Constructing strongly-MDS convolutional codes with maximum distance profile
Constructing strongly-MDS convolutional codes with maximum distance profile
复制标题
构建具有最大距离分布的强MDS卷积码
DOI：
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发表时间：
2016
影响因子：
0.9
通讯作者：
R. Smarandache
中科院分区：
文献类型：
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作者：
D. N. Avelli;R. Smarandache
本文重新研究了具有最大距离轮廓（MDP）的强MDS卷积码。这些是（非二进制）卷积码，具有列距离的最佳序列，并在尽可能早的时间帧内达到广义Singleton界。这些特性使得这些卷积码可应用于擦除信道，因为它们能够在每个时间间隔内纠正大量的擦除。这些代码的存在仅在某些特定情况下显示。本文通过构造证明了对于所有参数的选择都是强MDS和MDP的卷积码的存在性。
This paper revisits strongly-MDS convolutional codes with maximum distance profile (MDP). These are (non-binary) convolutional codes that have an optimum sequence of column distances and attains the generalized Singleton bound at the earliest possible time frame. These properties make these convolutional codes applicable over the erasure channel, since they are able to correct a large number of erasures per time interval. The existence of these codes have been shown only for some specific cases. This paper shows by construction the existence of convolutional codes that are both strongly-MDS and MDP for all choices of parameters.