Courses – Fakultet tehničkih nauka u Novom Sadu

Subject: Modern Coding Theory (17.DE414)

Native organizations units: Department of Power, Electronic and Telecommunication Engineering

Type of studies	Title
Doctoral Academic Studies	Mathematics in Engineering (Godina: 1, Winter)
Doctoral Academic Studies	Power, Electronic and Telecommunication Engineering (Godina: 2, Winter)
Doctoral Academic Studies	Mathematics in Engineering (Godina: 2, Winter)

General information:

Category	Professional-applicative
Scientific or art field	Telecommunications and Signal Processing
Interdisciplinary	No
ECTS	10

Educational goal:

The aim of the course is to offer students an overview and understanding of the fundamental theories of modern coding theory with emphasis on the construction of codes on graphs and iterative decoding techniques. The course will also highlight the problems and present solutions in the design of error-correction codes and iterative decoders that reach the limit in the amount of data that can be transferred over channels with noise and which became part of modern communication system standards.

Educational outcome:

After the course the student should have the following skills: 1) Be familiar with the principles of probabilistic graphical model systems and algorithms on graphical models with emphasis on the Belief-Propagation (BP) algorithm, 2) Obtain an overview of iterative development solutions in the field of error correction coding with emphasis the Turbo and Low-Density Parity-Check (LDPC) codes and corresponding versions of iterative decoders 3) get a wider picture of the applicability of iterative processing techniques and the additional examples? domains of signal transmission such as iterative techniques of estimation, equalization, and so on. 4) Obtain an overview of new techniques of information protection at packet level based on iterative principles with emphasis on Digital Fountain (DF) codes 5) gain insight into the extension of the theory of reliable transmission of information to the scenario of a communication link to the network scenario with emphasis on network coding.

Course content:

Course content includes the following topics: 1) Basics of probabilistic graphical modelling of the system and the Belief-Propagation (BP) algorithm 2) The introduction of turbo codes and turbo codes decoding algorithm 3) Introduction to LDPC codes and LDPC codes decoding algorithm 4) Extending the theory of iterative processing to other elements of the transmission signal processing 5) codes for packet communications based on iterative principles: LT and Raptor codes 6) Introduction to network coding, 7) Introduction to Polar Codes, and 8) Short-packet error correction codes.

Teaching methods:

Lectures: (Mentor with the student chooses one or more modules, depending on the scope of the module). The theoretical part is followed by examples which serve to clarify the theoretical part of the curriculum. In addition to lectures, tutorial classes (consultations) are held regularly. Through research study, student makes an overview of scientific journals and other literature, and deepens on its own the curriculum provided through lectures. In addition to working with the teacher, the student is trained to write its own scientific work.

Literature:

Authors	Title	Year	Publisher	Language
T. Richardson, R. Urbanke	Modern Coding Theory	2008	Cambridge University Press	English
E. Soljanin, C. Fragouli	Network Coding: Fundamentals and Applications	2008	NOW Academic Publishers	English
Lin, S., Costello, D.	Error Control Coding : Fundamentals and Applications	2004	Pearson Prentice Hall, New York	English