Principles of Digital Communications I (M-I-T)

Baseband detection and complex Gaussian processes (M-I-T)

Case study — code division multiple access (CDMA) (M-I-T)

Degrees of freedom, orthonormal expansions, and aliasing (M-I-T)

Detection for flat rayleigh fading and incoherent channels, and rake receivers (M-I-T)

Detection for random vectors and processes (M-I-T)

Discrete source encoding (M-I-T)

Discrete-time baseband models for wireless channels (M-I-T)

Discrete-time fourier transforms and sampling theorem (M-I-T)

Doppler spread, time spread, coherence time, and coherence frequency (M-I-T)

Entropy and asymptotic equipartition property (M-I-T)

High rate quantizers and waveform encoding (M-I-T)

Introduction of wireless communication (M-I-T)

Introduction: A layered view of digital communication (M-I-T)

Jointly Gaussian random vectors and processes and white Gaussian noise (WGN) (M-I-T)

Linear functionals and filtering of random processes (M-I-T)

Markov sources and Lempel-Ziv universal codes (M-I-T)

Measure, fourier series, and fourier transforms (M-I-T)

Memory-less sources, prefix free codes, and entropy (M-I-T)

Nyquist theory, pulse amplitude modulation (PAM), quadrature amplitude modulation (QAM), and frequency translation (M-I-T)

Quantization (M-I-T)

Random processes (M-I-T)

Review: introduction to detection (M-I-T)

Signal space, projection theorem, and modulation (M-I-T)

Theorem of irrelevance, M-ary detection, and coding (M-I-T)