Digital Communications: Fundamentals and Applications / Edition 2

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  • The clear, easy-to-understand introduction to digital communications
  • Completely updated coverage of today's most critical technologies
  • Step-by-step implementation coverage
  • Trellis-coded modulation, fading channels, Reed-Solomon codes, encryption, and more
  • Exclusive coverage of maximizing performance with advanced "turbo codes"
"This is a remarkably comprehensive treatment of the field, covering in considerable detail modulation, coding (both source and channel), encryption, multiple access and spread spectrum. It can serve both as an excellent introduction for the graduate student with some background in probability theory or as a valuable reference for the practicing ommunication system engineer. For both communities, the treatment is clear and well presented."

– Andrew Viterbi, The Viterbi Group

Master every key digital communications technology, concept, and technique.

Digital Communications, Second Edition is a thoroughly revised and updated edition of the field's classic, best-selling introduction. With remarkable clarity, Dr. Bernard Sklar introduces every digital communication technology at the heart of today's wireless and Internet revolutions, providing a unified structure and context for understanding them -- all without sacrificing mathematical precision.

Sklar begins by introducing the fundamentals of signals, spectra, formatting, and baseband transmission. Next, he presents practical coverage of virtually every contemporary modulation, coding, and signal processing technique, with numeric examples and step-by-step implementation guidance. Coverage includes:

  • Signals and processing steps: from information source through transmitter, channel, receiver, and information sink
  • Key tradeoffs: signal-to-noise ratios, probability of error, and bandwidth expenditure
  • Trellis-coded modulation and Reed-Solomon codes: what's behind the math
  • Synchronization and spread spectrum solutions
  • Fading channels: causes, effects, and techniques for withstanding fading
  • The first complete how-to guide to turbo codes: squeezing maximum performance out of digital connections
  • Implementing encryption with PGP, the de facto industry standard

Whether you're building wireless systems, xDSL, fiber or coax-based services, satellite networks, or Internet infrastructure, Sklar presents the theory and the practical implementation details you need. With nearly 500 illustrations and 300 problems and exercises, there's never been a faster way to master advanced digital communications.


The CD-ROM contains a complete educational version of Elanix' SystemView DSP design software, as well as detailed notes for getting started, a comprehensive DSP tutorial, and over 50 additional communications exercises.

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Editorial Reviews

From The Critics
This graduate textbook describes techniques for transmitting voice and data over a path that consists of wires, waveguides, or space. Sklar (UCLA) covers source coding, baseband and bandpass signaling, channel coding, multiplexing, spreading, and encryption. The second edition adds a chapter on fading channels. The CD-ROM contains an educational version of SystemView and 200 exercises. Annotation c. Book News, Inc., Portland, OR
Comprehensive coverage for senior-level undergraduates, first-year graduate students, and practicing engineers. Even though the emphasis is on digital communications, necessary analog fundamentals are included. Annotation c. Book News, Inc., Portland, OR
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Product Details

Meet the Author

DR. BERNARD SKLAR has over 40 years of experience in technical design and management positions at Republic Aviation, Hughes Aircraft, Litton Industries, and at The Aerospace Corporation, where he helped develop the MILSTAR satellite system. He is now head of advanced systems at Communications Engineering Services, a consulting company he founded in 1984. He has taught engineering courses at several universities, including UCLA and USC, and has trained professional engineers worldwide.

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Read an Excerpt

Chapter1: Signals and Spectra

This book presents the ideas and techniques fundamental to digital communication systems. Emphasis is placed on system design goals and on the need for tradeoffs among basic system parameters such as signal-to-noise ratio (SNR), probability of error, and bandwidth expenditure. We shall deal with the transmission of information (voice, video, or data) over a path (channel) that may consist of wires, wave-guides, or space.

