Simulation of Communication Systems
1st Edition
Published on 6. December 2012
XXVI, 731 pages
978-1-4615-3298-9 (ISBN)
Description
Simulation may be defined as the discipline whose objective is to imitate one or more aspects of reality in a way that is as close to that reality as possible; indeed, an apt synonym that is gaining some currency is artificial reality. Under this definition, simulation is a very old discipline. Probably the first applications of simulation were to scale models of various types of dynamical structures or mechanical devices. Man has always looked for ways to "try things out" before building the real thing; this is the motivation behind any form of simulation. Thus, simulation of communication systems is concerned with imitating some aspects of the behavior of communication systems. It is implicit in our use of simulation that the medium (so to speak) for carrying it out is the digital computer. Computer-based modeling and simulation of communication systems has only developed in the last 20 years or so, since the advent of modern digital computers. A variety of modeling and simulation techniques have been developed and described in widely scattered journals, but until now there has not been a single volume devoted to the subject. We have tried to provide a unified framework that describes both the disciplines involved and the methods of modeling and simulating communication systems and subsystems. In the electronic era, the first type of computer simulation, in today's use of the term, took shape in the form of analog computers.
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Michel C. Jeruchim | Philip Balaban | K. Sam Shanmugan
Simulation of Communication Systems
Modeling, Methodology and Techniques
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04/2006
2nd Edition
Kluwer Academic / Plenum Publishers
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Additional editions
Michel C. Jeruchim | Philip Balaban | K. Sam Shanmugan
Simulation of Communication Systems
Modeling, Methodology and Techniques
Book
04/1992
Kluwer Academic / Plenum Publishers
€193.13
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Content
1. Introduction.- 1.1. Methods of Performance Evaluation.- 1.2. Simulation Approach.- 1.3. The Application of Simulation to the Design of Communication Systems.- 1.4. Historical Perspective.- 1.5. Outline of the Book.- References.- 2. Representation of Signals and Systems in Simulation.- 2.1. Introduction.- 2.2 Linear Time-Invariant Systems.- 2.3. Frequency Domain Representation Contents.- 2.4. Low-Pass Equivalent Signals and Systems.- 2.5. Sampling and Interpolation.- 2.6. Characterization of LTI Systems Using the Laplace Transform.- 2.7. Representation of Continuous Systems by Discrete Transfer Functions.- 2.8. Fourier Analysis for Discrete-Time Systems.- 2.9. The Process of Mapping Continuous Signals and Systems into Discrete Signals and Systems for Simulation.- 2.10. Linear Time-Variant (LTV) Systems.- 2.11. Nonlinear Systems.- 2.12. Summary.- 2.13. Appendix.- 2.14. Problems and Projects.- References.- 3. Simulation of Random Variables and Random Processes.- 3.1. Introduction.- 3.2. Random Variables.- 3.3. Univariate Models.- 3.4. Multivariate Models.- 3.5. Transformations (Functions) of Random Variables.- 3.6. Bounds and Approximations.- 3.7. Random Processes.- 3.8. Random Process Models.- 3.9. Transformation of Random Processes.- 3.10. Sampling and Quantizing.- 3.11. Computer Generation of Random Numbers and Sequences.- 3.12. Testing of Random Number Generators.- 3.13. Summary.- 3.14. Problems and Projects.- References.- 4. Modeling of Communication Systems.- 4.1. Introduction.- 4.2. Radiofrequency and Optical Sources.- 4.3. Information Sources.- 43.1. Analog Signals.- 4.4. Source Encoders/Decoders.- 4.5. Baseband Modulation: Formatting; Line Coding.- 4.6. RF and Optical Moaulation.- 4.7. Demodulation.- 4.8. Filtering.- 4.9. Communication Channels and Models.- 4.10. Multiplexing/Multiple Access.- 4.11. Noise and Interference.- 4.12. Error Control Coding.- 4.13. Synchronization.- 4.14. Spread Spectrum Techniques.- 4.15. Coded Modulation.- 4.16. Summary.- 4.17. Problems and Projects.- References.- 5. Estimation of Performance Measures from Simulation.- 5.1. Preliminaries.- 5.2. Estimating the Average Level of a Waveform.- 5.3. Estimating the Average Power (Mean-Square Value) of a Waveform.- 5.4. Estimating the Signal-to-Noise Ratio (SNR).- 5.5. Estimating the Probability Density or Distribution Function of the Amplitude of a Waveform.- 5.6. Estimating the Error Probability (Bit-Error-Rate) of a Digital System.- 5.7. Estimating the Power Spectral Density (PSD) of a Process.- 5.8. Visual Indicators of Performance and Related Bounds.- 5.9. Summary.- 5.10. Problems and Projects.- References.- 6. Simulation and Modeling Methodology.- 6.1. Simulation Environment.- 6.2. Modeling Considerations.- 6.3. Performance Evaluation Techniques.- 6.4. Error Sources in Simulation.- 6.5. Validation.- 6.6. The Role of Simulation in Communication System Engineering.- 6.7. Summary.- 6.8. Appendix: The "Equivalent Phase NoiseThe " Process.- 6.9. Problems and Projects.- References.- 7. Three Case Studies.- 7.1. Case Study I: 64-QAM Equalized Digital Radio Link in a Fading Environment.- 7.2. Case Study II: Lightwave Communications Link.- 7.3. Case Study III: A Satellite System Example.- References.- Appendixes.- A. A Collection of Useful Results for the Error Probability of Digital Systems.- B. Gaussian Tail Probabilities Q(x) and an Approximation Q(x).- C. Coefficients of the Hermite Polynomials.- D. Some Abscissas and Weights for Gaussian Quadrature Integration.- E. Chi-Square Probabilities.
