Principles of Digital Communication
The renowned communications theorist Robert Gallager brings his lucid writing style to the study of the fundamental system aspects of digital communication for a one-semester course for graduate students. With the clarity and insight that have characterized his teaching and earlier textbooks, he develops a simple framework and then combines this with careful proofs to help the reader understand modern systems and simplified models in an intuitive yet precise way. A strong narrative and links between theory and practice reinforce this concise, practical presentation. The book begins with data compression for arbitrary sources. Gallager then describes how to modulate the resulting binary data for transmission over wires, cables, optical fibers, and wireless channels. Analysis and intuitive interpretations are developed for channel noise models, followed by coverage of the principles of detection, coding, and decoding. The various concepts covered are brought together in a description of wireless communication, using CDMA as a case study.
Why Read This Book
You will gain a concise, rigorous, and system-oriented foundation in digital communication from one of the field’s clearest expositors. Gallager blends intuitive system-level perspectives with careful proofs so you can connect theory (source and channel limits, detection, modulation) to practical design choices used in modern communications and signal-processing systems.
Who Will Benefit
Graduate students and practicing engineers in communications, signal processing, or related fields who want a precise, theory-grounded understanding of source coding, modulation, detection, and channel behavior for system design and analysis.
Level: Advanced — Prerequisites: Undergraduate-level calculus and linear algebra, probability and random processes (basic stochastic concepts), signals and systems or introductory communications fundamentals.
Key Takeaways
- Analyze the fundamental limits of data compression and relate source coding principles to real-world systems
- Characterize modulation schemes and represent communication signals in signal space for performance comparison
- Derive and apply detection and estimation results to evaluate receiver performance on noisy channels
- Evaluate channel capacity and trade-offs for various channel models (including Gaussian channels)
- Relate theoretical limits to practical system design choices such as modulation, coding strategies, and bandwidth/power tradeoffs
Topics Covered
- Introduction: System View of Digital Communication
- Mathematical Preliminaries and Signal Space
- Source Coding and Data Compression
- Representation of Signals and Modulation in Signal Space
- Detection Theory for Digital Signals
- Performance Measures and Error Probability Analysis
- Channel Models and Channel Capacity
- Gaussian Channels and Power–Bandwidth Tradeoffs
- Coding and Practical System Considerations
- Links between Theory and Modern Communication Systems
How It Compares
More concise and system-focused than Proakis' Digital Communications and more application-oriented than Cover & Thomas' Elements of Information Theory, Gallager provides a middle ground of rigorous insight with attention to practical system implications.
