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This unique text, for both the first year graduate student and the
newcomer to the field, provides in-depth coverage of the basic
principles of data communications and covers material which is not
treated in other texts, including phase and timing recovery and
echo cancellation. Throughout the book, exercises and applications
illustrate the material while up-to-date references round out the
work.
This unique text, for both the first year graduate student and the
newcomer to the field, provides in-depth coverage of the basic
principles of data communications and covers material which is not
treated in other texts, including phase and timing recovery and
echo cancellation. Throughout the book, exercises and applications
illustrate the material while up-to-date references round out the
work.
In large measure the traditional concern of communications
engineers has been the conveyance of voice signals. The most
prominent example is the telephone network, in which the techniques
used for transmission multiplex ing and switching have been
designed for voice signals. However, one of the many effects of
computers has been the growing volume of the sort of traffic that
flows in networks composed of user terminals, processors, and
peripherals. The characteristics of this data traffic and the
associated perfor mance requirements are quite different from those
of voice traffic. These differences, coupled with burgeoning
digital technology, have engendered a whole new set of approaches
to multiplexing and switching this traffic. The new techniques are
the province of what has been loosely called computer
communications networks. The subject of this book is the
mathematical modeling and analysis of computer communications
networks, that is to say, the multiplexing and switching techniques
that have been developed for data traffic. The basis for many of
the models that we shall consider is queueing theory, although a
number of other disciplines are drawn on as well. The level at
which this material is covered is that of a first-year graduate
course. It is assumed that at the outset the student has had a good
undergraduate course in probability and random processes of the
sort that are more and more common among electrical engineering and
computer science departments."
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