索引分配能够检测多个描述标量量化器的一比特错误

Yinghan Wan, S. Dumitrescu
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引用次数: 3

摘要

这项工作是关于通过对每个描述的索引应用置换来增加两个描述标量量化器的错误弹性,用于m对角线初始索引分配。首先,我们讨论了实现最小汉明距离至少为2的排列的存在性。这样的排列允许中央解码器检测任何1位错误模式。我们建立了与超立方体反带宽问题的联系,这种联系使我们能够确定存在这种排列的m的最大值并显示其构造。此外,我们强调了侧解码器的错误鲁棒性与与排列相关的超立方体标记带宽之间的关系。为了确保中央和侧解码器的容错性,我们对给定反带宽大于或等于m的最低带宽的标记感兴趣。我们通过构造一类超立方体标记,以反带宽的增加换取带宽的减少,在解决这个问题方面取得了一些进展。
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Index assignment capable of detecting one bit errors for multiple description scalar quantizers
This work is concerned with increasing the error resilience of two description scalar quantizers by applying a permutation to the index of each description, for an m-diagonal initial index assignment. First we address the existence of permutations achieving a minimum Hamming distance of at least 2. Such permutations allow the central decoder to detect any 1 bit error pattern. We establish the connection with the hypercube antibandwidth problem, connection which allows us to determine the highest value of m for which such a permutation exists and to show its construction. Further, we highlight the relation between the error robustness at the side decoders and the bandwidth of the hypercube labeling associated to the permutation. To ensure error resilience at both the central and side decoders we are interested in labelings with the lowest bandwidth given that the antibandwidth is larger or equal to m. We make some progress toward the solution of this problem by constructing a class of hypercube labelings trading the increase in antibandwidth for the decrease in bandwidth.
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