Mathuranathan Viswanathan's Blog
May 8, 2014
February 17, 2014
February 15, 2014
December 24, 2013
Computation of Power of a Signal in Matlab – Simulation and Verification
Link here for the full text:
http://www.gaussianwaves.com/2013/12/...
http://www.gaussianwaves.com/2013/12/...
December 20, 2013
Know the difference between energy and power
New post: Know the difference between energy and power. http://www.gaussianwaves.com/2013/12/...
November 29, 2013
September 25, 2013
Announcement of Release of 2nd Edition of eBook- Simulation of Digital Communication Systems Using Matlab
Dear all,
I am very happy to release the second edition of the eBook – Simulation of Digital Communication Systems Using Matlab.
Based on various feedback from students & professors around the world, I have revised the content. Also, new topics are added to this new edition. I thank you all for your unwavering support.
It is now available for purchase at GaussianWaves (PDF version) and Amazon (Kindle edition). In a few days, it will be released at other major online stores.
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, new chapter on probability and random process and simulating various random variables.
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.
Warm Regards,
Mathuranathan Viswanathan,
Founder & author @ gaussianwaves.com
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
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
I am very happy to release the second edition of the eBook – Simulation of Digital Communication Systems Using Matlab.
Based on various feedback from students & professors around the world, I have revised the content. Also, new topics are added to this new edition. I thank you all for your unwavering support.
It is now available for purchase at GaussianWaves (PDF version) and Amazon (Kindle edition). In a few days, it will be released at other major online stores.
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, new chapter on probability and random process and simulating various random variables.
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.
Warm Regards,
Mathuranathan Viswanathan,
Founder & author @ gaussianwaves.com
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
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
