolutional codes Learn message passing algorithms defined on graphs 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
References : Wicker 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
Weeks Topics
1 Source and channel coding basics, complexity, bounds
2 Algebra review
3 Polynomials over Galois fields
4 Linear block codes structure, Hamming codes
5 BCH codes
6 Reed-Solomon codes
7 Convolutional codes
8 Midterm Exam
9 Concatenated codes
10 Elements of graph theory
11 Algorithms on graphs
12 Turbo decoding
13 Low-density parity check codes
14 Project presentations
15 Final exam
16 Final exam
Assessment Methods
Course activities Number Percentage
Attendance 0 0
Laboratory 0 0
Application 0 0
Field activities 0 0
Specific practical training 0 0
Assignments 1 10
Presentation 1 10
Project 0 0
Seminar 0 0
Quiz 0 0
Midterms 1 30
Final exam 1 50
Total 100
Percentage of semester activities contributing grade success 50
Percentage of final exam contributing grade success 50
Total 100
Workload and ECTS Calculation
Course activities Number Duration (hours) Total workload
Course Duration 14 3 42
Laboratory 0 0 0
Application 0 0 0
Specific practical training 0 0 0
Field activities 0 0 0
Study Hours Out of Class (Preliminary work, reinforcement, etc.) 14 7 98
Presentation / Seminar Preparation 1 10 10
Project 1 25 25
Homework assignment 1 10 10
Quiz 0 0 0
Midterms (Study duration) 0 0 0
Final Exam (Study duration) 1 25 25
Total workload 32 80 210
Matrix Of The Course Learning Outcomes Versus Program Outcomes
Key learning outcomes Contribution level
1 2 3 4 5
1. Has general and detailed knowledge in certain areas of Electrical and Electronics Engineering in addition to the required fundamental knowledge.
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.
3. Follows and interprets scientific literature and uses them efficiently for the solution of engineering problems.
4. Designs and runs research projects, analyzes and interprets the results.
5. Designs, plans, and manages high level research projects; leads multidiciplinary projects.
6. Produces novel solutions for problems.
7. Can analyze and interpret complex or missing data and use this skill in multidiciplinary projects.
8. Follows technological developments, improves him/herself , easily adapts to new conditions.
9. Is aware of ethical, social and environmental impacts of his/her work.
10. Can present his/her ideas and works in written and oral form effectively; uses English effectively.
1: Lowest, 2: Low, 3: Average, 4: High, 5: Highest