The use of multiple antennas at the transmitter and/or at the receiver of wireless communication systems has rapidly gained in popularity over the past decade due to its four powerful performance-enhancing capabilities: array gain, spatial diversity gain, spatial multiplexing gain, and interference reduction. Multiple-input multiple-output (MIMO) technology is now considered a breakthrough in system design. Its importance is witnessed by its presence in many recent standards, such as IEEE802.11n, worldwide interoperability for microwave access (WiMAX), and the 3GPP long-term evolution (LTE).

This book is among the more gentle introductions to the MIMO concept. Chapter 1 provides a short overview of MIMO communication. It includes a section on key matrix properties and identities that are used throughout the book. The different types of MIMO schemes are explained, fundamental concepts such as spatial diversity and spatial multiplexing are defined, and performance results are presented. Chapter 2 is devoted to the derivation of the MIMO capacity formula, which predicts the maximum error-free data rate that can be supported by a MIMO communication system. This formula is used later in chapter 3 to provide conceptual insights into how multiple antennas enable an increase of spectral efficiency. Based on the concepts of information theory, the capacity of single-input single-output (SISO) systems is derived first. Chapter 3 explores the implications of the MIMO capacity formula and uses it to compute the communications capacities of MIMO systems under various assumptions. The concepts of eigenmodes and channel rank are examined, and the spatial multiplexing technique called eigen-beamforming is derived and explained in this chapter. Eigen-beamforming utilizes the properties of estimated channels by performing singular value decomposition on the channel matrix.

MIMO techniques are designed to operate in a scattering environment that gives rise to multipath propagation. Without scattering and multipath, the channels between the various combinations of transmit and receive antennas are correlated, which results in poor MIMO performance. Chapter 4 discusses radio frequency (RF) propagation in general and develops the terminology and concepts used in characterizing multipath propagation in particular. Chapter 5 presents several theoretical MIMO propagation models that have been developed based on theory and empirical results. Expressions for the channel model when both Rayleigh fading and line-of-sight propagation exist are also presented. These models are used to derive expressions for the dependence of the MIMO capacity on antenna correlation and on the amount of scattering in the channel.

Chapter 6 describes Alamouti space-time coding, which is an important practical MIMO technique used to achieve transmit diversity. This chapter begins by examining the performance of ideal maximal ratio receive combining and then shows how Alamouti coding achieves diversity gain equal to a maximal ratio receive combiner. Orthogonal space-time block codes (OSTBCs) are discussed in chapter 7 because they have simple decoding schemes and are used in practical wireless systems. Space-time trellis coding concepts are also presented briefly. Chapter 8 addresses spatial multiplexing, which comprises the second major class of MIMO techniques. Spatial multiplexing refers to transmitting multiple independent data streams over multipath channels, without the need to increase the bandwidth. Chapter 9 discusses MIMO over broadband channels. Up to this point in the book, the assumption is that the bandwidth of the transmitted signal is smaller than the coherence bandwidth of the channel; however, in modern wireless communication systems this is seldom the case. In practice, broadband systems operate by employing orthogonal frequency division multiplex (OFDM) signaling, so this chapter reviews OFDM and then shows how it is used with the narrowband MIMO techniques developed earlier to support broadband service.

Chapter 10 discusses an important practical aspect of MIMO communications: the estimation of the properties of the communications channel. Since most MIMO techniques require that either the transmitter or the receiver (or both) have knowledge of the channel, channel estimation techniques are an essential aspect of any MIMO communication system. This chapter discusses the fundamental concepts used in MIMO channel estimation and describes how practical MIMO systems perform this function. Chapter 11 demonstrates how those concepts are applied in real-world wireless communications systems. For this purpose, the book describes two popular wireless families of standards, Wi-Fi and LTE/LTE-Advanced, which are used for wireless local area network (LAN) applications and conventional cellular communications, respectively. The book concludes with six short appendices, where important equations or theorems presented in the book are derived.

MIMO, like any other topic in communication theory, is very mathematics driven and not for the fainthearted. This book is one of the more accessible introductions to the topic. Well structured, it leads the reader step by step through all important concepts. This is a book for researchers and communication engineers alike.