Information and Coding Theory

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Course Code: 
Course Outline: 
Department of Telecommunication Engineering
Information & Coding Theory (69461)
Total Credits3
major compulsory
PrerequisitesP1 : Digital Communications (69342) 
P2 : Statistical Methods & Probabilities for Engineers (21230) OR Random Variables & Probability (69233)
Course Contents
This course discusses the concept of information and coding theory, discrete sources and entropy, Shannon’s Theorem, channel capacity, source and channel coding, dictionary code and arithmetic code, encryption and error correction
Intended Learning Outcomes (ILO's)Student Outcomes 
1Argue some source coding/encryption techniques E 35 %
2Classify error control coding techniques B 35 %
3Prepare related research G 30 %
Textbook and/ or Refrences
1. Digital Communications: Glover & Ian, Pearson education, 2nd edition, 2004 
2. Communication Systems: Simon Haykin, Wiley, 4th edition, 2000 
3. Online Resources
Assessment CriteriaPercent (%)
Mid. Term Exam25 %
Projects25 %
Final Exam50 %
Course Plan
1Elements of digital communication system
2Information, uncertainty and entropy.
3Redundancy and information loss, discrete memory less source.
4Transition matrix and binary symmetric channel.
5Source coding theorem and efficiency
6Shannon Fane Coding
7Huffman coding
8Midterm exam
9Lempel Ziv coding
10Some source coding examples and bit rate.
11Data encryption principles(what, where and why)
12Types of encryption(public key and private key)
13Channel Coding Principles
15Channel Coding Principles
16Final Exam