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.
Class Times and Locations
Tue-Thu 12:50PM - 2:05PM
Building 540, Room 108
First lecture on Tue, April 3
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