LDPC code coding method based on optimum searching matrix LU decomposition

Abstract

The encoding method for LDPC code based on LU decomposition for optimized search matrix is realized by software pretreatment and hardware encoding. Wherein, eliminating correlative rows of check matrix, realigning the matrix; selecting nonsingular matrix with non-correlative column composite algorism for decomposition with simple LU algorism; optimizing search by diagonal element asymptotic one of nonsingular matrix; finally, selecting nonsingular matrix with lowest density, and reducing delay of whole coding system by time interval control parallel process hardware structure. This invention holds advantages in prior art, reduces calculation amount near Greedy algorism, and fit to any LDPC code special to abnormal code and normal node with correlative rows.

Description

technical field [0001] The present invention relates to a method in the technical field of channel coding, in particular to an LDPC code coding method based on LU decomposition of an optimized search matrix. Background technique [0002] Compared with Turbo codes, Low Density Check (LDPC) codes can achieve better error correction performance, and also have the advantages of simple decoder implementation and parallel operation, but LDPC code encoders are much more complicated than Turbo codes. The amount of code encoding operations increases linearly with the code length, while the LDPC code increases with the square of the code length. Since the excellent performance of LDPC codes is obtained by longer codes (generally greater than 1000), the amount of encoding operations and hardware The complexity of implementation is a major obstacle in its practical application. The traditional LDPC code encoding method is to obtain the generation matrix by Gaussian elimination of the p...

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[0003] After searching the literature of the prior art, it was found that in 2001, Richardson et al published "Efficientencoding of low-density" in "IEEE Trans.Inf.Theory" vol.47, no.2, pp.638-656, Feb.2001 parity-check codes" (IEEE Transactions on Information Theory, February 2001, Volume 47, Pages 638 to 656, Effective Coding of Low-Density Parity-check Codes), a coding scheme is proposed in this paper. Most of the matrices are obtained by using the greedy algorithm to replace the rows and columns of the parity check matrix, which maintains the sparsity of the matrix, greatly reduces the computational complexity of the encoding, and makes it approximately linear with the code length. This encoding scheme divides the check matrix into six blocks, and there is a non-singular dense matrix whose rows and columns are g (approximately the difference between the lower triangle and the lower triangle). The hardware implementation structure is more complicated, and the timing control is more difficult.

In the search, it was also found that in 2003, Su-Chang Chae et al. published in "IEEE 58 th "Low Complexity Encoding of Regular Low Density Parity Check Codes" published on Vehicular Technology Conference"vol.3, pp.1822-1826, 6-9Oct.2003 (IEEE 58th Vehicular Technology Conference, October 6-9, 2003, Volume 3, pages 1822 to 1826, Low-complexity encoding of regular low-density parity-check codes), the encoding scheme mentioned in this article uses the LU decomposition property of the matrix, and the structure of the encoder is greatly simplified compared with the RU scheme , but the LU decomposition requires the matrix to have non-singularity. In order to meet the requirements of non-singularity and facilitate LU decomposition, this paper proposes the pivot and bit reversal (PABR) algorithm. Although this algorithm overcomes the traditional LU decomposition algorithm, it may not be smooth However, in most cases, when searching for non-singular matrices and LU decomposition, it is necessary to change the code sub-bit redistribution structure, which will inevitably affect the use of the code sub with the best performance, and does not consider the denseness of the generated triangular matrix

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