Author: Mathuranathan Viswanathan
Editor (with publishing rights): Varsha Srinivasan
Formats : eBook and Paperback
Paperback: 384 pages
Publisher: Independently published (June 2020)
Language: English
ISBN: 979-8648350779 (paperback color print)
ISBN: 979-8648523210 (paperback black & white print)
Paperback Dimensions: 17.78 x 2.21 x 25.4 cm

Note: Only PDF version is available for purchase from this website. Paperback Print edition is available only from Amazon.

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Description

A learner-friendly, practical and example driven book, Wireless Communication Systems in Matlab gives you a solid background in building simulation models for wireless systems in Matlab. This book, an essential guide for understanding the basic implementation aspects of a wireless system, shows how to simulate and model such a system from scratch. The implemented simulation models shown in this book provide an opportunity for an engineer to understand the basic implementation aspects of modeling various building blocks of a wireless communication system. It presents the key topics with the required theoretical background along with the implementation details in the form of Matlab scripts.

Key features

• Random variables for simulating probabilistic systems and applications like Jakes filter design and colored noise generation.
• Models for Shannon’s channel capacity, unconstrained awgn channel, binary symmetric channel (BSC), binary erasure channel (BEC), constellation constrained capacities and ergodic capacity over fading channel. 
• The theory of linear block codes, decoding techniques using soft-decisions and hard-decisions, and their performance simulations.
• Monte Carlo simulation for ascertaining performance of digital modulation techniques in AWGN and fading channels – Eb/N0 Vs BER curves.
• Pulse shaping techniques, matched filtering and partial response signaling Design and implementation of linear equalizers – Zero forcing and MMSE equalizers, using them in a communication link and modulation systems with receiver impairments.
• Large-scale propagation models like Friis free space model, log distance model, two ray ground reflection model, single knife-edge diffraction model, Hata Okumura model.
• Essentials of small-scale propagation models for wireless channels, such as, power delay profile, Doppler power spectrum, Rayleigh and Rice processes. Modeling flat fading and frequency selective channels.
• Diversity techniques for multiple antenna systems: Alamouti space-time coding, maximum ratio combining, equal gain combining and selection combining.
• Simulation models for direct sequence spread spectrum, frequency hopping spread spectrum and OFDM.

