Abstract: The invention relates to a method of decoding a matrix built from concatenated codes, corresponding to at least two elementary codes, with uniform interleaving, the matrix having n1 lines, n2 columns and n1*n2 symbols, the method comprising processing all the lines- and columns-vectors of the matrix by symbol groups, the processing comprising a first decoding to simultaneously process all the symbols of a group of symbols according to their lines and then a second decoding to simultaneously process all the symbols of said group of symbols according to their columns, the symbol groups being thus successively processed in lines and in columns, or conversely.

Abstract: The invention relates to a Method of decoding a matrix built from concatenated codes, corresponding to at least two elementary codes, with uniform interleaving, this matrix having n1 lines, n2 columns and n1*n2 symbols, characterized in that the method comprises a process of all the lines- and columns-vectors of the matrix by symbols groups, this process comprises a first decoding for simultaneously processing all the symbols of a group of symbols according to their lines and then a second decoding for simultaneously processing all the symbols of the said group of symbols according to their columns, or inversely, the symbols groups being thus successively processed in lines and in columns.

Abstract: The invention concerns a module for decoding a concatenated code, corresponding at least to two elementary codes C1 and C2, using storage means (81, 83, 90, 111, 113) wherein are stored samples of data to be decoded, comprising at least two elementary decoders (821, 822, . . . 82m) of at least one of the elementary codes, the elementary decoders associated with one of the elementary codes simultaneously processing, in parallel separate code words contained in the storage means.

Abstract: The invention concerns a module for decoding a concatenated code, corresponding at least to two elementary codes C1 and C2, using storage means (81, 83, 90, 111, 113) wherein are stored samples of data to be decoded, comprising at least two elementary decoders (821, 822, . . . 82m) of at least one of the elementary codes, the elementary decoders associated with one of the elementary codes simultaneously processing, in parallel separate code words contained in the storage means.

Abstract: The bits transmitted are coded according to the product of at least two systematic block codes. Iterative decoding is applied in order to determine, at each code word search step, a data matrix ({R}) and a decision matrix ({D}) used for the following step. The new decision matrix is determined at each step by decoding the lines or columns of the input matrix, and the new data matrix is determined taking into account the correction terms which increase the reliability of the decoding on each iteration. The coding and decoding circuits (17) are rendered programmable by a shortening technique allowing selection of the number k-X of non-redundant information bits per block to be coded. Known values are assigned to the other bits, the positions of which are uniformly distributed according to each dimension of the matrices.

Abstract: The bits transmitted are coded according to the product of at least two systematic block codes. Iterative decoding is applied in order to determine, at each code word search step, a data matrix ({R}) and a decision matrix ({D}) used for the following step. The new decision matrix is determined at each step by decoding the rows or columns of the input matrix, and the new data matrix is determined taking into account the correction terms which increase the reliability of the decoding on each iteration. The coding and decoding circuits (17) are rendered programmable by a puncturing technique allowing selection of the number of bits transmitted per coded block, the punctured bits preferably having uniformly distributed positions according to each dimension of the matrices.

Abstract: A method for the decoding of digital data obtained according to a convolutional coding and transmitted on a noise-ridden channel aimed at improving the methods of maximum likelihood decoding such as the Viterbi algorithm consisting in associating, with each estimation s(t) of the corresponding source digital element a(t), a weighting coefficient m(t) representing the reliability of the estimation s(t), the estimation s(t) taking account of the values of a first series of L received samples, and the weighting m(t) taking account of the values of a second series of N samples received, N being strictly greater than L. In a preferred embodiment, a second trellis is associated with the standard first decoding trellis, a trace-back being done in the second trellis on two concurrent paths, used to revise the weighting coefficients obtained at output of the first trellis.