Modern Digital and Analog Communication Systems (The ^AOxford Series in Electrical and Computer Engineering)
An ideal first text on communication systems in electrical engineering, Modern Digital and Analog Communication Systems is now in its fourth edition. Retaining the superb pedagogical style of the first three editions, the authors first introduce the fundamentals of signals and systems and core communication topics; they then present the tools essential to the design and analysis of digital communications. Featuring a seamless blend of mathematics and heuristics, carefully crafted examples to clarify mathematical abstractions, and new and updated MATLAB exercises, this text provides a thorough coverage of modern communication system theory and application that is easily accessible to students.
Modern Digital and Analog Communication Systems is suitable for students with or without prior knowledge of probability theory. Only after laying a solid foundation in how communication systems work do the authors delve into analyses of communication systems that require probability theory and random processes. Revised, expanded, and updated throughout, the fourth edition reflects the many technological advances in the field, such as OFDM and CDMA, pervasive communication applications such as cellular systems, wireless LAN systems, and DSL modem technology services.
Features
* Flexible organization (outlined in the preface) that accommodates a variety of course structures, including one-semester, two-semester, one-quarter, and two-quarter
* Accessible to students with no background in probability theory
* Abundant real-world examples that are applicable to students' everyday lives
* Gives intuitive insights--rather than just proofs--wherever possible, as well as heuristic explanations of theoretical results
A solutions manual is available for adopting professors.
Why Read This Book
You should read this book if you want a clear, example-driven grounding in both analog and digital communication theory, with smooth transitions from signals and systems fundamentals to practical receiver design and performance analysis. The exposition balances mathematical rigor and intuition, and the end-of-chapter MATLAB exercises help you apply concepts to real problems.
Who Will Benefit
Undergraduate or beginning graduate engineers and practitioners who need a compact, readable treatment of modulation, noise, detection, and basic digital communications for design or coursework.
Level: Intermediate — Prerequisites: Calculus, linear systems (continuous-time signals and LTI systems), basic probability and random variables; familiarity with Fourier transforms and complex exponentials is helpful.
Key Takeaways
- Analyze signals in time and frequency using Fourier methods and sampling theory.
- Characterize the effects of noise and random processes on communication system performance.
- Design and evaluate analog modulation schemes (AM, DSB, SSB, FM/PM) and their receivers.
- Design and analyze baseband and bandpass digital signaling, matched filters, and optimum detectors in AWGN.
- Evaluate tradeoffs between bandwidth, power, and error probability for M-ary signaling.
- Apply MATLAB examples to simulate modulation/demodulation chains, receiver performance, and spectral properties.
Topics Covered
- Introduction and Signals & Systems Review
- Fourier Analysis, Spectra, and Sampling
- Noise and Random Processes
- Analog Modulation: AM, DSB, SSB
- Angle Modulation: FM and PM
- Receivers, Filtering, and Noise Performance
- Baseband Digital Transmission and Pulse Shaping
- Matched Filter, Correlator, and Optimum Detection
- M-ary Signaling, Bandpass Digital Communication
- Inter-symbol Interference and Equalization
- Performance Analysis in AWGN
- Introduction to Information Concepts and Practical MATLAB Exercises
Languages, Platforms & Tools
How It Compares
More readable and student-friendly than the mathematically dense Proakis 'Digital Communications', and comparable in scope to Haykin/Taub texts but with clearer step-by-step pedagogy and more worked MATLAB exercises.