Table of contents

• Part I Fundamental Concepts
• 1 Essentials of Signal Processing
  • Generating standard test signals
    • Sinusoidal signals
    • Square wave
    • Rectangular pulse
    • Gaussian pulse
    • Chirp signal
  • Interpreting FFT results – complex DFT, frequency bins and FFTShift
    • Real and complex DFT
    • Fast Fourier Transform (FFT)
    • Interpreting the FFT results
    • FFTShift
    • IFFTShift
    • Some observations on FFTShift and IFFTShift
  • Obtaining magnitude and phase information from FFT
    • Discrete-time domain representation
    • Representing the signal in frequency domain using FFT
    • Reconstructing the time domain signal from the frequency domain samples
    • Plotting Magnitude and Phase Spectrum
  • Power Spectral Density
  • Power and Energy of a signal
    • Energy of a signal
    • Power of a signal
    • Classification of signals
    • Computation of power of a signal – simulation and verification
  • Polynomials, Convolution and Toeplitz matrices
    • Polynomial functions
    • Representing single variable polynomial functions
    • Multiplication of polynomials and linear convolution
    • Toeplitz Matrix and Convolution
  • Methods to compute convolution
    • Method 1 – Brute-Force Method
    • Method 2 – Using Toeplitz Matrix
    • Method 3 – Using FFT to compute convolution
    • Miscellaneous methods
  • Analytic signal and its applications
    • Analytic signal and Fourier Transform
    • Applications of analytic signal
  • Choosing a filter : FIR or IIR : Understanding the design perspective
    • Design specification
    • General considerations in design
• 2 Random variables – simulating probabilistic systems
  • Introduction
  • Plotting the estimated PDF
  • Univariate random variables
    • Uniform random variable
    • Bernoulli random variable
    • Binomial random variable
    • Exponential random variable
    • Poisson process
    • Gaussian random variable
    • Chi-squared random variable
    • Non-central Chi-Squared random variable
    • Chi distributed random variable
    • Rayleigh random variable
    • Ricean random variable
    • Nakagami-m distributed random variable
  • Central limit theorem – a demonstration
  • Generating correlated random variables
    • Generating two sequences of correlated random variables
    • Generating multiple sequences of correlated random variables using Cholesky decomposition
  • Generating correlated Gaussian sequences
    • Spectral factorization method
    • Auto-Regressive (AR) model
• Part II Channel Capacity and Coding Theory
• 3 Channel Capacity
  • Introduction
  • Shannon’s noisy channel coding theorem
  • Unconstrained capacity for bandlimited AWGN channel
  • Shannon’s limit on spectral efficiency
  • Shannon’s limit on power efficiency
  • Generic capacity equation for Discrete Memoryless Channel (DMC)
    • Capacity over Binary Symmetric Channel
    • Capacity over Binary Erasure Channel
  • Constrained Capacity of Discrete input Continuous output Memoryless AWGN Channel
  • Ergodic capacity over a fading channel
• 4 Linear Block Coding
  • Introduction to error control coding
    • Error Control Schemes
    • Channel Coding Metrics
  • Overview of block codes
    • Error-detection and error-correction capability
    • Decoders for block codes
    • Classification of block codes
  • Theory of Linear Block Codes
  • Optimum Soft-Decision Decoding of Linear Block Codes for AWGN channel
  • Sub-optimal Hard-Decision Decoding of Linear Block Codes for AWGN channel
    • Standard Array Decoder
    • Syndrome decoding
  • Some classes of linear block codes
    • Repetition codes
    • Hamming codes
    • Maximum-length codes
    • Hadamard codes
  • Performance Simulation of Soft and Hard Decision Decoding of Hamming Codes
• Part III Digital Modulations
• 5 Digital Modulators and Demodulators – complex baseband equivalent models
  • Passband and complex baseband equivalent model
    • Complex Baseband representation of modulated signal
  • Complex baseband representation of channel response
  • Modulators for Amplitude and Phase modulations
    • Pulse Amplitude Modulation (M-PAM)
    • Phase Shift Keying Modulation (M-PSK)
    • Quadrature Amplitude Modulation (M-QAM)
  • Demodulators for Amplitude and Phase modulations
    • M-PAM detection
    • M-PSK detection
    • M-QAM detection
    • Optimum Detector on IQ plane using minimum Euclidean distance
  • M-ary FSK modulation and detection
    • Modulator for M orthogonal signals
    • M-FSK detection
• 6 Performance of Digital Modulations overWireless Channels
  • AWGN channel
    • Signal to Noise Ratio (SNR) definitions
    • AWGN channel model
    • Theoretical Symbol Error Rates
