Channel Coding in Communication Networks: From Theory to by Alain Glavieux

By Alain Glavieux

Utilizing info thought and primary theorems on resource and channel coding, this ebook describes the fundamentals of channel coding and complex coding concepts often called rapid codes. A dialogue of lock codes and convolutional codes, together with enter- and output-decoding algorithms and recursive-systematic convolutional codes, leads into assurance of trellis-coded modulations, that have basic functions in high-spectral potency transmissions. The booklet additional distinguishes convolutional-turbo codes from block-turbo codes and offers coding and interpreting ideas for every relations, concluding with the implementation of rapid codes in circuits.

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17] In its most usual formulation, the reconstruction quality standard used is an upper limit of the word error probability. 17] is not verified, it is impossible to obtain an arbitrarily small probability of error under the same conditions (in fact, the word error probability tends towards 1 when the length of the codewords increases indefinitely). 2. General comments The fundamental theorem of channel coding is undoubtedly the most original and the most important result of information theory: original in that it implies the paradoxical possibility of a transmission without error via a disturbed channel, so contrary to apparent common sense that engineers had not even imagined it before Shannon; important in theory, but also in practice, because a transmission without error is a highly desirable result.

This value is different from the entropy of the message at the output of the channel and is smaller than it, since, far from bringing additional information, the channel can only degrade the message transmitted by the source, which suffers there from random noise. In the simplest case, the channel is without memory like the source, in the sense that each output symbol depends only on an input symbol, itself independent of others, if the source is without memory. It can thus be fully described by the probabilities of output symbols conditioned to input symbols, referred to as transition probabilities, which are constant for a stationary channel.

Provides information on the probability of the transmitted symbol. In this case we speak of a soft decision, although this is rather a case of an absence of an explicit decision.

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