Wireless Communications: Signal Processing Perspectives, 1/e

Wireless Communications: Signal Processing Perspectives, 1/e

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H. Vincent Poor, Princeton University

Gregory W. Wornell, MIT, Cambridge, Massachusetts




These are exciting times in which to be involved in wireless communications research. The field is growing at an explosive rate, stimulated by a host of important emerging applications ranging from third-generation mobile telephony [5, 10, 17, 18, 20], wireless personal communications [1, 7, 8, 9, 13, 14, 16], and wireless subscriber loops, to radio and infrared indoor communications [2, 4, 6, 11, 15], nomadic computing [3, 12], and wireless tactical military communications [10]. These and other newly envisioned networks have both profound social implications and enormous commercial potential. For system planners and designers, the projections of rapidly escalating demand for such wireless services present major challenges, and meeting these challenges will require sustained technical innovation on many fronts.

Characteristics of Wireless Services

Many of the main technical challenges stem from three key characteristics inherent in existing and envisioned wireless services. First, the communication channels over which radio-frequency (RF), infrared, underwater acoustic, and other wireless systems must operate are all complex and highly dynamic. These channels suffer from numerous physical impairments that severely impact system performance, important examples of which include fading due to multipath propagation and interference from extra-network sources. Moreover, channel characteristics often change at rates that can be significant relative to system time scales, particularly in mobile communications applications.

Second, many emerging wireless applications are aimed toward providing universal access at relatively high data rates. Providing these capabilities is increasingly accomplished through the use of random multiple-access protocols, which while natural, lead to a still more complicated wireless channel. In particular, in such cases multiple- access/cochannel interference is at least as significant an impairment as noise and other forms of interference in limiting system performance. Another aspect of the universal access paradigm is that network demands more generally are highly dynamic, with the users entering and leaving the network having diverse quality-of-service requirements. At the same time, the network itself is often reconfigurable and typically part of a larger heterogeneous system of networks, meaning that the associated network resources are also highly dynamic as well.

Finally, driving much of the development of wireless technology is the need for truly portable communications. Many applications demand a system infrastructure that can be rapidly and flexibly deployed. And the end users themselves require a lightweight, compact interface to the network in the form of a pocket-sized, battery-powered transceiver or terminal. As such, complexity and power consumption are critical issues in the design of mobile systems and give rise to important practical constraints.

What all these diverse challenges have in common is the very central role that signal processing ultimately has to play in meeting them. Indeed, increasingly we are seeing many key problems in wireless communication system design being approached from signal processing perspectives, yielding solutions in the form of advanced signal processing algorithms and having implementations on flexible digital signal processing architectures. In turn, this evolution is stimulating both significantly heightened interest in signal processing methodologies within the wireless communications community and considerable recent growth of interest within the signal processing community in wireless communications applications.

The idea of this book evolved from these basic observations. As such, its aim is to provide a signal processing perspective on the field of wireless communications by describing the state of the art and recent research developments in this area, and also by identifying key directions in which further research is needed. The treatment comprises eight contributed chapters and an epilogue, spanning some of the main focus areas of signal processing research at both the physical and network layers of the wireless system hierarchy.

Overview of Chapters

A brief outline of the constituent chapters is as follows.
Chapter 1 is the first of four that focus primarily on issues at the physical layer. In this chapter, Wornell focuses on the role of signal processing in creating and exploiting diversity for counteracting the effects of multipath-induced signal fading. Multipath propagation effects generally lead to a channel signal-to-noise ratio characteristic that varies as a function of frequency, time, and space; diversity techniques take advantage of the fact that typically not all parts of such channels fade simultaneously. This chapter describes the key ways in which linear signal processing algorithms can be used at the transmitters and receivers of multiuser communication systems to realize effective forms of diversity with very low computational complexity. Such diversity is achieved by, in effect, spreading the transmission of symbols spectrally, temporally, and/or spatially to within the limits imposed by bandwidth, delay, and other physical system constraints. Spread-spectrum code-division multiple- access (CDMA) protocols and multiple-element antenna arrays at transmitters and receivers are discussed as means for realizing spreading of this type. All such techniques have the characteristic that they improve both average and worst-case performance and can be used in conjunction with---or as an alternative to—coding in such systems. The various techniques in Chapter 1 are described and interrelated within a common multirate/multichannel signal processing framework. This framework not only provides some useful new perspectives on traditional approaches for making use of diversity but also lends itself naturally to the description of several promising, more recently introduced methods.

