Principles of digital communication

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