Sources - memory less and Markov; Information; Entropy; Extended sources; Shannon’s noiseless coding theorem; Source coding; Mutual information; Channel capacity; BSC and other channels; Shannon's channel capacity theorem; Continuous channels; Comparison of communication systems based on Information Theory; Channel Coding - block and convolutional. Block codes majority logic decoding; Viterbi decoding algorithm; Coding gains and performance.

Same as Reference

1. Shu Lin & Daniel J. Costello.Jr., Error Control Coding : Fundamentals and Applications, Prentice Hall Inc., Englewood Cliffs, NJ.

2. Thomas M. Cover, Joy A. Thomas, Elements of Information theory, 2nd ed., John Wiley & Sons Pvt. Ltd.

3. Simon Haykin. Communication Systems, 3rd ed., John Wiley & Sons Pvt. Ltd.

4. Taub & Schilling. Principles of Communication Systems, 2nd ed., TataMcGraw Hill, New Delhi.

5. Das, Mullick& Chatterjee. Principles of Digital Communication, Wiley Eastern Ltd.

6. The theory of error‐correcting codes by F. J. Mac Williams and N. J. A. Sloane (North‐ Holland publishers).

7. Algebraic codes for data transmission by Richard Blahut (Cambridge).

Course Outcomes (COs):

CO1: Understand the theoretical bounds and the limitation of communication system

CO2: Design lossless and lossy source coding techniques

CO3: Ability to design a channel coding scheme for the specific error correction capability of the communication system