The expression ‘modern coding theory’ refers to a broad family of coding techniques and decoding algorithms that have been developed over the last twenty years. These techniques allow to achieve the information-theoretic limits of reliable communication and data storage in many settings, while keeping computational complexity under control.
Three unifying themes in modern coding theory are the use of sparse-graph constructions, iterative message-passing decoding algorithms, and probabilistic designs/analysis methods. All of these ideas have far-reaching applications beyond chanel coding.
This class presents the basic tools for analysis and optimization of iterative coding systems. Introduces several code ensembles: LDPC, Turbo, RA, Fountain codes. Discusses optimized ensembles, message passing algorithms, density evolution.