Digital communication systems are becoming increasingly attractive because of the ever-growing demand for data communication and because digital transmission offers data processing options and flexibilities not available with analog transmission. In this book, a digital system is often treated in the context of a satellite communications link. Sometimes the treatment is in the context of a mobile radio system, in which case signal transmission typically suffers from a phenomenon called fading. In general, the task of characterizing and mitigating the degradation effects of a fading channel is more challenging than performing similar tasks for a nonfading channel.

The principal feature of a digital communication system (DCS) is that during a finite interval of time, it sends a waveform from a finite set of possible wave-forms, in contrast to an analog communication system, which sends a waveform from an infinite variety of waveform shapes with theoretically infinite resolution. In a DCS, the objective at the receiver is not to reproduce a transmitted waveform with precision; instead, the objective is to determine from a noise-perturbed signal which waveform from the finite set of waveforms was sent by the transmitter. An important measure of system performance in a DCS is the probability of error (PE).

1.1 Digital Communication Signal Processing

1.1.1 Why Digital?

Why are communication systems, military and commercial alike, "going digital"? There are many reasons. The primary advantage is the ease with which digital signals, compared with analog signals, are regenerated. Figure 1.1 illustrates an ideal binary digital pulse propagating along a transmission line. The shape of the wave-form is affected by two basic mechanisms: (1) as all transmission lines and circuits have some nonideal frequency transfer function, there is a distorting effect on the ideal pulse; and (2) unwanted electrical noise or other interference further distorts the pulse waveform. Both of these mechanisms cause the pulse shape to degrade as a function of line length, as shown in Figure 1.1. During the time that the transmitted pulse can still be reliably identified (before it is degraded to an ambiguous state), the pulse is amplified by a digital amplifier that recovers its original ideal shape. The pulse is thus "reborn" or regenerated. Circuits that perform this function at regular intervals along a transmission system are called regenerative repeaters.

Digital circuits are less subject to distortion and interference than are analog circuits. Because binary digital circuits operate in one of two states—fully on or fully off—to be meaningful, a disturbance must be large enough to change the circuit operating point from one state to the other. Such two-state operation facilitates signal regeneration and thus prevents noise and other disturbances from accumulating in transmission. Analog signals, however, are not two-state signals; they can take an infinite variety of shapes. With analog circuits, even a small disturbance can render the reproduced waveform unacceptably distorted. Once the analog signal is distorted, the distortion cannot be removed by amplification. Because accumulated noise is irrevocably bound to analog signals, they cannot be perfectly regenerated. With digital techniques, extremely low error rates producing high signal fidelity are possible through error detection and correction but similar procedures are not available with analog.

There are other important advantages to digital communications. Digital circuits are more reliable and can be produced at a lower cost than analog circuits. Also, digital hardware lends itself to more flexible implementation than analog hardware [e.g., microprocessors, digital switching, and large-scale integrated (LSI) circuits]. The combining of digital signals using time-division multiplexing (TDM) is simpler than the combining of analog signals using frequency-division multiplexing (FDM). Different types of digital signals (data, telegraph, telephone, television) can be treated as identical signals in transmission and switching—a bit is a bit. Also, for convenient switching, digital messages can be handled in autonomous groups called packets. Digital techniques lend themselves naturally to signal processing functions that protect against interference and jamming, or that provide encryption and privacy. (Such techniques are discussed in Chapters 12 and 14, respectively.) Also, much data communication is from computer to computer, or from digital instruments or terminal to computer. Such digital terminations are naturally best served by digital communication links.

What are the costs associated with the beneficial attributes of digital communication systems? Digital systems tend to be very signal-processing intensive com-pared with analog. Also, digital systems need to allocate a significant share of their resources to the task of synchronization at various levels. (See Chapter 10.) With analog systems, on the other hand, synchronization often is accomplished more easily. One disadvantage of a digital communication system is nongraceful degradation. When the signal-to-noise ratio drops below a certain threshold, the quality of service can change suddenly from very good to very poor. In contrast, most analog communication systems degrade more gracefully.

