Principles of Digital Communications I

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3 STUDENTS

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 -High rate quantizers and waveform encoding – Measure, fourier series, and fourier transforms – Discrete – time fourier transforms and sampling theorem – Degrees of freedom, orthonormal expansions, and aliasing – Signal space, projection theorem, and modulation – Nyquist theory, pulse amplitude modulation (PAM), quadrature amplitude modulation (QAM), and frequency translation-Random processes

Jointly Gaussian random vectors and processes and white Gaussian noise (WGN) – Linear functionals and filtering of random processes – Review; introduction to detection – Detection for random vectors and processes – Theorem of irrelevance, M-ary detection, and coding – Baseband detection and complex Gaussian processes – Introduction of wireless communication – Doppler spread, time spread, coherence time, and coherence frequency – Discrete-time baseband models for wireless channels – Detection for flat rayleigh fading and incoherent channels, and rake receivers – Case study � code division multiple access (CDMA)

Course Curriculum

Introduction: A layered view of digital communication Details 1:19:36
Discrete source encoding Details 1:19:15
Memory-less sources, prefix free codes, and entropy Details 1:9:26
Entropy and asymptotic equipartition property Details 1:21:19
Markov sources and Lempel-Ziv universal codes Details 1:18:58
Quantization Details 1:19:32
High rate quantizers and waveform encoding Details 1:20:1
Measure, fourier series, and fourier transforms Details 1:19:29
Discrete-time fourier transforms and sampling theorem Details 1:16:45
Degrees of freedom, orthonormal expansions, and aliasing Details 1:18:28
Signal space, projection theorem, and modulation Details 1:22:38
Nyquist theory, pulse amplitude modulation (PAM), quadrature amplitude modulation (QAM), and frequency translation Details 1:20:55
Random processes Details 1:15:6
Jointly Gaussian random vectors and processes and white Gaussian noise (WGN) Details 1:20:34
Linear functionals and filtering of random processes Details 1:18:4
Review; introduction to detection Details 1:12:1
Detection for random vectors and processes Details 1:8:1
Theorem of irrelevance, M-ary detection, and coding Details 1:12:39
Baseband detection and complex Gaussian processes Details 1:16:34
Introduction of wireless communication Details 1:16:28
Doppler spread, time spread, coherence time, and coherence frequency Details 1:16:40
Discrete-time baseband models for wireless channels Details 1:10:56
Detection for flat rayleigh fading and incoherent channels, and rake receivers Details 1:4:13
Case study — code division multiple access (CDMA) Details 1:9:30

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