D. Shivakrishna, V. Rameshwar, V. Lalitha, B. Sasidharan
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引用次数: 6
摘要
给定局部奇偶校验约束的拓扑结构,最大可恢复代码(MRC)可以纠正所有在信息理论上可纠正的擦除模式。在类似网格的拓扑结构中,每列中有$a$局部约束,形成列码;每行中有$b$局部约束,形成行码;在码字的(m × n)网格中有$h$全局约束。最近,Gopalan等人对类网格拓扑下的MRCs进行了研究,导出了当$a = 1, h = 0$时擦除模式可恢复的充分必要条件,称为正则性条件。在本文中,我们考虑产品拓扑($h = 0$)的MRCs。首先,基于满足积拓扑(任意$a, b, h = 0$)正则性条件的擦除模式构造了一个二部图,并证明了该二部图存在一个完全匹配。然后给出了a = 1, h = 0时充分条件的另一种直接证明。稍后,我们将扩展我们的技术来研究$a = 2, h = 0$的拓扑结构,并在这种情况下描述可恢复擦除模式的子集。对于两个$a = 1,2 $,我们的证明方法是一致的,即通过构造列码和行码的生成矩阵的张量积Gcol⊗grow,使得某些方子矩阵保持满秩。利用前面确定的匹配和擦除子模式中的另一组匹配证明了满秩条件。
On Maximally Recoverable Codes for Product Topologies
Given a topology of local parity-check constraints, a maximally recoverable code (MRC) can correct all erasure patterns that are information-theoretically correctable. In a grid-like topology, there are $a$ local constraints in every column forming a column code, $b$ local constraints in every row forming a row code, and $h$ global constraints in an (m × n) grid of codeword. Recently, Gopalan et al. initiated the study of MRCs under grid-like topology, and derived a necessary and sufficient condition, termed as the regularity condition, for an erasure pattern to be recoverable when $a = 1, h = 0$. In this paper, we consider MRCs for product topology ($h = 0$). First, we construct a certain bipartite graph based on the erasure pattern satisfying the regularity condition for product topology (any $a, b, h = 0$) and show that there exists a complete matching in this graph. We then present an alternate direct proof of the sufficient condition when $a = 1, h = 0$. We later extend our technique to study the topology for $a = 2, h = 0$, and characterize a subset of recoverable erasure patterns in that case. For both $a = 1, 2$, our method of proof is uniform, i.e., by constructing tensor product Gcol ⊗ Growof generator matrices of column and row codes such that certain square sub-matrices retain full rank. The full-rank condition is proved by resorting to the matching identified earlier and also another set of matchings in erasure sub-patterns.