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Principles of Communication Systems Simulation with Wireless Applications

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Principles of Communication Systems Simulation with Wireless Applications


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  • Real-world simulation techniques.
    • Allows for the analysis of complex and practical systems. Ex.___

  • Systems level approach.
    • Provides students with a holistic view of communication systems by integrating a variety of concepts that are traditionally presented independently. Ex.___

  • Worked problems and example simulations.
    • Allows students to see how the techniques should be effectively applied in an actual simulation model. Ex.___

  • Example simulations using the Student Edition of MATLAB—Carefully documents each example.
    • Ensures that the majority of students will be able make use of the simulation examples since MATLAB is already used extensively in engineering curricula. Ex.___

  • Modern wireless communications—Including digital cellular techniques.
    • Provides students with practical, real-world experience in developing simulations for the most current specialty in communications. Ex.___

  • Support materials available on-line.
    • Provides students with necessary MATLAB software code as well as viewgraphs designed to support the course. Ex.___


  • Copyright 2004
  • Dimensions: 7x9-1/4
  • Pages: 800
  • Edition: 1st
  • Book
  • ISBN-10: 0-13-494790-8
  • ISBN-13: 978-0-13-494790-7

The hands-on, example-rich guide to modeling and simulating advanced communications systems.

Simulation is an important tool used by engineers to design and implement advanced communication systems that deliver optimal performance. This book is a hands-on, example-rich guide to modeling and simulating advanced communications systems. The authors take a systems-level approach, integrating digital communications, channel modeling, coding, elementary statistical estimation techniques, and other essential facets of modeling and simulation. This is the first book to present complete simulation models built with MATLAB that can serve as virtual laboratories for predicting the impact of system design changes. Coverage includes:

  • Role of simulation in communication systems engineering
  • Simulation approaches and methodologies
  • Signal and system representations, filter models, noise generation, Monte Carlo simulation, and postprocessing
  • Advanced techniques for modeling and simulating nonlinear and time-varying systems
  • Waveform level and discrete channel models
  • Performance estimation via Monte Carlo simulation
  • Semianalytic simulation techniques
  • Variance reduction techniques
  • Co-channel interference in wireless communication systems, and more

The authors also present detailed case studies covering phase-locked loops, CDMA systems, multichannel nonlinear systems, as well as a start-to-finish simulation of an advanced cellular radio system.

Prentice Hall Series in Communications Engineering & Emerging Technologies, Theodore S. Rappaport, Editor


Support File(s)

Untitled Document Prepared by: William H. Tranter
Department of Electrical and Computer Engineering
Virginia Tech - Mail Code 0350
Blacksburg, VA 24061

email: btranter@vt.edu

Revision Dates: March, 20, 2004
June 14, 2004

The collection of folders contained herein provide the MATLAB source code for all programs contained in the textbook:

W. H. Tranter, K. S. Shanmugan, T. S. Rappaport, and K. L. Kosbar, Principles of Communications System Simulation with Wireless Applications, Printice Hall PTR, 2004 (ISBN 0-13-494790-8)

Please report any errors, omissions, or suggestions to W. H. Tranter at btranter@vt.edu.


The authors have used reasonable care to ensure that the MATLAB programs given in the book are correct and all programs executed properly using MATLAB Version (January 17, 1998). The authors realize that this is an old version of MATLAB. This was done on purpose so that the latest version of MATLAB need not be required by the user. For the most part, MATLAB programs developed on older versions of MATLAB can be properly executed on newer versions of MATLAB. Sometimes, however, this is not the case and changes in MATLAB library functions result in compatibility problems. Most of these problems are easily fixed by one familiar with MATLAB code development. Should difficulties occur one should obvious carefully examine the code in the m-file of interest. The first item to check should be the argument list. A number of compatibility issues have been traced to changes made in argument lists.

The programs are developed for teaching purposes and are not intended to support the design or analysis of commercial hardware or software. In addition, many of the simulation programs are not written in the most efficient manner so that the signal processing algorithms can be easily understood by the student. Where speed of execution is a problem, the code can be written more efficiently, or the MATLAB code can rewritten in a language that can be easily compiled with the MATLAB code serving as the prototype.

Program Folders and Files:

The code is arranged by chapter with the code for each chapter in a separate folder. Each MATLAB program is in an individual file. The folder names are denoted Chapter_X where X denotes the chapter number. Folders are given for Chapters 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, and 18. There are no folders for Chapters 1, 2, and 11, since these three chapters contain no MATLAB code.

Programs within folders follow the naming conventions given in the textbook. In some cases there will be a README file in a given folder that indicates changes made from the files given in the textbook. In addition, some programs are contained in more than one folder. These are supporting programs and are used with main programs appearing in more than one chapter.

An effort was made to not require MATLAB add-on toolboxes in order to execute the programs given here. However, the Signal and Systems Toolbox is required a number of programs, especially those in Chapter 5.

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Table of Contents



1. The Role of Simulation.

Examples of Complexity. Multidisciplinary Aspects of Simulation. Models. Deterministic and Stochastic Simulations. The Role of Simulation. Software Packages for Simulation. A Word of Warning. The Use of MATLAB. Outline of the Book. Further Reading.

2. Simulation Methodology.

Introduction. Aspects of Methodology. Performance Estimation. Summary. Further Reading. Problems.