1.1.2 Typical Block Diagram and Transformations

The functional block diagram shown in Figure 1.2 illustrates the signal flow and the signal-processing steps through a typical digital communication system (DCS). This figure can serve as a kind of road map, guiding the reader through the chapters of this book. The upper blocks—format, source encode, encrypt, channel encode, multiplex, pulse modulate, bandpass modulate, frequency spread, and multiple access— denote signal transformations from the source to the transmitter (XMT). The lower blocks denote signal transformations from the receiver (RCV) to the sink, essentially reversing the signal processing steps performed by the upper blocks. The modulate and demodulate/detect blocks together are called a modem. The term "modem" often encompasses several of the signal processing steps shown in Figure 1.2; when this is the case, the modem can be thought of as the "brains" of the system. The transmitter and receiver can be thought of as the "muscles" of the system. For wireless applications, the transmitter consists of a frequency up-conversion stage to a radio frequency (RF), a high-power amplifier, and an antenna. The receiver portion consists of an antenna and a low-noise amplifier (LNA). Frequency down-conversion is performed in the front end of the receiver and/or the demodulator.

Figure 1.2 illustrates a kind of reciprocity between the blocks in the upper transmitter part of the figure and those in the lower receiver part. The signal processing steps that take place in the transmitter are, for the most part, reversed in the receiver. In Figure 1.2, the input information source is converted to binary digits (bits); the bits are then grouped to form digital messages or message symbols. Each such symbol (mi , where i =1 , . . . , M) can be regarded as a member of a finite alphabet set containing M members. Thus, for M =2, the message symbol mi is binary (meaning that it constitutes just a single bit). Even though binary symbols fall within the general definition of M-ary, nevertheless the name M-ary is usually applied to those cases where M >2; hence, such symbols are each made up of a sequence of two or more bits. (Compare such a finite alphabet in a DCS with an analog system, where the message waveform is typically a member of an infinite set of possible waveforms.) For systems that use channel coding (error correction coding), a sequence of message symbols becomes transformed to a sequence of channel symbols (code symbols), where each channel symbol is denoted ui . Because a message symbol or a channel symbol can consist of a single bit or a grouping of bits, a sequence of such symbols is also described as a bit stream, as shown in Figure 1.2.

Consider the key signal processing blocks shown in Figure 1.2; only formatting, modulation, demodulation/detection, and synchronization are essential for a DCS. Formatting transforms the source information into bits, thus assuring compatibility between the information and the signal processing within the DCS. From this point in the figure up to the pulse-modulation block, the information remains in the form of a bit stream. Modulation is the process by which message symbols or channel symbols (when channel coding is used) are converted to waveforms that are compatible with the requirements imposed by the transmission channel. Pulse modulation is an essential step because each symbol to be transmitted must first be transformed from a binary representation (voltage levels representing binary ones and zeros) to a baseband waveform. The term baseband refers to a signal whose spectrum extends from (or near) dc up to some finite value, usually less than a few megahertz. The pulse-modulation block usually includes filtering for minimizing the transmission bandwidth. When pulse modulation is applied to binary symbols, the resulting binary waveform is called a pulse-code-modulation (PCM) waveform. There are several types of PCM waveforms (described in Chapter 2); in telephone applications, these waveforms are often called line codes. When pulse modulation is applied to nonbinary symbols, the resulting waveform is called an M-ary pulse-modulation waveform. There are several types of such waveforms, and they too are described in Chapter 2, where the one called pulse-amplitude modulation (PAM) is emphasized. After pulse modulation, each message symbol or channel symbol takes the form of a baseband waveform gi(t), where i =1, . . . , M. In any electronic implementation, the bit stream, prior to pulse-modulation, is represented with voltage levels. One might wonder why there is a separate block for pulse modulation when in fact different voltage levels for binary ones and zeros can be viewed as impulses or as ideal rectangular pulses, each pulse occupying one bit time. There are two important differences between such voltage levels and the baseband waveforms used for modulation. First, the pulse-modulation block allows for a variety of binary and M-ary pulse-waveform types. Section 2.8.2 describes the different useful attributes of these types of waveforms. Second, the filtering within the pulse-modulation block yields pulses that occupy more than just one-bit time. Filtering yields pulses that are spread in time, thus the pulses are "smeared" into neighboring bit-times. This filtering is sometimes referred to as pulse shaping; it is used to contain the transmission bandwidth within some desired spectral region.

