Channel Coding

Course Name: Information Theory II (Channel Coding)

Instructor: Dr. Afrooz Haghbin

Level: Graduate

Course Meeting Times: 3 Hours / Week

 Prerequisites: Stochastic Processes.

 

Course Description


     Channel coding is one of the effective methods help reaching the channel capacity. In this course, first, the mathematical principles required to discuss the channel coding concept are presented. Then, some common channel codes like BCH codes, Reed-solomon codes and convolutional codes are presented. Code concatenation is a method to help improving the system performance, so it will be discussed in this course. LDPC codes and Turbo codes are two famous codes in the group of iterative codes that can reach channel capacity. These codes will also be discussed in this course if time permit. 

Course Description (Farsi)

 

Course Syllabus


     1- Overview

    2- A review on Linear Algebra

    3- Linear Block Codes

    4- Cyclic Codes

    5- BCH Codes

    6- Reed-Solomon Codes

    7- Convolutional Codes

    8- Concatenation Codes

    9- LDPC and Turbo Codes

 

Course Evaluation


    Midterm Exam                 40%

    Final Exam                       40%

    Homework                      10%

    Simulation Homework     10%

 

References


 [1] Shu Lin, and D. J. Costello, Jr., Error Control Coding: Fundamentals and Applications,  Prentice-Hall, 1983.Download.

[2] Blahut, Richard E., Theory and Practice of Error Control Codes, Addison-Wesley, 1983.

[3] Blahut, Richard E., Algebraic Codes for Data Transmission, Cambridge University Press, 2003. (A revision of his 1983 book. Includes new material on turbo codes. Has a brief survey chapter on iterative decoding for codes described on graphs which is too condensed to be of much use.)

[4] Gallager, R.G., Information Theory and Reliable Communication, John Wiley & Sons, New York, 1968, Chapter 6. (An excellent introduction to cyclic codes. Sequential decoding of convolutional codes also analyzed.)

[5] S. Huffman, W. Cary, and Vera Pless, Fundamentals of Error-Correcting Codes, Cambridge University Press, 2003. Download.

[6] Viterbi, A.J., and J.K. Omura, Principles of Communication and Coding, McGraw-Hill, 1979. (A clear, detailed presentation of convolutional codes and the Viterbi decoding algorithm.)

[7] J. G. Proakis, and M. Salehi, Digital Communications, 5th Ed, McGraw Hill, 2007.

 


Lecture Notes

  • 96-97 (Fall)

Lecture 1

Lecture 2

Lecture 3

Lecture 4

Lecture 5

Lecture 6

Lecture 7

Lecture 8

Lecture 9

Lecture 10

Lecture 11

Lecture 12

Lecture 13


  • 95-96 (Spring)

Lecture 1

Lecture 2

Lecture 3

Lecture 4

Lecture 5

Lecture 6

Lecture 7

Lecture 8

Lecture 9

Lecture 10

Lecture 11

Lecture 12


  • 1394

Lecture 1

Lecture 2 

Lecture 3

Lecture 4

Lecture 5

Lecture 6

Lecture 7

Lecture 8

Lecture 9

Lecture 10

Lecture 11

Lecture 12

Lecture 13

Lecture 14

Lecture 15

 


Homeworks


    1- Homework No. 1. Download

    2- Homework No. 2. Download

    3- Homework No. 3. Download

    4- Homework No. 4. Download

    5- Homework No. 5. As defined in class

    6- Homework No. 6. Download

    7- Homework No. 7. Download