Principles of Digital Communications free videos and free material uploaded by Massachusetts Institute of Technology Staff .
Introduction: A layered view of digital
communication
Discrete source encoding
Memory-less sources, prefix free codes, and
entropy
Entropy and asymptotic equipartition property
Markov sources and Lempel-Ziv universal codes
Quantization
7High rate quantizers and waveform encoding
8Measure, fourier series, and fourier
transforms
9Discrete-time fourier transforms and sampling
theoremQuiz 1 taken 2 days after Ses #9
10Degrees of freedom, orthonormal expansions,
and aliasing
11Signal space, projection theorem, and
modulation
12Nyquist theory, pulse amplitude modulation
(PAM), quadrature amplitude modulation (QAM), and frequency translation
13Random processes
14Jointly Gaussian random vectors and processes
and white Gaussian noise (WGN)
15Linear functionals and filtering of random
processes
16Review; introduction to detectionQuiz 2 taken
2 days after Ses #16
17Detection for random vectors and processes
18Theorem of irrelevance, M-ary detection, and
coding
19Baseband detection and complex Gaussian
processes
20Introduction of wireless communication
21Doppler spread, time spread, coherence time,
and coherence frequency
22Discrete-time baseband models for wireless
channels
23Detection for flat rayleigh fading and
incoherent channels, and rake receivers
24Case study — code division multiple access
(CDMA)
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.
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