For an application involving RF transmission, the next important step is bandpass modulation; it is required whenever the transmission medium will not support the propagation of pulse-like waveforms. For such cases, the medium requires a bandpass waveform si(t), where i =1 , . . . , M . The term bandpass is used to indicate that the baseband waveform gi(t) is frequency translated by a carrier wave to a frequency that is much larger than the spectral content of gi(t). As si(t) propagates over the channel, it is impacted by the channel characteristics, which can be described in terms of the channel's impulse response hc(t) (see Section 1.6.1). Also, at various points along the signal route, additive random noise distorts the received signal r(t), so that its reception must be termed a corrupted version of the signal si(t) that was launched at the transmitter. The received signal r(t) can be expressed as...

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Table of Contents

(NOTE: Each chapter concludes with a Conclusion, References, Problems, Questions, and CD Exercises.)

1. Signals and Spectra.

Digital Communication Signal Processing. Classification of Signals. Spectral Density. Autocorrelation. Random Signals. Signal Transmission through Linear Systems. Bandwidth of Digital Data.

2. Formatting and Baseband Modulation.

Baseband Systems. Formatting Textual Data (Character Coding). Messages, Characters, and Symbols. Formatting Analog Information. Sources of Corruption. Pulse Code Modulation. Uniform and Nonuniform Quantization. Baseband Modulation. Correlative Coding.

3. Baseband Demodulation/Detection.

Signals and Noise. Detection of Binary Signals in Gaussian Noise. Intersymbol Interference. Equalization.

4. Bandpass Modulation and Demodulation/Detection.

Why Modulate? Digital Bandpass Modulation Techniques. Detection of Signals in Gaussian Noise. Coherent Detection. Noncoherent Detection. Complex Envelope. Error Performance for Binary Systems. M-ary Signaling and Performance. Symbol Error Performance for M-ary Systems (M2).

5. Communications Link Analysis.

What the System Link Budget Tells the System Engineer. The Channel. Received Signal Power and Noise Power. Link Budget Analysis. Noise Figure, Noise Temperature, and System Temperature. Sample Link Analysis. Satellite Repeaters. System Trade-Offs.

6. Channel Coding: Part 1.

Waveform Coding. Types of Error Control. Structured Sequences. Linear Block Codes. Error-Detecting and Correcting Capability. Usefulness of the Standard Array. Cyclic Codes. Well-Known Block Codes.

7. Channel Coding: Part 2.

Convolutional Encoding. Convolutional Encoder Representation. Formulation of the Convolutional Decoding Problem. Properties of Convolutional Codes. Other Convolutional Decoding Algorithms.

8. Channel Coding: Part 3.

Reed-Solomon Codes. Interleaving and Concatenated Codes. Coding and Interleaving Applied to the Compact Disc Digital Audio System. Turbo Codes.

Appendix 8A. The Sum of Log-Likelihood Ratios.
9. Modulation and Coding Trade-Offs.

Goals of the Communications System Designer. Error Probability Plane. Nyquist Minimum Bandwidth. Shannon-Hartley Capacity Theorem. Bandwidth Efficiency Plane. Modulation and Coding Trade-Offs. Defining, Designing, and Evaluating Systems. Bandwidth-Efficient Modulations. Modulation and Coding for Bandlimited Channels. Trellis-Coded Modulation.

10. Synchronization.

Introduction. Receiver Synchronization. Network Synchronization.

11. Multiplexing and Multiple Access.

Allocation of the Communications Resource. Multiple Access Communications System and Architecture. Access Algorithms. Multiple Access Techniques Employed with INTELSAT. Multiple Access Techniques for Local Area Networks.

