Principles of Communication: Systems, Modulation and Noise, 5th Edition
Sections on important areas such as spread spectrum, cellular communications, and orthogonal frequency--division multiplexing are provided. Computational examples are included, illustrating how to use the computer as a simulation tool, thereby allowing waveforms, spectra, and performance curves to be generated. Overviews of the necessary background in signal, system, probability, and random process theory required for the analog and digital communications topics covered in the book.
Why Read This Book
You should read this book if you want a clear, simulation-friendly bridge between signals & systems theory and practical communication engineering — you will learn how modulation, noise, and detection interact in real systems and how to use computational examples to visualize waveforms, spectra, and performance. The text emphasizes intuition and worked examples (including spread spectrum, cellular concepts, and OFDM), so you can move from theory to simulation and system-level analysis quickly.
Who Will Benefit
An undergraduate-to-early-graduate engineer or practitioner who knows basic signals and probability and wants a practical, simulation-oriented grounding in analog and digital communications and noise analysis.
Level: Intermediate — Prerequisites: Undergraduate calculus, basic signals & systems (linear time-invariant systems, Fourier transforms), and introductory probability; prior exposure to linear algebra and basic programming (MATLAB/Octave or similar) is helpful.
Key Takeaways
- Analyze and quantify the effects of noise on analog and digital modulation schemes using signal-to-noise and error-probability metrics.
- Design and evaluate common modulation and demodulation techniques (AM, FM, PSK, QAM, FSK) and their bandwidth/efficiency tradeoffs.
- Apply matched-filter and optimum detection theory to derive receiver structures and performance for baseband and bandpass signals.
- Simulate spread-spectrum techniques, CDMA concepts, and OFDM systems to observe spectral characteristics and performance under realistic noise and interference.
- Use spectral analysis and FFT-based methods to examine communication waveforms and measure system behavior in frequency and time domains.
- Model signals as random processes and apply statistical signal-processing concepts to predict system performance and interpret measurement results.
Topics Covered
- Introduction and Signal Representation
- Review of Probability and Random Processes for Communications
- Noise: Models, Metrics, and Effects on Signals
- Linear Systems, Filtering, and Spectral Analysis (FFT applications)
- Analog Modulation and Demodulation (AM, DSB, SSB, FM)
- Angle Modulation and Performance Analysis
- Pulse, Sampling, and Pulse-Code Modulation
- Digital Baseband Transmission and Detection Theory
- Bandpass Digital Modulation (PSK, QAM, FSK) and Error Analysis
- Spread Spectrum and CDMA Techniques
- Orthogonal Frequency-Division Multiplexing (OFDM) and Multicarrier Systems
- Cellular Communications, Multipath Effects, and System-Level Considerations
- Performance Evaluation, Computational Examples, and Simulation Techniques
Languages, Platforms & Tools
How It Compares
Compared with Proakis' Digital Communications (more mathematically rigorous and theory-heavy), Ziemer is more approachable and simulation-focused; it complements Sklar's Digital Communications by emphasizing foundational signal/noise analysis and worked computational examples.
