Research and development of digital communications systems is undergoing a revolution fueled by rapid advances in technology. With the ever-growing sophistication of signal processing and computation, advances in communication theory have an increasing potential to bridge the gap between practically feasible channel utilization and the fundamental information theoretic limits on channel capacity. If conquering channel capacity is the manifest destiny of communications technology, the need for efficient use of channel bandwidth and transmission power is felt most acutely in wireless communication, where the exponentially-growing demand for data rate must be accommodated in a finite segment of the radio spectrum. To add to the challenge, information is transmitted not by a single source but by several uncoordinated, bursty and geographically apart sources.

Multiuser Detection deals with the demodulation of mutually interfering digital streams of information. Cellular telephony, satellite communication, high-speed data transmission lines, digital radio/television broadcasting, fixed wireless local loops, and multitrack magnetic recording are some of the communication systems subject to multiaccess interference. The superposition of transmitted signals may originate from nonideal characteristics of the transmission medium, or it may be an integral part of the multiplexing method as in the case of Code-Division Multiple-Access. Multiuser Detection (also known as co-channel interference suppression, multiuser demodulation, interference cancellation, etc.) exploits the considerable structure of the multiuser interference in order to increase the efficiency with which channel resources are employed.

Although isolated generalizations of digital communication models to multi-input multi-output channels had taken place as early as the 1960s, it was not until the mid 1980s that Multiuser Detection started developing as a cohesive body of analytical results that took into account the specific features of multiuser channels. Since then, the number of researchers working on this discipline has rapidly multiplied, to the point where it is now one of the most active and vibrant branches of digital communications. The extensive set of references collected in this book, although not pretending to be comprehensive in any way, gives evidence of the level of activity in Multiuser Detection in the last few years. The bibliographical notes at the end of each chapter provide an account of the development of the main results as well as a snapshot of the current state-of-the-art. I can only hope that that part of the book will become quickly obsolete in view of the speed at which the field is currently evolving.

While aiming for a fairly comprehensive coverage of the design and analysis of receivers for multiaccess channels, my goal has been to distill the elements of multiuser detection in the simplest setting that brings out the key concepts. A fertile ground for geometrical intuition, the linearly-modulated synchronous multiuser channel proves to be a garden of Euclidean delights. Borrowing from the tradition in multiuser information theory, most of the main ideas are first introduced in the two-user channel, which emerges as a powerful pedagogical tool.

Chapter 1 gives a brief introduction to the main approaches in multiaccess communications. Chapter 2 introduces the basic channel models used throughout the book. The main paradigm is the Code-Division Multiple-Access channel, in which each user modulates its own signature waveform. This channel is general enough to encompass orthogonal and non-orthogonal multiplexing methods, with or without spread-spectrum signaling. Chapter 3 covers background material on hypothesis testing and single-user detection, and analyzes the effects of multiaccess interference on the single-user receiver. Chapter 4 is devoted to the design and analysis of optimum multiuser detectors. Linear signal processing for multiuser detection is studied in Chapters 5 and 6, with and without the constraint of complete multiuser interference suppression, respectively. Adaptive linear multiuser detection is covered in Chapter 6. Chapter 7 deals with nonlinear multiuser detectors that use decisions on the interfering digital streams in order to mitigate their effect.

Whether it is used as a textbook, self-study tool or research reference, the set of over 300 problems is an essential component of this book. They range from simple drill exercises to research results that complement the theory expounded in the text. I hope the reader will draw some sense of accomplishment from solving them.

No prerequisites are assumed beyond undergraduate-level probability, linear algebra and an introductory course on communications. At Princeton, I have used this text to teach a one-semester course on Multiuser Detection to first- and second-year graduate students with diverse backgrounds. Although previous or concurrent exposure to a conventional detection and estimation course may be beneficial, Chapter 3 gives a self-contained presentation of the required material. A typical ``single-user'' digital communications course covering the fundamentals of equalization is not required either. In fact, it is my contention that (synchronous) multiaccess channels provide an easier setting for learning many of the fundamentals of equalization in digital communications than the conventional single-user intersymbol interference channel.

The text contains substantial material that can be tailored to serve as the core of various Master's and doctoral courses on multiuser communication. In addition, the book can be used as a self-study guide for practicing engineers and as a reference volume for academic and industrial researchers in communications and signal processing.