Catalog

Principles of Digital Communications I

Electrical Engineering and Computer Science MIT CC BY-NC-SA 4.0 24 lectures

The course serves as an introduction to the theory and practice behind many of today's communications systems. 6.450 forms the first of a two-course sequence on digital communication. The second class, 6.451, is offered in the spring. Topics covered include: digital communications at the block diagram level, data compression, Lempel-Ziv algorithm, scalar and vector quantization, sampling and aliasing, the Nyquist criterion, PAM and QAM modulation, signal constellations, finite-energy waveform spaces, detection, and modeling and system design for wireless communication.

Syllabus

  1. 1 Lecture 1: Introduction
  2. 2 Lecture 2: Discrete Source Encoding
  3. 3 Lecture 3: Memory-less Sources
  4. 4 Lecture 4: Entropy and Asymptotic Equipartition Property
  5. 5 Lecture 5: Markov Sources
  6. 6 Lecture 6: Quantization
  7. 7 Lecture 7: High Rate Quantizers and Waveform Encoding
  8. 8 Lecture 8: Measure
  9. 9 Lecture 9: Discrete-Time Fourier Transforms
  10. 10 Lecture 10: Degrees of Freedom
  11. 11 Lecture 11: Signal Space
  12. 12 Lecture 12: Nyquist Theory
  13. 13 Lecture 13: Random Processes
  14. 14 Lecture 14: Jointly Gaussian Random Vectors
  15. 15 Lecture 15: Linear Functionals
  16. 16 Lecture 16: Review; Introduction to Detection
  17. 17 Lecture 17: Detection for Random Vectors and Processes
  18. 18 Lecture 18: Theory of Irrelevance
  19. 19 Lecture 19: Baseband Detection
  20. 20 Lecture 20: Introduction of Wireless Communication
  21. 21 Lecture 21: Doppler Spread
  22. 22 Lecture 22: Discrete-Time Baseband Models for Wireless Channels
  23. 23 Lecture 23: Detection for Flat Rayleigh Fading and Incoherent Channels
  24. 24 Lecture 24: Case Study on Code Division Multiple Access

Course materials