12. Spread-Spectrum Techniques.

Spread-Spectrum Overview. Pseudonoise Sequences. Direct-Sequence Spread-Spectrum Systems. Frequency Hopping Systems. Synchronization. Jamming Considerations. Commercial Applications. Cellular Systems.

13. Source Coding.

Sources. Amplitude Quantizing. Differential Pulse-Code Modulation. Adaptive Prediction. Block Coding. Transform Coding. Source Coding for Digital Data. Examples of Source Coding.

14. Encryption and Decryption.

Models, Goals, and Early Cipher Systems. The Secrecy of a Cipher System. Practical Security. Stream Encryption. Public Key Cryptosystems. Pretty Good Privacy.

15. Fading Channels.

The Challenge of Communicating over Fading Channels. Characterizing Mobile-Radio Propagation. Signal Time-Spreading. Time Variance of the Channel Caused by Motion. Mitigating the Degradation Effects of Fading. Summary of the Key Parameters Characterizing Fading Channels. Applications: Mitigating the Effects of Frequency-Selective Fading.

A. A Review of Fourier Techniques.

Signals, Spectra, and Linear Systems. Fourier Techniques for Linear System Analysis. Fourier Transform Properties. Useful Functions. Convolution. Tables of Fourier Transforms and Operations.

B. Fundamentals of Statistical Decision Theory.

Bayes' Theorem. Decision Theory. Signal Detection Example.

C. Response of a Correlator To White Noise.D. Often-Used Identities.E. s-Domain, z-Domain and Digital Filtering.F. List of Symbols.G. SystemView by ELANIX Guide to the CD.

