A Novel Method for Combining Algebraic Decoding and Iterative Processing
A Novel Method for Combining Algebraic Decoding and Iterative Processing
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DOI：
10.1109/isit.2006.261714
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发表时间：
2006-07
期刊：
影响因子：
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通讯作者：
Xiangyu Tang;R. Koetter
中科院分区：
文献类型：
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作者：
Xiangyu Tang;R. Koetter
我们提出了一种新的纠错编码方案，称为广义集成交织和稀疏集成交织。在块交织码字的上下文中，广义集成交织允许在所有交织之间共享非均匀冗余。这允许即时调整冗余以更好地适应通道或存储设备的错误统计。稀疏集成交织将分布式存储系统中的数据节点分组为子组。一个数据节点可以属于几个子组。在每个子组内局部纠正小错误。局部代数迭代译码算法用于跨子组译码，以纠正在子组内无法纠正的大错误。为了实现快速纠错和更低的通信开销，几乎不牺牲纠错能力。该方案改进了对所有数据节点的数据访问，并允许分布式存储网络的轻松扩展
We propose novel error correction coding schemes called generalized integrated interleaving and sparsely integrated interleaving codes. In the context of block interleaved codewords, generalized integrated interleaving allows nonuniform redundancy to be shared among all the interleaves. This allows the redundancy to be adjusted on-the-fly to better suit the error statistics of the channel or storage device. Sparsely integrated interleaving groups data nodes in a distributed storage system into subgroups. A data node can belong to several subgroups. Small errors are corrected locally within each subgroup. A localized algebraic iterative decoding algorithm is used to decode across subgroups to correct large errors that cannot be corrected within subgroups. Very little correction capability is sacrificed to achieve fast error correction and lower communication overhead. This scheme improves data access for all the data nodes and allows easy scaling of the distributed storage network