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2004 | Buch | 3. Auflage

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Digital Communication

verfasst von: John R. Barry, Edward A. Lee, David G. Messerschmitt

Verlag: Springer US

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Über dieses Buch

This book concerns digital communication. Specifically, we treat the transport of bit streams from one geographical location to another over various physical media, such as wire pairs, coaxial cable, optical fiber, and radio. We also treat multiple-access channels, where there are potentially multiple transmitters and receivers sharing a common medium. Ten years have elapsed since the Second Edition, and there have been remarkable advances in wireless communication, including cellular telephony and wireless local-area networks. This Third Edition expands treatment of communication theories underlying wireless, and especially advanced techniques involving multiple antennas, which tum the traditional single-input single-output channel into a multiple-input multiple-output (MIMO) channel. This is more than a trivial advance, as it stimulates many advanced techniques such as adaptive antennas and coding techniques that take advantage of space as well as time. This is reflected in the addition of two new chapters, one on the theory of MIMO channels, and the other on diversity techniques for mitigating fading. The field of error-control coding has similarly undergone tremendous changes in the past decade, brought on by the invention of turbo codes in 1993 and the subsequent rediscovery of Gallager's low-density parity-check codes. Our treatment of error-control coding has been rewritten to reflect the current state of the art. Other materials have been reorganized and reworked, and three chapters from the previous edition have been moved to the book's Web site to make room.

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Inhaltsverzeichnis

Frontmatter

Chap. 1. Introduction

Abstract

Digital transmission of information has sufficiently overwhelming advantages that it increasingly dominates communication systems, and certainly all new designs. In computer-to-computer communication, the information to be transported is inherently digital. But information that at its source is inherently continuous time (or continuous space) and continuous amplitude, like voice, music, pictures, and video, can be represented, not exactly but accurately, by a collection of bits. Why does it make sense to do so?

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 2. Deterministic Signal Processing

Abstract

In this chapter we review some basic concepts in order to establish the notation used in the remainder of the book. In addition, we cover in more detail several specific topics that some readers may not be familiar with, including complex signals and systems, the convergence of bilateral Z-transforms, and signal-space geometry. The latter allows simple geometric interpretation of many signal processing operations, and demonstrates relationships among many seemingly disparate topics

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 3. Stochastic Signal Processing

Abstract

Although modulation and demodulation are deterministic, the information to be transmitted, as well as the noise encountered in the physical transmission medium, is random or stochastic. These phenomena cannot be predicted in advance, but they have certain predictable characteristics which can be summarized in a random process model. The design of a digital communication system heavily exploits these characteristics

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 4. Limits of Communication

Abstract

In the late 1940’s, Claude Shannon of Bell Laboratories developed a mathematical theory of information that profoundly altered our basic thinking about communication, and stimulated considerable intellectual activity, both practical and theoretical. This theory, among other things, gives us some fundamental boundaries within which communication can take place. Often we can gain considerable insight by comparing the performance of a digital communication system design with these limits

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 5. Pulse-Amplitude Modulation

Abstract

An information-bearing signal must conform to the limitations of its channel. While the bit streams we wish to transmit are inherently discrete-time, all physical media are continuous-time in nature. Hence, we need to represent the bit stream as a continuous-time signal for transmission, a process called modulation

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 6. Advanced Modulation

Abstract

In Chapter 5 we described transmitter and receiver design using PAM. In this chapter we extend to other modulation schemes. We begin by considering a general form of modulation called M-ary modulation, in which one of M signals is transmitted every signaling interval. In this general setting, we present the correlation and projection receivers as practical means for implementing the minimum-distance receiver, and we present a union-bound approximation for the resulting probability of error in the presence of AWGN

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 7. Probabilistic Detection

Abstract

A fundamental problem in digital communications is the corruption of the transmitted signal by noise. The minimum-distance philosophy for receiver design is reasonably robust in the presence of noise, but two questions arise: when is it optimal? And what should be done when it is not? In this chapter we start with the statistics of the noise and develop a theory of optimal detection for both discrete-time and continuous-time channels. With this theory, we identify the circumstances under which the minimum-distance receiver is optimal. Moreover, we take a systematic approach to receiver design based on a probabilistic characterization of the noise that is applicable to a wide range of applications beyond the classical model of additive white Gaussian noise, including those for which minimizing distance is not optimal. The probabilistic tools developed in this chapter play an important role in iterative decoding of error-control codes (Chapter 12)

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 8. Equalization

Abstract

In PAM, intersymbol interference (ISI) results from linear amplitude and phase distortion in the channel that broadens the pulses and causes them to interfere with one another. The Nyquist criterion specifies a condition on the received pulses under which there is no ISI. Generally this or a similar condition is not satisfied unless we equalize the channel, meaning roughly that we filter to compensate for the channel distortion. Unfortunately, any equalization of amplitude distortion also enhances or amplifies any noise introduced by the channel, called noise enhancement. There is therefore a tradeoff between accurately minimizing intersymbol interference and minimizing the noise at the slicer input. Ultimately, of course, our goal is to minimize the probability of error

