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Channel Coding in Communication Networks: From Theory to Turbo Codes

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The very title of this book is borrowed from the information theory vocabulary, and, quite naturally, it is an outline of this theory that will serve as an introduction. The subject of information theory is the scientific study of communications. To this end it defines a quantitative measurement of the communicated content, i.e. information, and deals with two operations essential for communication techniques: source coding and channel encoding. Its main results are two fundamental theorems related to each of these operations. The possibility of channel encoding itself has been essentially revealed by information theory. That shows, to which point a brief summary of this theory is essential for its introduction. Apart from some capital knowledge of its possibilities and limits, the theory has, however, hardly contributed to the invention of means of implementation: whereas it is the necessary basis for the understanding of channel encoding, it by no means suffices for its description. The reader interested in information theory, but requiring more information than is provided in this brief introduction, may refer to [1], which also contains broader bibliographical references.

Using information theory and fundamental theorems on source and channel coding, this book describes the basics of channel coding and advanced coding techniques known as turbo codes. A discussion of lock codes and convolutional codes, including input- and output-decoding algorithms and recursive-systematic convolutional codes, leads into coverage of trellis-coded modulations, which have primary applications in high-spectral efficiency transmissions. The book further distinguishes convolutional-turbo codes from block-turbo codes and presents coding and decoding principles for each family, concluding with the implementation of turbo codes in circuits.
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