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Massachusetts Institute of Technology

Principles of Digital Communication II

Massachusetts Institute of Technology via MIT OpenCourseWare

Overview

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.

Syllabus

  • chap_1.pdf
  • chap1_3.pdf
  • Lecture 1: Introduction Sampling Theorem
  • chap_2.pdf
  • Lecture 2: Performance of Small Signal Constellations
  • chap_3.pdf
  • Lecture 3: Hard-decision and Soft-decision Decoding
  • chap4.pdf
  • Lecture 4: Hard-decision and Soft-decision Decoding
  • chap_5.pdf
  • Lecture 5: Introduction to Binary Block Codes
  • chap6.pdf
  • Lecture 6: Introduction to Binary Block Codes
  • chap7.pdf
  • Lecture 7: Introduction to Finite Fields
  • chap8.pdf
  • Lecture 8: Introduction to Finite Fields
  • chap9.pdf
  • Lecture 9: Introduction to Finite Fields
  • chap10.pdf
  • Lecture 10: Reed-Solomon Codes
  • chap11.pdf
  • Lecture 11: Reed-Solomon Codes
  • chap12.pdf
  • Lecture 12: Reed-Solomon Codes
  • chap13.pdf
  • Lecture 13: Introduction to Convolutional Codes
  • chap14.pdf
  • 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

Taught by

Prof. David Forney

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