| Description
| 1. Introduction
2. Mathematical Preliminaries
- Probability
- Random processes: autocorrelation function and power spectral density, Gaussian processes, white noise
- Orthonormal expansions and linear filtering
- Sampling and quantization
3. Optimal Receiver Design
- Geometric interpretation of signals
- MAP and ML receiver principles
- Matched filters
- Probability of error
4. Digital Modulation and Multiplexing
- Digital modulation: ASK, PSK, QAM, FSK
- Digital modulation tradeoffs: error probability, power, bandwidth and complexity
- Multiplexing: FDMA, TDMA and CDMA
5. Introduction to Information Theory
- Source coding and entropy
- Channel coding and capacity
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