Information Theory G

Course aim

The course presents concepts of information theory and their application to modern communication systems.

Course content

The course presents an introduction to the area of information theory. The course starts with a detailed introduction to information-theoretic tools and concepts. It is then followed by the study of fundamental limits of source and channel coding. Finally, rate regions of network information theory are explored. The outline of the course contents are as follows:

• Random Variables and Processes, Entropy, Mutual Information, Kullback-Leibler Divergence, Data Processing Inequality and Fano’s inequality
• Weak law of large numbers, Weak Typicality, Strong Typicality, and Lossless Source Coding Theorem.
• Entropy Rates of Random Processes, and Source Coding for Processes with Memory
• Rate-Distortion Theory, Computation of Rate-Distortion functions
• Channel Coding Theorem
• Multi-User Information Theory: Slepian-Wolf Problem, Wyner-Ziv Problem, Coditional Rate-Distortion Problem, Multi-Access Channels and Broadcast Channels.

Textbook(s)

Thomas M. Cover 2006, Elements of Information Theory, 2, Wiley-Interscience

Prerequisite(s)

Basic understanding of probability theory is required. Knowledge of communication theory would be advantageous.

Corequisite(s)

Nil

Teaching method

Component	Duration
INTERNAL, MAWSON LAKES
Lecture	2 hours x 13 weeks
Tutorial	1 hours x 13 weeks

Note: These components may or may not be scheduled in every study period. Please refer to the timetable for further details.

Assessment

Assignments (6), Examination

Fees

EFTSL*: 0.125
Commonwealth Supported program (Band 2)
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Fee-paying program for domestic and international students
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Non-award enrolment
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* Equivalent Full Time Study Load. Please note: all EFTSL values are published and calculated at ten decimal places. Values are displayed to three decimal places for ease of interpretation.