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Column Rank Distances of Rank Metric Convolutional Codes

机译:级别度量卷积码的柱子级距离

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In this paper, we deal with the so-called multi-shot network coding, meaning that the network is used several times (shots) to propagate the information. The framework we present is slightly more general than the one which can be found in the literature. We study and introduce the notion of column rank distance of rank metric convolutional codes for any given rate and finite field. Within this new framework we generalize previous results on column distances of Hamming and rank metric convolutional codes [3,8]. This contribution can be considered as a continuation follow-up of the work presented in [10].
机译:在本文中,我们处理所谓的多射网网络编码,这意味着网络使用了几次(镜头)来传播信息。我们呈现的框架比在文献中可以找到的框架略高。我们研究并介绍任何给定速率和有限场的秩度卷积码的列级距离的概念。在这个新的框架内,我们概括了汉明的柱距离的先前结果[3,8]。这种贡献可以被视为[10]中所提供的工作的延续后续行动。

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