1.1 Motivation

Wireless communications is one of the most active areas of technology development of our time. This development is being driven primarily by the transformation of what has been largely a medium for supporting voice telephony into a medium for supporting other services, such as the transmission of video, images, text, and data. Thus, similar to the developments in wireline capacity in the 1990s, the demand for new wireless capacity is growing at a very rapid pace. Although there are, of course, still a great many technical problems to be solved in wireline communications, demands for additional wireline capacity can be fulfilled largely with the addition of new private infrastructure, such as additional optical fiber, routers, switches, and so on. On the other hand, the traditional resources that have been used to add capacity to wireless systems are radio bandwidth and transmitter power. Unfortunately, these two resources are among the most severely limited in the deployment of modern wireless networks: radio bandwidth because of the very tight situation with regard to useful radio spectrum, and transmitter power because mobile and other portable services require the use of battery power, which is limited. These two resources are simply not growing or improving at rates that can support anticipated demands for wireless capacity. On the other hand, one resource that is growing at a very rapid rate is that of processing power. Moore's Law, which asserts a doubling of processor capabilities every 18 months, has been quite accurate over the past 20 years, and its accuracy promises to continue for years to come. Given these circumstances, there has been considerable research effort in recent years aimed at developing new wireless capacity through the deployment of greater intelligence in wireless networks (see, e.g., [145, 146, 270, 376, 391] for reviews of some of this work). A key aspect of this movement has been the development of novel signal transmission techniques and advanced receiver signal processing methods that allow for significant increases in wireless capacity without attendant increases in bandwidth or power requirements. The purpose of this book is to present some of the most recent of these receiver signal processing methods in a single place and in a unified framework.

Wireless communications today covers a very wide array of applications. The telecommunications industry is one of the largest industries worldwide, with more than $1 trillion in annual revenues for services and equipment. (To put this in perspective, this number is comparable to the gross domestic product of many of the world's richest countries , including France, Italy, and the United Kingdom.) The largest and most noticeable part of the telecommunications business is telephony. The principal wireless component of telephony is mobile (i.e., cellular) telephony. The worldwide growth rate in cellular telephony is very aggressive , and analysts report that the number of cellular telephony subscriptions worldwide has now surpassed the number of wireline (i.e., fixed) telephony subscriptions. Moreover, at the time of this writing in 2003, the number of cellular telephony subscriptions worldwide is reportedly on the order of 1.2 billion. These numbers make cellular telephony a very important driver of wireless technology development, and in recent years the push to develop new mobile data services, which go collectively under the name third-generation (3G) cellular , has played a key role in motivating research in new signal processing techniques for wireless. However, cellular telephony is only one of a very wide array of wireless technologies that are being developed very rapidly at the present time. Among other technologies are wireless piconetworking (as exemplified by the Bluetooth radio-on-a-chip) and other personal area network (PAN) systems (e.g., the IEEE 802.15 family of standards), wireless local area network (LAN) systems (exemplified by the IEEE 802.11 and HiperLAN families of standards, called WiFi systems), wireless metropolitan area network (MAN) systems (exemplified by the IEEE 802.16 family of standards, called WiMax systems), other wireless local loop (WLL) systems, and a variety of satellite systems. These additional wireless technologies provide a basis for a very rich array of applications, including local telephony service, broadband Internet access, and distribution of high-rate entertainment content such as high-definition video and high-quality audio to the home, within the home, to automobiles, and so on (see, e.g., [9, 41, 42, 132, 159, 161, 164, 166, 344, 361, 362, 365, 393 “395, 429, 437, 449, 457, 508, 558, 559] for further discussion of these and related applications). Like 3G, these technologies have spurred considerable research in signal processing for wireless.

These technologies are supported by a number of transmission and channel-assignment techniques, including time-division multiple access (TDMA), code-division multiple access (CDMA), and other spread-spectrum systems, orthogonal frequency-division multiplexing (OFDM) and other multicarrier systems, and high-rate single-carrier systems. These techniques are chosen primarily to address the physical properties of wireless channels, among the most prominent of which are multipath fading, dispersion, and interference. In addition to these temporal transmission techniques, there are spatial techniques, notably beamforming and space-time coding, that can be applied at the transmitter to exploit the spatial and angular diversity of wireless channels. To obtain maximal benefit from these transmission techniques, to exploit the diversity opportunities of the wireless channel, and to mitigate the impairments of the wireless channel, advanced receiver signal processing techniques are of interest. These include channel equalization to combat dispersion, RAKE combining to exploit resolvable multipath, multiuser detection to mitigate multiple-access interference, suppression methods for co-channel interference, beamforming to exploit spatial diversity, and space-time processing to jointly exploit temporal and spatial properties of the signaling environment. These techniques are all described in the ensuing chapters.