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18.413 Error-Correcting Codes Laboratory, Spring 2004

Graph of density evolution of LDPC code on BEC.
Graph of density evolution of LDPC code on BEC. (Image courtesy of Prof. Daniel Spielman.)

Highlights of this Course

This course includes extensive lecture notes that summarize the topics discussed and analyzed in class, as well as projects sections.

Course Description

This course introduces students to iterative decoding algorithms and the codes to which they are applied, including Turbo Codes, Low-Density Parity-Check Codes, and Serially-Concatenated Codes. The course will begin with an introduction to the fundamental problems of Coding Theory and their mathematical formulations. This will be followed by a study of Belief Propagation--the probabilistic heuristic which underlies iterative decoding algorithms. Belief Propagation will then be applied to the decoding of Turbo, LDPC, and Serially-Concatenated codes. The technical portion of the course will conclude with a study of tools for explaining and predicting the behavior of iterative decoding algorithms, including EXIT charts and Density Evolution.
 

Staff

Instructor:
Prof. Daniel Spielman

Course Meeting Times

Lectures:
Two sessions / week
1.5 hours / session

Level

Undergraduate

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