In Chapter 2, Honig and Poor describe the analogous role that signal processing algorithms have to play in suppressing interference in the receivers of wireless systems. The primary focus of the chapter is on suppression of interference that arises due to the nonorthogonal multiplexing inherent in random-access protocols such as CDMA. While these formats allow systems to optimize their use of bandwidth in channels subject to fading, bursty traffic, and time-varying user populations, overall system performance depends critically on the degree to which the accompanying increase in interference is effectively eliminated at the receiver. Unlike the ambient noise that limits all electronic communications, this multiple-access interference is highly structured. This structure provides both challenges and opportunities for the use of advanced signal processing to mitigate the effects of the interference. Chapter 2 develops the basic signal processing concepts relevant to this and closely related classes of interference suppression problems such as multipath mitigation, narrowband interference suppression, and beamforming. These problems are treated within the basic framework of the CDMA transmission protocol, although many of the techniques described are equally applicable to any system in which structured interference is a major impairment. Moreover, because typically the wireless channel is rapidly time-varying, the emphasis in the chapter is on adaptive methods. This is a very active area of current research, and a number of open issues are discussed.

Wireless channels are ultimately limited by their bandwidths. As data rates become more demanding with respect to the channel bandwidth, dispersion and the attendant intersymbol interference become a critical, performance- limiting issue. The equalization of wireless channels presents major signal processing challenges not present in more traditional wireline equalization, again both because of the rapid time-variation in the channel and because of the additional sources of interference that compound the problem. In Chapter 3, Papadopoulos discusses the principal issues arising in the problem of equalizing wireless channels in multiuser environments and describes several of the key algorithmic structures being explored for their solution. The development of this chapter emphasizes a powerful multiple-input multiple-output linear systems perspective within which equalizers that efficiently and jointly mitigate both intersymbol and multiple-access interference are described. As the development reflects, the resulting equalizers constitute natural and powerful generalizations of equalizers used in many traditional communications applications. Representative examples of both training-based and blind algorithms from this particularly active area of research are discussed.

In Chapter 4, Paulraj, Papadias, Reddy, and van der Veen turn to the problem of space-time processing for wireless systems. This chapter is complementary to the preceding three in that it also considers issues of spatial diversity, interference suppression, and equalization in the wireless channel. However, the focus of this chapter is on explicit space- time signal processing strategies that can be employed in these pursuits. In particular, this chapter develops array signal processing for both single-user and multiuser systems with the underlying assumptions of linear modulation and time-division multiple-access transmission. Key elements of this treatment are the issues of blind channel identifiability and linear channel equalizability in the presence of both intersymbol interference and cochannel interference.

Ensuring that emerging wireless networks operate efficiently while meeting the quality-of-service requirements of end users increasingly requires sophisticated strategies for dynamic allocation of power, bandwidth, and other resources. Moreover, many of the key system design issues are particularly challenging because they span both the physical layer and the network layer within the wireless communication system hierarchy---two layers whose development has traditionally been treated separately and by culturally different subcommunities. In Chapter 5, Tse and Hanly explore some key aspects of the interplay between these two layers in wireless architectures. In particular, they discuss natural and practical notions of capacity for a cellular system in terms of the quality-of-service requirements of the participating users. Central to their development is the powerful concept of a user's effective bandwidth, which summarizes the fraction of a cell's resources that is required to support a user at its desired target signal-to-interference ratio, given the class of interference suppression techniques being implemented at the physical layer. Through this framework, several important insights into the problem of optimal power control are obtained.

Focusing further on the network layer, one of the major thrusts of current research in wireless communications is the development of techniques for introducing multimedia capability into wireless networks. The high bandwidth requirements and quality-of-service expectations of multimedia traffic place major demands on all signal processing functions of the wireless system. In Chapter 6, Haskell, Messerschmitt, and Yun consider the major signal processing issues that arise from the needs of such multimedia transmission. In particular, the chapter examines four primary signal processing functions—data compression, encryption, modulation, and error control—in this context and considers the impact of multimedia traffic on the backbone network. The authors propose a novel architectural framework for the design of both network protocols and signal processing algorithms that allows for the resolution of most issues arising in wireless multimedia networks. In outlining this framework, the authors also identify a number of active research areas, both in networking and signal processing.

