# Simulation of Digital Communication Systems Using Matlab [eBook] – Second Edition

**Simulation 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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**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.

**Note:** If you are** residing in India and do not have a credit card** to purchase this book, write to us at support@gaussianwaves.com. We will assist you.

**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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I bought this book from iTune one week ago. This book introduces simulation of communication systems from the beginning. It deeply attracts me. It includes digital communication, channel coding, inter-symbol interference, fading, digital modulations, OFDM and so on. This book covers all the basics of simulation of communication systems. I am hoping that authors can add some new technologies into it.

1. In general, for most of the topics , matlab codes are given. So, it is possible to practically simulate and understand the concepts. This is a good feature.

2. If possible references may be added to get a better understand of some of the topics.

3. Some areas, explanantion can be more clear. For example , I went through the convolution encoder. It is not clear how the generator polynomials are used.

4. According to the formula given, the number of states in the state diagram is 2(m-1), where m is the number of memory element.

For a (2,1,3) encoder, the number of memeory elements m is calculated as follows:

L = k(m+1) -> 3 = 1(m+1) -> m=2

Therefore, the number of states = 2(m-1) -> 2(2-1) = 2.

But in the book, it is mentioned as 4 states. I am not sure if I am making any mistake. Please check.

Hi Kalpa,

Thanks for your inputs. I will improve the ebook and provide more clarity on the topics.

Regarding the states, the equation is and not . That was a typo in printing. I will take care of that in the next edition. So that leaves us with 4 states.

Hi

Thanks a lot for your reply.

Even while using power as as mentioned in the reply, if my understanding is right, for m= 2 ,

2 ( m-1) in the above example is again 2 ( 2 1 )

Therefore only 2 states are there. I am not sure, if I am going wrong somewhere. Please check

Thanks a lot for your time.

Hi,

There exist two versions of formulas to calculate the constraint length (L)

The number of memory elements has to be interpreted accordingly.

For a (n=2,k=1,L=3) convolutional code the constraint length L=3.

If we use formula 1, then 3=1*(m+1) => m=2. This gives us two memory elements, which is straight forward. Then the number of states will be 2^m = 2^2=4 states.

If we use formula 2, then 3=1*m => m=3. Then you have to use the formula 2^(m-1) to calculate the number of states. Which gives 2^(3-1)=2^2=4 states again.

So, care must be taken to interpret the constrain length definition properly. I will elaborate more on this.