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This second edition of Digital Communications: Fundamentals and Applications represents an update of the original publication. The key features that have been updated are:
  • The error-correction coding chapters have been expanded, particularly in the areas of Reed-Solomon codes, turbo codes, and trellis-coded modulation.
  • A new chapter on fading channels and how to mitigate the degrading effects of fading has been introduced.
  • Explanations and descriptions of essential digital communication concepts have been amplified.
  • End-of-chapter problem sets have been expanded. Also, end-of-chapter question sets (and where to find the answers), as well as end-of-chapter CD exercises have been added.
  • A compact disc (CD) containing an educational version of the design software SystemView by ELANIX accompanies the textbook. The CD contains a workbook with over 200 exercises, as well as a concise tutorial on digital signal processing (DSP). CD exercises in the workbook reinforce material in the textbook; concepts can be explored by viewing waveforms with a windows-based PC and by changing parameters to see the effects on the overall system. Some of the exercises provide basic training in using SystemView; others provide additional training in DSP techniques.
The teaching of a one-semester university course proceeds in a very different manner compared with that of a short-course in the same subject. At the university, one has the luxury of time—time to develop the needed skills and mathematical tools, time to practice the ideas with homework exercises. In a short-course, the treatment is almost backwards compared with the university. Because of the time factor, a short-course teacher must "jump in" early with essential concepts and applications. One of the vehicles that I found useful in structuring a short course was to start by handing out a check list. This was not merely an outline of the curriculum. It represented a collection of concepts and nomenclature that are not clearly documented, and are often misunderstood. The short-course students were thus initiated into the course by being challenged. I promised them that once they felt comfortable describing each issue, or answering each question on the list, they would be well on their way toward becoming knowledgeable in the field of digital communications. I have learned that this list of essential concepts is just as valuable for teaching full-semester courses as it is for short courses. Here then is my "check list" for digital communications.
  1. What mathematical dilemma is the cause for there being several definitions of bandwidth? (See Section 1.7.2.)
  2. Why is the ratio of bit energy-to-noise power spectral density, Eb/N0 , a natural figure-to-merit for digital communication systems? (See Section 3.1.5.)
  3. When representing timed events, what dilemma can easily result in confusing the most-significant bit (MSB) and the least-significant bit (LSB)? (See Section
  4. The error performance of digital signaling suffers primarily from two degradation types. a) loss in signal-to-noise ratio, b) distortion resulting in an irreducible bit-error probability. How do they differ? (See Section 3.3.2.)
  5. Often times, providing more Eb/N0 will not mitigate the degradation due to intersymbol interference (ISI). Explain why. (See Section 3.3.2.)
  6. At what location in the system is Eb/N0 defined? (See Section 4.3.2.)
  7. Digital modulation schemes fall into one of two classes with opposite behavior characteristics. a) orthogonal signaling, b) phase/amplitude signaling. Describe the behavior of each class. (See Section 4.8.2 and 9.7.)
  8. Why do binary phase shift keying (BPSK) and quaternary phase shift keying (QPSK) manifest the same bit-error-probability relationship? Does the same hold true for M-ary pulse amplitude modulation (M-PAM) and M 2-ary quadrature amplitude modulation (M 2-QAM) bit-error probability? (See Sections 4.8.4 and
  9. In orthogonal signaling, why does error-performance improve with higher dimensional signaling? (See Section 4.8.5.)
  10. Why is free-space loss a function of wavelength? (See Section 5.3.3.)
  11. What is the relationship between received signal to noise (S/N) ratio and carrier to noise (C/N) ratio? (See Section 5.4.)
  12. Describe four types of trade-offs that can be accomplished by using an error-correcting code. (See Section 6.3.4.)
  13. Why do traditional error-correcting codes yield error-performance degradation at low values of Eb/N0 ? (See Section 6.3.4.)
  14. Of what use is the standard array in understanding a block code, and in evaluating its capability? (See Section 6.6.5.)
  15. Why is the Shannon limit of -1.6 dB not a useful goal in the design of real systems? (See Section
  16. 16. What are the consequences of the fact that the Viterbi decoding algorithm does not yield a posteriori probabilities? What is a more descriptive name for the Viterbi algorithm? (See Section 8.4.6.)
  17. 17. Why do binary and 4-ary orthogonal frequency shift keying (FSK) manifest the same bandwidth-efficiency relationship? (See Section 9.5.1.)
  18. 18. Describe the subtle energy and rate transformations of received signals: from data-bits to channel-bits to symbols to chips. (See Section 9.7.7.)
  19. 19. Define the following terms: Baud, State, Communications Resource, Chip, Robust Signal. (See Sections 1.1.3 and 7.2.2, Chapter 11, and Sections 12.3.2 and 12.4.2.)
  20. 20. In a fading channel, why is signal dispersion independent of fading rapidity? (See Section

I hope you find it useful to be challenged in this way. Now, let us describe the purpose of the book in a more methodical way. This second edition is intended to provide a comprehensive coverage of digital communication systems for senior level undergraduates, first year graduate students, and practicing engineers. Though the emphasis is on digital communications, necessary analog fundamentals are included since analog waveforms are used for the radio transmission of digital signals. The key feature of a digital communication system is that it deals with a finite set of discrete messages, in contrast to an analog communication system in which messages are defined on a continuum. The objective at the receiver of the digital system is not to reproduce a waveform with precision; it is instead to determine from a noise-perturbed signal, which of the finite set of waveforms had been sent by the transmitter. In fulfillment of this objective, there has arisen an impressive assortment of signal processing techniques.

The book develops these techniques in the context of a unified structure. The structure, in block diagram form, appears at the beginning of each chapter; blocks in the diagram are emphasized, when appropriate, to correspond to the subject of that chapter. Major purposes of the book are to add organization and structure to a field that has grown and continues to grow rapidly, and to insure awareness of the "big picture" even while delving into the details. Signals and key processing steps are traced from the information source through the transmitter, channel, receiver, and ultimately to the information sink. Signal transformations are organized according to nine functional classes: Formatting and source coding, Baseband signaling, Bandpass signaling, Equalization, Channel coding, Muliplexing and multiple access, Spreading, Encryption, and Synchronization. Throughout the book, emphasis is placed on system goals and the need to trade off basic system parameters such as signal-to-noise ratio, probability of error, and bandwidth expenditure.