In Chapter 7, Ramchandran and Vetterli explore issues of data compression (i.e., source coding) and error control (i.e., channel coding) in wireless multimedia networks in more detail. In particular, this chapter focuses on the interaction between source and channel coding in such contexts. The heterogeneous nature of both the information sources and the physical channels in these applications introduces issues that are not addressed by more traditional information-theoretic approaches to these problems. Joint source and channel coding techniques are featured as an approach to some of the key challenges in these contexts, and promising techniques based on multiresolution signal processing in the form of wavelet- and subband-based source coders together with multilevel error-correcting coders are emphasized. The chapter illustrates how such techniques can be particularly well suited to the demands of speech, image, and video transmission over wireless channels, allowing, for example, rate adaptation and flexible control over noise immunity.

Finally, while much of the discussion in Chapters 1 through 7 applies, in principle, to general wireless communication systems, these chapters are largely developed with RF systems in mind. As an illustration of other kinds of propagation environments and how they have their own unique sets of issues in terms of wireless system design, in Chapter 8, Brady and Preisig explore wireless communication through the underwater acoustic channel. In practice, this channel is an important one in a number of scientific and military applications involving underwater communication, and it presents particularly challenging problems for signal processing design. Indeed, many of the impairments encountered on wireless RF channels are experienced at even more severe levels in the underwater acoustic channel. As such, this latter channel provides a useful context in which to explore and develop some of the most aggressive and signal-processing- intensive emerging techniques.

Finally, in the epilogue, Viterbi provides a philosophical view of the forces driving the development of wireless technology. In particular, he identifies four laws, two each from the natural sciences and the social sciences, that have formed the basis for the development of digital wireless communication networks. This essay describes their interaction, as well as their logical support for spread-spectrum multiple-access techniques.

Audience for This Book

Collectively, these nine contributions represent a sampling of some of the main themes and directions being pursued within this active field of research. While broad in scope, this volume does not attempt to be comprehensive in its coverage. Indeed, given the brisk pace at which developments are currently taking place, thorough coverage would be almost impossible. Instead, the goal of the book is a more modest one. The topics are representative rather than exhaustive, and the treatment is aimed toward developing perspectives and insights that will allow readers to appreciate what some of the fundamental challenges are, what the scope of current activities is, and where some of the major research opportunities lie. For newcomers, this book can be used as a starting point for navigating the rapidly growing body of literature on various aspects of the topic. For those already active in the field, this book can provide an opportunity to reflect on one's work in the context of developments in other aspects of the topic and to explore interconnections between these developments that may lead to fundamentally new research directions.

More broadly, it is our hope that this volume will be a useful resource to the dual audience it is intended to serve: both to the signal processing community as it becomes more active in the wireless communications area, and to the communications community as it increasingly embraces signal processing algorithms and architectures in the development of efficient wireless systems of the future. More generally, there is tremendous opportunity for major advances to come from expanded dialog and interaction between these two communities, and thus it is also our hope that projects such as this can ultimately be vehicles for fostering such collaboration.

H. Vincent Poor
Gregory W. Wornell

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List of Contributors
David Brady Northeastern University
Stephen V. Hanly University of Melbourne, Australia
Paul Haskell DiviComm, Inc.
Michael L. Honig Northwestern University
David G. Messerschmitt University of California, Berkeley
Constantinos B. Papadias Lucent Technologies (Bell Labs Research)
Haralabos C. Papadopoulos Massachusetts Institute of Technology
Arogyaswami J. Paulraj Stanford University
H. Vincent Poor Princeton University
James C. Preisig Woods Hole Oceanographic Institution
Kannan Ramchandran University of Illinois, Urbana-Champaign
Vellenki U. Reddy Indian Institute of Science, Bangalore, India
David N. C. Tse University of California, Berkeley
Alle-Jan van der Veen Delft University of Technology, The Netherlands
Martin Vetterli Ecole Polytechnique F<\e'>d<\e'>rale de Lausanne, Switzerland
Andrew J. Viterbi Qualcomm, Inc.
Gregory W. Wornell Massachusetts Institute of Technology
Louis Yun ArrayComm, Inc.


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