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arXiv 0812.4642cs.ITmath.IT
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基于循环矩阵的LDPC卷积码的差错-网格状态复杂度

Error-Trellis State Complexity of LDPC Convolutional Codes Based on Circulant Matrices

M. Tajima, K. Okino, T. Miyagoshi

摘要:

设H(D)是LDPC卷积码的奇偶校验矩阵,对应于使用Tanner等人的方法获得的QC码的奇偶校验矩阵H。我们看到H(D)中的条目都是单项式,并且几行(列)具有单项式因子。让我们循环移动H的行。然后,对应于修改矩阵H ′的奇偶校验矩阵H ′(D)定义另一个卷积码。然而,其自由距离的下限是原始QC码的最小距离。此外,H ′(D)的每一行(列)具有与H(D)中的因子不同的因子。我们证明了在保持纠错能力的情况下,通过控制施加到H的行移位,可以显著降低与H '(D)相关联的错误网格的状态空间复杂度。

英文摘要:

Let H(D) be the parity-check matrix of an LDPC convolutional code corresponding to the parity-check matrix H of a QC code obtained using the method of Tanner et al. We see that the entries in H(D) are all monomials and several rows (columns) have monomial factors. Let us cyclically shift the rows of H. Then the parity-check matrix H'(D) corresponding to the modified matrix H' defines another convolutional code. However, its free distance is lower-bounded by the minimum distance of the original QC code. Also, each row (column) of H'(D) has a factor different from the one in H(D). We show that the state-space complexity of the error-trellis associated with H'(D) can be significantly reduced by controlling the row shifts applied to H with the error-correction capability being preserved.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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