Chapter 1 introduces the overall digital communication system and the basic signal transformations that are highlighted in subsequent chapters. Some basic ideas of random variables and the additive white Gaussian noise (AWGN) model are reviewed. Also, the relationship between power spectral density and autocorrelation, and the basics of signal transmission through linear systems are established. Chapter 2 covers the signal processing step, known as formatting, in order to render an information signal compatible with a digital system. Chapter 3 emphasizes baseband signaling, the detection of signals in Gaussian noise, and receiver optimization. Chapter 4 deals with bandpass signaling and its associated modulation and demodulation/detection techniques. Chapter 5 deals with link analysis, an important subject for providing overall system insight; it considers some subtleties that are often missed. Chapters 6, 7, and 8 deal with channel coding—a cost-effective way of providing a variety of system performance trade-offs. Chapter 6 emphasizes linear block codes, Chapter 7 deals with convolutional codes, and Chapter 8 deals with Reed-Solomon codes and concatenated codes such as turbo codes.

Chapter 9 considers various modulation/coding system trade-offs dealing with probability of bit-error performance, bandwidth efficiency, and signal-to-noise ratio. It also treats the important area of coded modulation, particularly trellis-coded modulation. Chapter 10 deals with synchronization for digital systems. It covers phase-locked loop implementation for achieving carrier synchronization. It covers bit synchronization, frame synchronization, and network synchronization, and it introduces some ways of performing synchronization using digital methods.

Chapter 11 treats multiplexing and multiple access. It explores techniques that are available for utilizing the communication resource efficiently. Chapter 12 introduces spread spectrum techniques and their application in such areas as multiple access, ranging, and interference rejection. This technology is important for both military and commercial applications. Chapter 13 deals with source coding which is a special class of data formatting. Both formatting and source coding involve digitization of data; the main difference between them is that source coding additionally involves data redundancy reduction. Rather than considering source coding immediately after formatting, it is purposely treated in a later chapter so as not to interrupt the presentation flow of the basic processing steps. Chapter 14 covers basic encryption/decryption ideas. It includes some classical concepts, as well as a class of systems called public key cryptosystems, and the widely used E-mail encryption software known as Pretty Good Privacy (PGP). Chapter 15 deals with fading channels. Here, we deal with applications, such as mobile radios, where characterization of the channel is much more involved than that of a nonfading one. The design of a communication system that will withstand the degradation effects of fading can be much more challenging than the design of its nonfading counterpart. In this chapter, we describe a variety of techniques that can mitigate the effects of fading, and we show some successful designs that have been implemented.

It is assumed that the reader is familiar with Fourier methods and convolution. Appendix A reviews these techniques, emphasizing those properties that are particularly useful in the study of communication theory. It also assumed that the reader has a knowledge of basic probability and has some familiarity with random variables. Appendix B builds on these disciplines for a short treatment on statistical decision theory with emphasis on hypothesis testing—so important in the understanding of detection theory. A new section, Appendix E, has been added to serve as a short tutorial on s-domain, z-domain, and digital filtering. A concise DSP tutorial also appears on the CD that accompanies the book.

If the book is used for a two-term course, a simple partitioning is suggested; the first seven chapters can be taught in the first term, and the last eight chapters in the second term. If the book is used for a one-term introductory course, it is suggested that the course material be selected from the following chapters: 1, 2, 3, 4, 5, 6, 7, 9, 10, and 12.

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  • Anonymous

    Posted January 23, 2004

    Well written & Well presented

    This is one of the few classic books in the Digital Communications subject that presents the material in an easy to understand approach while covering the core of the subject. This book is well written. The author addresses in depth the theory of Digital Communications without the complexity present in most Digital Communications books. I found this book to be useful for novel to the subject as well as professionals. I use this book as a reference.

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    Posted May 6, 2009

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