About
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.
Recommended Citation
For any use or distribution of these materials, please cite as follows:
Robert Gallager and Lizhong Zheng, course materials for 6.450 Principles of Digital Communications I, Fall 2006.
Course Homepage: 6.450 Principles of Digital Communications I Fall 2006
Course features at MIT OpenCourseWare page: *Syllabus *Lecture Notes *Assignment *Exams *Download Course Materials
Complete MIT OCW video collection at MIT OpenCourseWare - VideoLectures.NET
Uploaded videos:
Lecture 1: Introduction: A layered view of digital communication
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Lecture 2: Discrete source encoding
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Lecture 3: Memory-less sources, prefix free codes, and entropy
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Lecture 4: Entropy and asymptotic equipartition property
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Lecture 5: Markov sources and Lempel-Ziv universal codes
Apr 16, 2009
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Lecture 6: Quantization
Apr 16, 2009
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Lecture 7: High rate quantizers and waveform encoding
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Lecture 8: Measure, fourier series, and fourier transforms
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Lecture 9: Discrete-time fourier transforms and sampling theorem
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Lecture 10: Degrees of freedom, orthonormal expansions, and aliasing
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Lecture 11: Signal space, projection theorem, and modulation
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Lecture 12: Nyquist theory, pulse amplitude modulation (PAM), quadrature amplitu...
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Lecture 13: Random processes
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Lecture 14: Jointly Gaussian random vectors and processes and white Gaussian noi...
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Lecture 15: Linear functionals and filtering of random processes
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Lecture 16: Review; introduction to detection
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Lecture 17: Detection for random vectors and processes
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Lecture 18: Theorem of irrelevance, M-ary detection, and coding
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Lecture 19: Baseband detection and complex Gaussian processes
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Lecture 20: Introduction of wireless communication
Apr 16, 2009
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Lecture 21: Doppler spread, time spread, coherence time, and coherence frequency
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Lecture 22: Discrete-time baseband models for wireless channels
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Lecture 23: Detection for flat rayleigh fading and incoherent channels, and rake...
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Lecture 24: Case study — code division multiple access (CDMA)
Apr 16, 2009
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4882 Views