The continuing vitality of spread-spectrum communication systems and the devel-
opment of new mathematical methods for their analysis provided the motivation to
undertake this new edition of the book. This edition is intended to enable readers
to understand the current state-of-the-art in this field. Almost twenty percent of the
materialinthiseditionisnew, includingseveralnewsections, anewchapteronadap-
tive arrays and filters, and a new chapter on code-division multiple-access networks.
The multiple-input multiple-output (MIMO) technique provides higher bit rates
and better reliability in wireless systems. The efficient design of RF transceivers
has a vital impact on the implementation of this technique. This first book is com-
pletely devoted to RF transceiver design for MIMO communications. The book
covers the most recent research in practical design and applications and can be
an important resource for graduate students, wireless designers, and practical
engineers.
The first question most readers of an O’Reilly book might ask is about the choice of the
cover animal. In this case, “why a duck?” Well, for the record, our first choice was a
unicorn decked out in glitter and a rainbow sash.
That response always gets a laugh (we are sure you just giggled a little), but it also brings
to the surface a common perception of software-defined networks among many expe‐
rienced network professionals. Although we think there is some truth to this perception,
there is certainly more meat than myth to this unicorn.
Driven by the desire to boost the quality of service of wireless systems closer to that afforded
by wireline systems, space-time processing for multiple-input multiple-output (MIMO)
wireless communications research has drawn remarkable interest in recent years. Excit-
ing theoretical advances, complemented by rapid transition of research results to industry
products and services, have created a vibrant and growing area that is already established
by all counts. This offers a good opportunity to reflect on key developments in the area
during the past decade and also outline emerging trends.
The continuing vitality of spread-spectrum communication systems and the devel-
opment of new mathematical methods for their analysis provided the motivation to
undertake this new edition of the book. This edition is intended to enable readers
to understand the current state-of-the-art in this field. Almost twenty percent of the
materialinthiseditionisnew, includingseveralnewsections, anewchapteronadap-
tive arrays and filters, and a new chapter on code-division multiple-access networks.
The remainder of the material has been thoroughly revised, and I have removed a
considerable amount of material that has been superseded by more definitive results.
A mobile ad-hoc network (MANET) is formed by multiple moving nodes
equipped with wireless transceivers. The mobile nodes communicate with
each other through multi-hop wireless links, where every node can transmit
and receive information. Mobile ad-hoc networks have become increasingly
important in areas where deployment of communications infrastructure is
difficult.
An acronym for Multiple-In, Multiple-Out, MIMO communication sends the same data as several signals
simultaneously through multiple antennas, while still utilizing a single radio channel. This is a form of
antenna diversity, which uses multiple antennas to improve signal quality and strength of an RF link. The
data is split into multiple data streams at the transmission point and recombined on the receive side by
another MIMO radio configured with the same number of antennas. The receiver is designed to take
into account the slight time difference between receptions of each signal, any additional noise or
interference, and even lost signals.
Once upon a time, cellular wireless networks provided two basic services: voice
telephony and low-rate text messaging. Users in the network were separated
by orthogonal multiple access schemes, and cells by generous frequency reuse
patterns [1]. Since then, the proliferation of wireless services, fierce competition,
andthe emergenceof new service classes such as wireless data and multimediahave
resulted in an ever increasing pressure on network operators to use resources in a
moreefficient manner.In the contextof wireless networks,two of the most common
resources are power and spectrum—and, due to regulations, these resources are
typically scarce. Hence, in contrast to wired networks, overprovisioning is not
feasible in wireless networks.
The information age is exploding around us,
giving us access to dizzying amounts of data the instant it becomes available.
Smart phones and tablets provide an untethered experience that offers stream-
ing video, audio, and other media formats to just about any place on the planet.
Even people who are not “computer literate” use Facebook to catch up with
friends and family, use Google to research a new restaurant choice and print
directions to get there, or Tweet their reactions once they have sampled the
fare. The budding Internet-of-things will only catalyze this data eruption.
The infrastructure supporting these services is also growing exponentially,
and the technology that facilitates this rapid growth is virtualization.
The advent of modern wireless devices, such as smart phones and MID 1 terminals,
has revolutionized the way people think of personal connectivity. Such devices
encompass multiple applications ranging from voice and video to high-speed data
transfer via wireless networks. The voracious appetite of twenty-first century users
for supporting more wireless applications on a single device is ever increasing.
These devices employ multiple radios and modems that cover multiple frequency
bands and multiple standards with a manifold of wireless applications often running
simultaneously.
