6.451 Principles of Digital Communication II, Spring 2003
Name
6-451Spring-2003/OcwWeb/Electrical-Engineering-and-Computer-Science/6-451Spring-2003/CourseHome/index.htm
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16.28 KB
Format
HTML
Checksum (MD5)
096427a5443f97349a3c227f163db43a
Author(s)
Forney, G. David
Alternative Title
Principles of Digital Communication II
Date Issued
June 2003
Abstract
Coding for the AWGN channel; block and convolutional codes; lattice and trellis codes; capacity-approaching codes; equalization of linear Gaussian channels; linear, decision-feedback, and MLSD equalization; precoding; multicarrier modulation; and topics in wireless communication. Description from the course home page: 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. More advanced topics include trellis representations of binary linear block codes and trellis-based decoding; codes on graphs; the sum-product and min-sum algorithms; the BCJR algorithm; turbo codes, LDPC codes and RA codes; and performance of LDPC codes with iterative decoding. Finally, the course addresses coding for the bandwidth-limited regime, including lattice codes, trellis-coded modulation, multilevel coding and shaping. If time permits, it covers equalization of linear Gaussian channels.
Subjects
coding techniques
the Shannon limit of additive white Gaussian noise channels
Small signal constellations
performance analysis
coding gain
Hard-decision and soft-decision decoding
Introduction to binary linear block codes
Reed-Muller codes
finite fields
Reed-Solomon and BCH codes
binary linear convolutional codes
Viterbi and BCJR algorithms
Trellis representations of binary linear block codes
trellis-based ML decoding
Codes on graphs
sum-product
max-product
decoding algorithms
Turbo codes
LDPC codes and RA codes
Coding for the bandwidth-limited regime
Lattice codes
Trellis-coded modulation
Multilevel coding
Shaping
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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