Simulation of Digital Communication Systems using MatlabSimulation of Digital Communication Systems Using Matlab [eBook]
Author: Mathuranathan Viswanathan
Published: Feb. 18, 2013
Language: English
ISBN : 9781301525089
Words: 57,050 (approximate)
Release date: 25 September 2013 (Second Edition)

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Simulation of Digital Communication Systems using Matlab


Description:
Are you interested in simulation of communication systems in Matlab and do not know where to start? If so, your search for a good text ends here. Some of the simulation topics include various digital modulation and channel coding techniques, OFDM, fading channels, random distributions .Essential topics in digital communication are also introduced to foster better understanding of simulation methodologies.

This ebook is meant for students and instructors who are interested in simulation of signal processing and digital communication with Matlab. You should have a fair understanding of Matlab programming to begin with. Essential topics in digital communication are introduced to foster understanding of simulation methodologies.

This second edition includes following new topics – propagation path models like – log normal shadowing, Hata-Okumura models, in-depth treatment of Shannon-Hartley equation and Channel Capacity calculation

Some of the key topics include: Sampling theorem, hard & soft decision decoding, Hamming codes, Reed Solomon codes, convolutional codes, Viterbi decoding, Inter symbol interference, Correlative coding, Raised cosine filter, Square Root Raised Cosine filter, Gibbs phenomenon, Moving average filter, Probability and random process, Chi-square, Gaussian, Uniform, Rician, Rayleigh distributions, demonstration of central limit theorem, Propagation models, fading models, digital modulation techniques, OFDM, spread spectrum.

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Table of Contents:

Table of Contents (click to expand)

  • 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
    • 5.6 Rayleigh Fading and Rayleigh Distribution
    • 5.7 Rayleigh Fading Simulation – Young’s model
    • 5.8 Simulation of Rayleigh Fading Model – (Clarke’s Model – Sum of Sinusoids)
    • 5.9 Rician Fading and Rician Distribution
  • Chapter 6: Digital Modulations
    • 6.1 BPSK Modulation and Demodulation
    • 6.2 BER vs. Eb/N0 for BPSK modulation over AWGN
    • 6.3 Eb/N0 vs. BER for BPSK over Rayleigh Channel
    • 6.4 Eb/N0 Vs BER for BPSK over Rician Fading Channel
    • 6.5 QPSK Modulation and Demodulation
    • 6.6 BER vs. Eb/N0 for QPSK modulation over AWGN
    • 6.7 BER vs. Eb/N0 for 8-PSK Modulation over AWGN
    • 6.8 Simulation of M-PSK modulations over AWGN
    • 6.9 Symbol Error Rate vs. SNR performance curve simulation for 16-QAM
    • 6.10 Symbol Error Rate Vs SNR performance curve simulation for 64-QAM
    • 6.11 Performance comparison of Digital Modulation techniques
    • 6.12 Intuitive derivation of Performance of an optimum BPSK receiver in AWGN channel
  • Chapter 7: Orthogonal Frequency Division Multiplexing (OFDM)
    • 7.1 Introduction to OFDM
    • 7.2 Role of FFT/IFFT in OFDM
    • 7.3 Role of Cyclic Prefix in OFDM
    • 7.4 Simulation of OFDM system in Matlab – BER Vs Eb/N0 for OFDM in AWGN channel
  • Chapter 8: Spread Spectrum Techniques
    • 8.1 Introduction to Spread Spectrum Communication
    • 8.2 Codes used in CDMA
    • 8.3 Maximum Length Sequences (m-sequences)
    • 8.4 Preferred Pairs m-sequences generation for Gold Codes
    • 8.5 Generation of Gold Codes and their cross-correlation
  • Appendix
    • A1: Deriving Shannon-Hartley Equation for CCMC AWGN channel -Method 1
    • A2. Capacity of Continuous input Continuous output Memoryless AWGN -Method 2
    • A3: Constellation Constrained Capacity of M-ary Scheme for AWGN channel
    • A4: Natural and Binary Codes
    • A5: Constructing a rectangular constellation for 16QAM
    • A6: Q Function and Error Function
  • References

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