3. Sampling and Quantizing.

Sampling. Quantizing. Reconstruction and Interpolation. The Simulation Sampling Frequency. Summary. Further Reading. References. Problems.

4. Lowpass Simulation Models for Bandpass Signals and Systems.

The Lowpass Complex Envelope for Bandpass Signals. Linear Bandpass Systems. Multicarrier Signals. Nonlinear and Time-Varying Systems. Summary. Further Reading. References. Problems. Appendix A: MATLAB Program QAMDEMO. Appendix B: Proof of Input-Output Relationship.

5. Filter Models and Simulation Techniques.

Introduction. IIR and FIR Filters. IIR and FIR Filter Implementations. IIR Filters: Synthesis Techniques and Filter Characteristics. FIR Filters: Synthesis Techniques and Filter Characteristics. Summary. Further Reading. References. Problems. Appendix A: Raised Cosine Pulse Example. Appendix B: Square Root Raised Cosine Pulse Example. Appendix C: MATLAB Code and Data for Example 5.11.

6. Case Study: Phase-Locked Loops and Differential Equation Methods.

Basic Phase-Locked Loop Concepts. First-Order and Second-Order Loops. Case Study: Simulating the PLL. Solving Differential Equations Using Simulation. Summary. Further Reading. References. Problems. Appendix A: PLL Simulation Program. Appendix B: Preprocessor for PLL Example Simulation. Appendix C: PLL Postprocessor. Appendix D: MATLAB Code for Example 6.3.

7. Generating and Processing Random Signals.

Stationary and Ergodic Processes. Uniform Random Number Generators. Mapping Uniform RVs to an Arbitrary pdf. Generating Uncorrelated Gaussian Random Numbers. Generating Correlated Gaussian Random Numbers. Establishing a pdf and a PSD. PN Sequence Generators. Signal Processing. Summary. Further Reading. References. Problems. Appendix A: MATLAB Code for Example 7.11. Main Program: c7 Jakes.m.

8. Postprocessing.

Basic Graphical Techniques. Estimation. Coding. Summary. Further Reading. References. Problems. Appendix A: MATLAB Code for Example 8.1.

9. Introduction to Monte Carlo Methods.

Fundamental Concepts. Application to Communications Systems—The AWGN Channel. Monte Carlo Integration. Summary. Further Reading. References. Problems.

10. Monte Carlo Simulation of Communication Systems.

Two Monte Carlo Examples. Semianalytic Techniques. Summary. References. Problems. Appendix A: Simulation Code for Example 10.1. Appendix B: Simulation Code for Example 10.2. Appendix C: Simulation Code for Example 10.3. Appendix D: Simulation Code for Example 10.4.

11. Methodology for Simulating a Wireless System.

System-Level Simplifications and Sampling Rate Considerations. Overall Methodology. Summary. Further Reading. References. Problems.


12. Modeling and Simulation of Nonlinearities.

Introduction. Modeling and Simulation of Memoryless Nonlinearities. Modeling and Simulation of Nonlinearities with Memory. Techniques for Solving Nonlinear Differential Equations. PLL Example. Summary. Further Reading. References. Problems. Appendix A: Saleh's Model. Appendix B: MATLAB Code for Example 12.2.

13. Modeling and Simulation of Time-Varying Systems.

Introduction. Models for LTV Systems. Random Process Models. Simulation Models for LTV Systems. MATLAB Examples. Summary. Further Reading. References. Problems. Appendix A: Code for MATLAB Example 1. Appendix B: Code for MATLAB Example 2.

14. Modeling and Simulation of Waveform Channels.

Introduction. Wired and Guided Wave Channels. Radio Channels. Multipath Fading Channels. Modeling Multipath Fading Channels. Random Process Models. Simulation Methodology. Summary. Further Reading. References. Problems. Appendix A: MATLAB Code for Example 14.1. Appendix B: MATLAB Code for Example 14.2.

15. Discrete Channel Models.

Introduction. Discrete Memoryless Channel Models. Markov Models for Discrete Channels with Memory. Example HMMs—Gilbert and Fritchman Models. Estimation of Markov Model Parameters. Two Examples. Summary. Further Reading. References. Problems. Appendix A: Error Vector Generation. Appendix B: The Baum-Welch Algorithm. Appendix C: The Semi-Hidden Markov Model. Appendix D: Run-Length Code Generation. Appendix E: Determination of Error-Free Distribution.

16. Efficient Simulation Techniques.

Tail Extrapolation. pdf Estimators. Importance Sampling. Summary. Further Reading. References. Problems. Appendix A: MATLAB Code for Example 16.3.

17. Case Study: Simulation of a Cellular Radio System.

Introduction. Cellular Radio System. Simulation Methodology. Summary. Further Reading. References. Problems. Appendix A: Program for Generating the Erlang B Chart. Appendix B: Initialization Code for Simulation. Appendix C: Modeling Co-Channel Interference. Appendix D: MATLAB Code for Wilkinson's Method.

18. Two Example Simulations.

A Code-Division Multiple Access System. FDM System with a Nonlinear Satellite Transponder. References. Appendix A: MATLAB Code for CDMA Example. Appendix B: Preprocessors for CDMA Application. Appendix C: MATLAB Function c18 errvector.m. Appendix D: MATLAB Code for Satellite FDM Example.

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