By inventing the wireless transmitter or radio in 1897, the Italian physicist Tomaso
Guglielmo Marconi added a new dimension to the world of communications. This
enabled the transmission of the human voice through space without wires. For this
epoch-making invention, this illustrious scientist was honored with the Nobel Prize
for Physics in 1909. EVEN today, students of wireless or radio technology remember
this distinguished physicist with reverence. A new era began in Radio
Communications.
It was only a few years ago that “ubiquitous connectivity” was recognized as the future of
wireless communication systems. In the era of ubiquitous connectivity, it was expected that
the broadband mobile Internet experience would be pervasive, and seamless connectivity on
a global scale would be no surprise at all. The quality of service would be guaranteed no
matter when/where/what the users wanted with the connectivity. Connectivity would EVEN be
extended to object-to-object communication, where no human intervention was required. All
objects would become capable of autonomous communication.
This book was born from the perception that there is much more to spectrum use
and sharing than one sees reflected in publications, whether academic, commercial
or political. the former – in good research style – tend towards reductionism and
concentrate on specific, detailed aspects. commercial publications tend to empha-
size the positive aspects and they tend to put promise above practice. Given the ever
increasing pace of technology development and recent successes of new wireless
technologies, some pundits predict large-scale spectrum scarcity, potentially lead-
ing to economic catastrophe. Although economic theory has a hard time explaining
recent EVENts that shook the world economy, the notion of spectrum scarcity is intui-
tively acceptable, EVEN if not correct or immediately relevant.
Since the first edition of the book was published, the field of modeling and simulation of
communication systems has grown and matured in many ways, and the use of simulation as a
day-to-day tool is now EVEN more common practice. Many new modeling and simulation
approaches have been developed in the recent years, many more commercial simulation
packages are available, and the evolution of powerful general mathematical applications
packages has provided still more options for computer-aided design and analysis. With the
current interest in digital mobile communications, a primary area of application of modeling
and simulation is now to wireless systems of a different flavor than the traditional ones.
Until the mid-1990s most readers would probably not have EVEN come across the term soft-
ware defined radio (SDR), let alone had an idea what it referred to. Since then SDR has made
the transition from obscurity to mainstream, albeit still with many different understandings of
the terms – software radio, software defined radio, software based radio, reconfigurable radio.
Radio frequency spectrum is a scarce and critical natural resource that is utilized for
many services including surveillance, navigation, communication, and broadcast-
ing. Recent years have seen tremendous growth in the use of spectrum especially by
commercial cellular operators. Ubiquitous use of smartphones and tablets is one
of the reasons behind an all-time high utilization of spectrum. As a result, cellular
operators are experiencing a shortage of radio spectrum to meet bandwidth
demands of users. On the other hand, spectrum measurements have shown that
much spectrum not held by cellular operators is underutilized EVEN in dense urban
areas. This has motivated shared access to spectrum by secondary systems with no
or minimal impact on incumbent systems. Spectrum sharing is a promising
approach to solve the problem of spectrum congestion as it allows cellular operators
access to more spectrum in order to satisfy the ever-growing bandwidth demands of
commercial users.
A wireless communication network can be viewed as a collection of nodes, located in some domain, which
can in turn be transmitters or receivers (depending on the network considered, nodes may be mobile users,
base stations in a cellular network, access points of a WiFi mesh etc.). At a given time, several nodes
transmit simultaneously, each toward its own receiver. Each transmitter–receiver pair requires its own
wireless link. The signal received from the link transmitter may be jammed by the signals received from
the other transmitters. EVEN in the simplest model where the signal power radiated from a point decays in
an isotropic way with Euclidean distance, the geometry of the locations of the nodes plays a key role since
it determines the signal to interference and noise ratio (SINR) at each receiver and hence the possibility of
establishing simultaneously this collection of links at a given bit rate. The interference seen by a receiver is
the sum of the signal powers received from all transmitters, except its own transmitter.
In this book we focus on the basic signal processing that underlies current and
future ultra wideband systems. By looking at signal processing in this way we
hope this text will be useful EVEN as UWB applications mature and change or
regulations regarding ultra wideband systems are modified. The current UWB
field is extremely dynamic, with new techniques and ideas being presented at every
communications and signal-processing conference. The basic signal-processing
techniques presented in this text though will not change for some time to come.
Thus, we have taken a somewhat theoretical approach, which we believe is longer
lasting and more useful to the reader in the long term than an up-to-the-minute
summary that is out of date as soon as it is published.
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.
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.
