Principles of Digital Communications I

MIT Course , Fall 2006 , Prof. Robert Gallager and Prof. Lizhong Zheng

333 students enrolled

Overview

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)

Lecture 6: Quantization

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