Journal ArticleDOI
Near optimum error correcting coding and decoding: turbo-codes
Claude Berrou,A. Glavieux +1 more
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A new family of convolutional codes, nicknamed turbo-codes, built from a particular concatenation of two recursive systematic codes, linked together by nonuniform interleaving appears to be close to the theoretical limit predicted by Shannon.Abstract:
This paper presents a new family of convolutional codes, nicknamed turbo-codes, built from a particular concatenation of two recursive systematic codes, linked together by nonuniform interleaving. Decoding calls on iterative processing in which each component decoder takes advantage of the work of the other at the previous step, with the aid of the original concept of extrinsic information. For sufficiently large interleaving sizes, the correcting performance of turbo-codes, investigated by simulation, appears to be close to the theoretical limit predicted by Shannon.read more
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Information Theory, Inference and Learning Algorithms
TL;DR: A fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering.
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Clustering by Passing Messages Between Data Points
Brendan J. Frey,Delbert Dueck +1 more
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Good error-correcting codes based on very sparse matrices
TL;DR: It is proved that sequences of codes exist which, when optimally decoded, achieve information rates up to the Shannon limit, and experimental results for binary-symmetric channels and Gaussian channels demonstrate that practical performance substantially better than that of standard convolutional and concatenated codes can be achieved.
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Iterative (turbo) soft interference cancellation and decoding for coded CDMA
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TL;DR: Simulation results demonstrate that the proposed low complexity iterative receivers structure for interference suppression and decoding offers significant performance gain over the traditional noniterative receiver structure.
References
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The viterbi algorithm
TL;DR: This paper gives a tutorial exposition of the Viterbi algorithm and of how it is implemented and analyzed, and increasing use of the algorithm in a widening variety of areas is foreseen.
Proceedings ArticleDOI
Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1
TL;DR: In this article, a new class of convolutional codes called turbo-codes, whose performances in terms of bit error rate (BER) are close to the Shannon limit, is discussed.
Journal ArticleDOI
Optimal decoding of linear codes for minimizing symbol error rate (Corresp.)
TL;DR: The general problem of estimating the a posteriori probabilities of the states and transitions of a Markov source observed through a discrete memoryless channel is considered and an optimal decoding algorithm is derived.