MCSE- 202 Information theory, coding and cryptography

Unit1. Information Theory, Probability and Channel: Introduction, Information Measures, Review

probability theory, Random variables, Processes, Mutual Information, Entropy, Uncertainty, Shannon's

theorem, redundancy, Huffman Coding, Discrete random Variable. Gaussian random variables, Bounds

on tail probabilities.

Unit.2 Stochastic Processes: Statistical independence, Bernoulli Process, Poisson Process, Renewal

Process, Random Incidence, Markov Modulated Bernoulli Process, Irreducible Finite Chains with

Aperiodic States, Discrete-Time Birth-Death Processes, Markov property, Finite Markov Chains,

Continuous time Markov chain, Hidden Markov Model.

Unit 3. Error Control Coding: Channel Coding: Linear Block Codes: Introduction, Matrix description,

Decoding, Equivalent codes, Parity check matrix, Syndrome decoding, Perfect codes Hamming Codes

,Optimal linear codes ,.Maximum distance separable (MDS) codes. Cyclic Codes: Introduction,

generation, Polynomials, division algorithm, Matrix description of cyclic codes, burst error correction, Fire

Codes, Golay Codes, and CRC Codes. BCH Codes: Introduction, Primitive elements, Minimal

polynomials, Generator Polynomials in terms of Minimal Polynomials, Decoding of BCH codes.

Unit.4 Coding for Secure Communications: Review of Cryptography, Introduction, Encryption

techniques and algorithms, DES, IDEA , RC Ciphers ,RSA Algorithm ,Diffi-Hellman, PGP, Chaos

Functions, Cryptanalysis, Perfect security, Unicity distance, Diffusion and confusion, McEliece

Cryptosystem

Unit.5 Advance Coding Techniques: Reed-Solomon codes, space time codes, concatenated codes,

turbo coding and LDPC codes (In details), Nested Codes, block (in Details), Convolutional channel

coding: Introduction, Linear convolutional codes, Transfer function representation & distance properties,

Decoding convolutional codes( Soft-decision MLSE, Hard-decision MLSE),The Viterbi algorithm for

MLSE, Performance of convolutional code decoders, Soft & Hard decision decoding performance, Viterbi

algorithm implementation issues: RSSE, trellis truncation, cost normalization, Sequential decoding:

Stack, Fano, feedback decision decoding, Techniques for constructing more complex convolutional

codes with both soft and hard decoding.

Text Books and References:

1. Rajan Bose “Information Theory, Coding and Cryptography”, TMH, 2002.

2. Kishor S. Trivedi “Probability and Statistics with Reliability, Queuing and Computer Science

Applications”, Wiley India, Second Edition.

3. J.C.Moreira, P.G. Farrell “Essentials of Error-Control Coding”, Willey Student Edition

4. San Ling and Chaoping “Coding Theory: A first Course”, Cambridge University Press, 2004.

5. G A Jones J M Jones, “Information and Coding Theory”, Springer Verlag, 2004.

6. Cole, “Network Security”, Bible, Wiley INDIA, Second Addition

7. Proakis and Masoud, “Digital Communication” ,McGraw-Hill ,2008