Digital Communications and Systems Lab

Undergraduate Program: Department of Informatics and Telecommunications, University of Peloponnese

Category: Specialization in Telecommunications-Elective

ECTS credits: 5

Semester: 6^th

Prerequisites: Probabilities and Statistics

Learning outcomes

By the end of this course students will:

• Evaluate the discrete source entropy
• Explain 1^st and 2^nd Shannon coding theorem
• Recognize and categorize source codes
• Perform data compression
• Evaluate the mutual information and the discrete channel capacity
• Explain the motivation for source and channel coding
• Encode and decode linear block codes and cyclic codes

Contents

Introduction, entropy, joint entropy, mutual information, information rate, redundancy, discrete message sources, memoryless sources, Markov sources, source coding, Huffman coding, communication channels, discrete channel capacity, continuous channel capacity, Galois field GF(2), linear block codes, Hamming codes, cyclic codes, systematic codes, BCH and CRC codes, burst error correcting codes.

Assessment

Written exams at the end of the semester. Given projects have 30%-40% weight on the total course grade.

Bibliography

1. Thomas M. Cover and Joy A. Thomas, Elements of Information Theory, 2nd edition, 2006. DOI: 10.1002/047174882X
2. S. Haykin και M. Moher, Communication Systems, 5^th Edition,  November 2008, ISBN: 978-0-470-46088-7