COURSE UNIT TITLE

: CODING THEORY

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EED 4006 CODING THEORY ELECTIVE 3 0 0 6

Offered By

Electrical and Electronics Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR REYAT YILMAZ

Offered to

Electrical and Electronics Engineering

Course Objective

The objective of this course is to introduce the students the basics of information theory, effective source information representation and source coding, the concept of error correcting codes and the necessity of channel coding. In this context, encoding and decoding techniques of linear block codes and convolutional codes will be presented. By the end of this course the students will have the vision about information theory and coding and be prepared for a graduate level of similar courses.

Learning Outcomes of the Course Unit

1   To be able to represent the data generated by a discrete source efficiently
2   To be able to define and use some data compression techniques
3   To be able to know the problems ocur in the transmission channel
4   To be able to get rid of the problem by using error correcting codes
5   To be able to improve the existing error correcting codes

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Shannon's source coding theorem, channel coding theorem
2 Shannon's channel capacity theorem
3 Source coding, Huffman coding, prefix coding, Arithmetic coding
4 Linear block codes, encoding, Hamming codes
5 Decoding of linear block codes,
6 Error rate performance bounds for linear block codes.
7 Midterm 1
8 Definition, generation and properties of cyclic codes, Decoding of cyclic codes
9 Definition of convolutional codes and structural properties, Punctured convolutional codes
10 Viterbi decoding algorithm
11 Trellis coded modulation, systematic recursive convolutional encoders
12 Midterm 2
13 Signal mapping and set partitioning
14 Known good trellis codes for PSK and QAM

Recomended or Required Reading

Main reference: Applied Coding and Information Theory for Engineers, R.B. Wells, Prentice Hall.
Supplementary References: Error Control Systems for Digital Communication and Storage, S.B. Wicker, Prentice Hall.
Lecture Notes

Planned Learning Activities and Teaching Methods

Lectures will be supported by regularly assigned homeworks , recitation hours, and a simulation/research project that will be presented by the end of the course.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.50 + FIN * 0.50
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.50 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Learning outcomes are evaluated by homeworks and exam questions.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

reyat.yilmaz@deu.edu.tr

Office Hours

will be posted

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Presentations 14 3 42
Weekly pre/post lecture preparation (reading lecture notes, papers, etc.) 14 3 42
Preparation for midterm exam 1 15 15
Preparation for final exam 1 20 20
Homework preparation 5 5 25
Presentation preparation 1 5 5
Final Exam 1 2 2
Midterm Exam 1 2 2
TOTAL WORKLOAD (hours) 153

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13
LO.1331
LO.233
LO.344
LO.4441
LO.544121