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 9. Adaptive Equalization

Abstract

In Chapter 8 we derived a set of receiver structures that counter intersymbol interference under the assumptions of a known channel and unconstrained implementation complexity. The resulting structures are impractical for most applications in the exact form we derived them for several reasons. First, assumption of a known received pulse shape is unrealistic, particularly for channels such as the digital subscriber loop (with bridged taps), radio channel (with selective fading), and voiceband data channel, where there are significant variations in the channel affecting the reception. Thus, the received pulse shape is not actually known in advance for these channels, and is sometimes varying during actual transmission. Second, the receiver structures we derived usually have an infinite number of coefficients, and cannot be realized. Third, our optimizations did not take into account significant impairments such as timing jitter and timing offset, which must be considered in the design of receive filtering

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 10. MIMO Communications

Abstract

Prior chapters were concerned with communication across a single-input single-output (SISO) channel for which the channel input and channel output were scalar-valued signals. In this chapter we study the problem of communicating across a multiple-input multiple-output (MIMO) channel, for which the channel input and output are vector-valued signals. In doing so, this chapter adds another impediment to the mix. Not only must a receiver contend with ISI and noise, but also with interference between the inputs. Depending on the application, this interference may be referred to as co-channel interference, adjacent-channel interference, crosstalk, or multiuser interference. Whatever its name, the presence of this interference is what distinguishes this chapter from previous chapters

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 11. Fading and Diversity

Abstract

The previous chapter examined MIMO communications from an abstract point of view, with an eye towards all types of MIMO applications. In contrast, this chapter specializes to wireless MIMO applications, which suffer from not only additive noise and multiuser interference but also from multipath fading

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 12. Error Control

Abstract

Error-control coding is the name given to the process of converting source bits into transmitted symbols so as to make possible reliable communications despite the presence of noise. As shown in Fig. 12–1, a channel coder precedes the mapping of bits to symbols at the transmitter. The channel coder constrains the symbol sequence a _k so that only a strict subset of all possible symbol sequences can be transmitted. There is thus redundancy in the coded sequence, which can be exploited at the receiver to improve the robustness to noise

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 13. Signal-Space Coding

Abstract

The binary error-control schemes of Chapter 12 were designed specifically for binary modulation formats. They are ideally suited for the low-SNR regime where the target spectral efficiency is small. This chapter treats the problem of error control when the target spectral efficiency is large. In this scenario, one might be tempted to concatenate a binary encoder with an independently designed QAM symbol mapper, but the resulting performance will usually be poor

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 14. Phase-Locked Loops

Abstract

In a continuous-time world, establishing a common time base at physically separated locations presents some serious challenges. Typical systems use independent time bases, frequently derived from crystal oscillators, as shown in Fig. 14–1. Although crystal oscillators provide extremely accurate timing references at low cost, “extremely accurate” is not adequate to maintain the integrity of discrete-time data. Timing references often have to be identical, at least in the sense of long term averages. In other words, systems must be synchronized. Underlying most synchronization techniques is the phase-locked loop (PLL). In this chapter we derive the basic principles of PLLs. Two practical applications, carrier and timing recovery, are treated in-depth in Chapters 15 and 16

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 15. Carrier Recovery

Abstract

In passband systems, the carrier frequency is generated in the transmitter from a local timing reference such as a crystal oscillator. As we saw in Chapters 5 and 6, coherent demodulation of a passband signal requires exactly the same carrier frequency and phase to perform the demodulation. But the receiver usually has an independent timing reference, as illustrated in Fig. 14–1. Deriving the carrier frequency and phase from the data bearing signal is the topic of this chapter

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 16. Timing Recovery

Abstract

The purpose of timing recovery is to recover a clock at the symbol rate or a multiple of the symbol rate from the modulated waveform. This clock is required to convert the continuous-time received signal into a discrete-time sequence of data symbols

John R. Barry, Edward A. Lee, David G. Messerschmitt

Chap. 17. Multiple Access Alternatives

Abstract

Thus far in this book we have discussed the signal processing necessary for digital communications from one point to another over a communications medium. The remainder of the book will begin to address the realization of a digital communications network in which many users simultaneously communicate with one another. One of the key issues that must be resolved in moving from a single digital communication system to a network is how we provide access to a single transmission medium for two or more (typically many more) users. In moving from a single transmitter and receiver to the sharing of media by multiple users, we must address two primary issues. First, how do we resolve the contention that is inherent in sharing a single resource. This issue is discussed in this chapter. Secondly, how do we synchronize all the users of the network as an aid to resolving the contention

John R. Barry, Edward A. Lee, David G. Messerschmitt

Backmatter

Titel: Digital Communication
verfasst von: John R. Barry
Edward A. Lee
David G. Messerschmitt
Copyright-Jahr: 2004
Verlag: Springer US
Electronic ISBN: 978-1-4615-0227-2
Print ISBN: 978-1-4613-4975-4
DOI: https://doi.org/10.1007/978-1-4615-0227-2