Simulation of Communication Systems: Modeling, Methodology and Techniques (Information Technology: Transmission, Process
Since the first edition of this book was published seven years ago, the field of modeling and simulation of communication systems has grown and matured in many ways, and the use of simulation as a day-to-day tool is now even more common practice. With the current interest in digital mobile communications, a primary area of application of modeling and simulation is now in wireless systems of a different flavor from the `traditional' ones.
This second edition represents a substantial revision of the first, partly to accommodate the new applications that have arisen. New chapters include material on modeling and simulation of nonlinear systems, with a complementary section on related measurement techniques, channel modeling and three new case studies; a consolidated set of problems is provided at the end of the book.
Why Read This Book
You will learn practical, repeatable methods for building credible simulations of real communication systems — from signal and channel modeling to Monte Carlo analysis and measurement-based validation. The book emphasizes methodology and pitfalls, so you’ll be able to turn theoretical algorithms into trustworthy simulation experiments for wireless, radar, audio, or speech applications.
Who Will Benefit
Practicing communications and signal-processing engineers or graduate students who need to design, validate, or benchmark simulators and models for digital communications, radar, audio/speech, or wireless systems.
Level: Advanced — Prerequisites: Undergraduate-level probability and random processes, basic communications theory (digital modulation, channel concepts), and familiarity with signal-processing concepts (filters, FFT); basic programming experience (MATLAB or C/C++).
Key Takeaways
- Build accurate simulation models of transmitters, receivers, channels (including wireless fading) and measurement chains
- Implement and run statistically valid Monte Carlo experiments and interpret confidence intervals and error estimates
- Model and simulate nonlinear system effects and link them to practical measurement techniques
- Apply spectral-analysis, FFT-based techniques and digital filter models within end-to-end communications simulations
- Validate and verify simulation results against theoretical expectations and real measurement data
- Design and reproduce case-study simulations for modulation, coding, radar returns and audio/speech processing scenarios
Topics Covered
- 1. Introduction to Modeling and Simulation Methodology
- 2. Random Processes and Statistical Tools for Simulation
- 3. Monte Carlo Methods and Experimental Design
- 4. Simulator Architecture, Software Design and Implementation Practices
- 5. Modeling of Transmitter and Receiver Blocks (modulation, coding, DSP modules)
- 6. Digital Filter Models, FFT and Spectral Analysis in Simulations
- 7. Channel Modeling: AWGN, Fading, Multipath and Wireless Propagation
- 8. Modeling and Simulation of Nonlinear Systems and Measurement Techniques
- 9. Adaptive Filtering, Estimation and Statistical Signal Processing
- 10. Specialized Applications: Radar, Audio/Speech and Communication Case Studies
- 11. Validation, Verification and Interpretation of Simulation Results
- 12. Practical Case Studies and Worked Examples
Languages, Platforms & Tools
How It Compares
Compared with Proakis' Digital Communications (theory-focused) and Haykin's Communication Systems (broad theory and design), Jeruchim's book emphasizes practical modeling methodology, Monte Carlo practice and measurement-based validation for simulators.
