Claude Berrou

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This paper deals with a new class of convolutional codes called Turbo-codes, whose performances in terms of Bit Error Rate (BER) are close to the SHANNON limit. The Turbo-Code encoder is built using a parallel concatenation of two Recursive Systematic Convolutional codes and the associated decoder, using a feedback decoding rule, is implemented as P(More)
AbsfructThis 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(More)
The original turbo codes (TCs), presented in 1993 by Berrou et al., consist of the parallel concatenation of two rate-1/2 binary recursive systematic convolutional (RSC) codes. This paper explains how replacing rate-1/2 binary component codes by rate( + 1) binary RSC codes can lead to better global performance. The encoding scheme can be designed so that(More)
The design of the turbo code internal permutation is crucial regarding the minimum Hamming distance (MHD) and the related achievable asymptotic gain. After having set down the permutation issues in a synthetic way, this paper presents a generic model which allows us to obtain large MHDs for turbo codes and also offers large possibilities of natural(More)
Coded recurrent neural networks with three levels of sparsity are introduced. The first level is related to the size of messages that are much smaller than the number of available neurons. The second one is provided by a particular coding rule, acting as a local constraint in the neural activity. The third one is a characteristic of the low final connection(More)
A new method for computing the minimum distances of linear error correcting codes is proposed and justi ed Unlike classical techniques that rely on exhaustive or partial enu meration of codewords this new method is based on the ability of the Soft In decoder to overcome Error Impulse input patterns It is shown that the maximum magnitude of the Error Impulse(More)
This paper presents a means to adapt the classical architecture of a Viterbi decoder to make it able to provide soft (weighted) decisions. After a theoretical justification of the proposed method, based on Battail or Hagenauer-Hoeher algorithms, we detail the new architecture which leads to a real-time circuit, the size of which is roughly twice the size of(More)
Convolutional turbo codes are very flexible codes, easily adaptable to a large range of data block sizes and coding rates. This is the main reason for their being adopted in the DVB standard for Return Channel via Satellite (DVB-RCS). The paper presents the turbo coding/decoding scheme specified in this standard, for twelve block sizes and seven coding(More)