# 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

ASISTANT 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

Face -to- Face

#### Prerequisites and Co-requisites

EED 4101 - DIGITAL COMMUNICATION

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

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.

None

#### Assessment Criteria

Learning outcomes are evaluated by homeworks and exam questions.

English

To be announced.

#### Contact Details for the Lecturer(s)

reyat.yilmaz@deu.edu.tr

will be posted

None