K. Sam Shanmugan – författare

Since the first edition of this book was published seven years ago, 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. With the current interest in digital mobile communications, a primary area of application of modeling and simulation is now in wireless systems of a different flavor from the `traditional' ones. This second edition represents a substantial revision of the first, partly to accommodate the new applications that have arisen. New chapters include material on modeling and simulation of nonlinear systems, with a complementary section on related measurement techniques, channel modeling and three new case studies; a consolidated set of problems is provided at the end of the book.

Since the first edition of this book was published seven years ago, 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. With the current interest in digital mobile communications, a primary area of application of modeling and simulation is now in wireless systems of a different flavor from the `traditional'' ones. This second edition represents a substantial revision of the first, partly to accommodate the new applications that have arisen. New chapters include material on modeling and simulation of nonlinear systems, with a complementary section on related measurement techniques, channel modeling and three new case studies; a consolidated set of problems is provided at the end of the book.

Random Signals, Noise and Filtering develops the theory of random processes and its application to the study of systems and analysis of random data. The text covers three important areas: (1) fundamentals and examples of random process models, (2) applications of probabilistic models: signal detection, and filtering, and (3) statistical estimation--measurement and analysis of random data to determine the structure and parameter values of probabilistic models. This volume by Breipohl and Shanmugan offers the only one-volume treatment of the fundamentals of random process models, their applications, and data analysis.

Simulation may be defined as the discipline whose objective is to imitate one or more aspects of reality in a way that is as close to that reality as possible; indeed, an apt synonym that is gaining some currency is artificial reality. Under this definition, simulation is a very old discipline. Probably the first applications of simulation were to scale models of various types of dynamical structures or mechanical devices. Man has always looked for ways to "try things out" before building the real thing; this is the motivation behind any form of simulation. Thus, simulation of communication systems is concerned with imitating some aspects of the behavior of communication systems. It is implicit in our use of simulation that the medium (so to speak) for carrying it out is the digital computer. Computer-based modeling and simulation of communication systems has only developed in the last 20 years or so, since the advent of modern digital computers. A variety of modeling and simulation techniques have been developed and described in widely scattered journals, but until now there has not been a single volume devoted to the subject. We have tried to provide a unified framework that describes both the disciplines involved and the methods of modeling and simulating communication systems and subsystems. In the electronic era, the first type of computer simulation, in today''s use of the term, took shape in the form of analog computers.