Table of Contents
Chapter 1: Essentials of Digital Communication
1.1 Introduction to Digital Communication
1.2 Sampling Theorem – Baseband Sampling
1.3 Sampling Theorem – Bandpass or Intermediate or Under Sampling
1.4 Oversampling, ADC – DAC Conversion, pulse shaping and Matched Filter
1.5 Channel Capacity
1.6 Performance of Channel Codes
1.7 Distances: Hamming Vs. Euclidean
1.8 Hard and Soft Decision Decoding
1.9 Maximum Likelihood Decoding
Chapter 2: Channel Coding
2.1 Hamming Codes - How it works
2.2 Construction of Hamming codes using matrices
2.3 Introduction to Reed Solomon Codes
2.4 Block Interleaver Design for RS codes
2.5 Convolutional Coding and Viterbi Decoding
Chapter 3: Inter Symbol Interference and Filtering
3.1 Introduction to controlled ISI (Inter Symbol Interference)
3.2 Correlative coding – Duobinary Signaling
3.3 Modified Duobinary Signaling
3.4 Raised Cosine Filter
3.5 Square Root Raised Cosine Filter (Matched/split filter implementation)
3.6 Gibbs Phenomena – A demonstration
3.7 Moving Average (MA) Filter
Chapter 4: Probability and Random Process
4.1 Introduction to concepts in probability
4.2 Bayes’ Theorem
4.3 Distributions and Density Functions
4.4 Gaussian random variable and Gaussian distribution
4.5 Uniform Random Variables and Uniform Distribution
4.6 Chi-Squared Random Variable and Chi-Squared Distribution
4.7 Non-central Chi-squared Distribution
4.8 Central Limit Theorem
4.9 Colored Noise Generation in Matlab
Chapter 5: Channel Models and Fading
5.1 Introduction to Channel models
5.2 Friis Free Space Propagation Model
5.3 Log Distance Path Loss or Log Normal Shadowing Model
5.4 Hata – Okumura Models
5.5 Introduction to Fading Models
