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6.451 Principles of Digital Communications II

6.451 Principles of Digital Communications II (Spring 2005, MIT OCW). Instructor: Professor David Forney. This course is the second of a two-term sequence with 6.450. The focus is on coding techniques for approaching the Shannon limit of additive white Gaussian noise (AWGN) channels, their performance analysis, and design principles. After a review of 6.450 and the Shannon limit for AWGN channels, the course begins by discussing small signal constellations, performance analysis and coding gain, and hard-decision and soft-decision decoding. It continues with binary linear block codes, Reed-Muller codes, finite fields, Reed-Solomon and BCH codes, binary linear convolutional codes, and the Viterbi algorithm. (from ocw.mit.edu)

Lecture 10 - Reed-Solomon Codes


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Lecture 01 - Introduction, Sampling Theorem
Lecture 02 - Performance of Small Signal Constellations
Lecture 03 - Hard-decision and Soft-decision Decoding
Lecture 04 - Hard-decision and Soft-decision Decoding
Lecture 05 - Introduction to Binary Block Codes
Lecture 06 - Introduction to Binary Block Codes
Lecture 07 - Introduction to Finite Fields
Lecture 08 - Introduction to Finite Fields
Lecture 09 - Introduction to Finite Fields
Lecture 10 - Reed-Solomon Codes
Lecture 11 - Reed-Solomon Codes
Lecture 12 - Reed-Solomon Codes
Lecture 13 - Introduction to Convolutional Codes
Lecture 14 - Introduction to Convolutional Codes
Lecture 15 - Trellis Representations of Binary Linear Block Codes
Lecture 16 - Trellis Representations of Binary Linear Block Codes
Lecture 17 - Codes on Graphs
Lecture 18 - Codes on Graphs
Lecture 19 - The Sum-Product Algorithm
Lecture 20 - Turbo, LDPC, and RA Codes
Lecture 21 - Turbo, LDPC, and RA Codes
Lecture 22 - Lattice and Trellis Codes
Lecture 23 - Lattice and Trellis Codes
Lecture 24 - Linear Gaussian Channels
Lecture 25 - Linear Gaussian Channels