    • Unified Simulation model for performance simulation
  • Fading channels
    • Linear Time Invariant channel model and FIR filters
    • Simulation model for detection in flat Fading Channel
    • Rayleigh flat-fading channel
    • Ricean flat-fading channel
• Part IV Intersymbol interference and Equalizers
• 7 Pulse Shaping, Matched Filtering and Partial Response Signaling
  • Introduction
  • Nyquist Criterion for zero ISI
  • Discrete-time model for a system with pulse shaping and matched filtering
    • Rectangular pulse shaping
    • Sinc pulse shaping
    • Raised-cosine pulse shaping
    • Square-root raised-cosine pulse shaping
  • Eye Diagram
  • Implementing a Matched Filter system with SRRC filtering
    • Plotting the eye diagram
    • Performance simulation
  • Partial Response Signaling Models
    • Impulse response and frequency response of PR signaling schemes
  • Precoding
    • Implementing a modulo-M precoder
    • Simulation and results
• 8 Linear Equalizers
  • Introduction
  • Linear Equalizers
  • Zero-Forcing Symbol Spaced Linear Equalizer
    • Design and simulation of Zero Forcing equalizer
    • Drawbacks of Zero Forcing Equalizer
  • Minimum Mean Squared Error (MMSE) Equalizer
    • Design and simulation of MMSE equalizer
  • Equalizer Delay Optimization
  • BPSK Modulation with ZF and MMSE equalizers
• 9 Receiver Impairments and Compensation
  • Introduction
  • DC offsets and compensation
  • IQ imbalance model
  • IQ imbalance estimation and compensation
    • Blind estimation and compensation
    • Pilot based estimation and compensation
  • Visualizing the effect of receiver impairments
  • Performance of M-QAM modulation with receiver impairments
• Part V Wireless Channel Models
• 10 Large-scale propagation models
  • Introduction
  • Friis free space propagation model
  • Log distance path loss model
  • Two ray ground reflection model
  • Modeling diffraction loss
    • Single knife-edge diffraction model
    • Fresnel zones
  • Hata Okumura model for outdoor propagation
• 11 Small-scale models for multipath effects
  • Introduction
  • Statistical Characteristics of Multipath Channels
    • Mutipath Channel Models
    • Scattering Function
    • Power Delay Profile
    • Doppler Power Spectrum
    • Classification of small-scale fading
  • Rayleigh and Rice processes
    • Probability density function of amplitude
    • Probability density function of frequency
  • Modeling Frequency Flat Channel
  • Modeling Frequency Selective Channel
    • Method of Equal Distances (MED) to model specified power delay profiles
    • Simulating a Frequency Selective channel using TDL model
• 12 Multiple Antenna Systems – Spatial Diversity
  • Introduction
    • Diversity techniques
    • Single input single output (SISO) channel model
    • Multiple antenna systems channel model
  • Diversity and spatial multiplexing
    • Classification with respect to antenna configuration
    • Two flavors of multiple antenna systems
    • Spatial diversity
    • Spatial multiplexing
  • Receive diversity
    • Received signal model
    • Maximum ratio combining (MRC)
    • Equal gain combining (EGC)
    • Selection combining (SC)
    • Performance simulation
    • Array gain and diversity gain
  • Transmit diversity
    • Transmit beamforming with CSIT
    • Alamouti code for CSIT unknown
• Part VI Multiuser and Multitone Communication systems
• 13 Spread spectrum techniques
  • Introduction
  • Code sequences
    • Sequence correlations
    • Maximum-length sequences (m-sequences)
    • Gold codes
  • Direct Sequence Spread Spectrum
    • Simulation of DSSS system
    • Performance of Direct Sequence Spread Spectrum over AWGN channel
    • Performance of Direct Sequence Spread spectrum in the presence of Jammer
  • Frequency Hopping Spread Spectrum
    • Simulation model
    • Binary Frequency Shift Keying (BFSK)
    • Allocation of frequency channels
    • Frequency hopping generator
    • Fast and slow frequency hopping
    • Simulation code for BFSK-FHSS
• 14 Orthogonal Frequency Division Multiplexing (OFDM)
  • Introduction
  • Understanding the role of cyclic prefix in a CP-OFDM system
    • Circular convolution and designing a simple frequency domain equalizer
    • Demonstrating the role of Cyclic Prefix
    • Verifying DFT property
  • Discrete-time implementation of baseband CP-OFDM
  • Performance of MPSK-CP-OFDM and MQAM-CP-OFDM on AWGN channel
  • Performance of MPSK-CP-OFDM and MQAM-CP-OFDM on frequency selective Rayleigh channel

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Note: Only PDF version is available for purchase from this website. Paperback Print edition is available only from Amazon.