Stanford University

EE 388
Modern Coding Theory
Spring 2009–10

Course Information

Class Times and Locations

  • Tuesdays and Thursdays, 12:35-02:05 PM in Room: 380-380D

Course Description

Tools for analysis and optimization of iterative coding systems. LDPC, turbo and RA codes. Optimized ensembles, message passing algorithms, density evolution, and analytic techniques.

References

The course is mainly based on

Additional references are

Prerequisites

The prerequisite mentioned in the bulletin is EE376A (Information Theory.) If you did not take EE376A, this is not a problem. On the other hand, it is important to know some basic probability (say, enough probability for understanding a proof of the central limit theorem.)

Instructors

Grading

Each week will be devoted to solving one concrete problem in code design (theory will be developed whenever requested for moving forward.) There will be a weekly homework (except in the last 3 weeks.) This will be a small implementation exercise based on the problem discussed in class. Implementations can be realized in C, C++, Matlab, Mathematica... There will be also a final project, which will consist in designing a code under some constraints.

Grading will be assigned according to: 35% for attendance, 35% for homework, 30% for final project.


Handouts

Handout Posted
Syllabus [pdf] 3/27
Final project [project description][reports] 5/11
T. Richardson, Error floors of LDPC codes 5/20
G. Ungerboeck Trellis-coded modulation with redundant signal sets 5/20

Lecture notes and homeworks

We provide the solution in C. There can be many different (and better) ways of implementing the same decoding algorithms.

Handout Posted Due Solution
Lecture 1-2, Homework 1 [pdf] 3/27 4/06 [tar.gz]
Lecture 3-4, Homework 2 [pdf] 4/05 4/13 [tar.gz]
Lecture 5-6, Homework 3 [pdf] 4/12 4/20 [tar.gz]
Lecture 7-8, Homework 4 [pdf] 4/19 4/27 [tar.gz]
Lecture 9-10, Homework 5 [pdf] 4/26 5/4 [tar.gz]
Lecture 11-12, Homework 6 [pdf] 5/4 5/11 [tar.gz]