Author Information
Course Code:
69461
Course Outline:
| Department of Telecommunication Engineering | ||||||
| Information & Coding Theory (69461) | ||||||
| Total Credits | 3 | |||||
| major compulsory | ||||||
| Prerequisites | P1 : 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 | ||||||
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| 1 | Argue some source coding/encryption techniques | E | 35 % | |||
| 2 | Classify error control coding techniques | B | 35 % | |||
| 3 | Prepare 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 | ||||||
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| Mid. Term Exam | 25 % | |||||
| Projects | 25 % | |||||
| Final Exam | 50 % | |||||
| Course Plan | ||||||
|---|---|---|---|---|---|---|
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| 1 | Elements of digital communication system | |||||
| 2 | Information, uncertainty and entropy. | |||||
| 3 | Redundancy and information loss, discrete memory less source. | |||||
| 4 | Transition matrix and binary symmetric channel. | |||||
| 5 | Source coding theorem and efficiency | |||||
| 6 | Shannon Fane Coding | |||||
| 7 | Huffman coding | |||||
| 8 | Midterm exam | |||||
| 9 | Lempel Ziv coding | |||||
| 10 | Some source coding examples and bit rate. | |||||
| 11 | Data encryption principles(what, where and why) | |||||
| 12 | Types of encryption(public key and private key) | |||||
| 13 | Channel Coding Principles | |||||
| 14 | Midterm | |||||
| 15 | Channel Coding Principles | |||||
| 16 | Final Exam | |||||
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