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arXiv 0812.2379cs.ITmath.IT
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秩度量码和常维码的译码错误概率

On the Decoder Error Probability of Rank Metric Codes and Constant-Dimension Codes

Maximilien Gadouleau, Zhiyuan Yan

摘要:

在随机网络编码中,秩度量码和常维码被用来进行差错控制。由于解码器错误比解码器故障对系统性能更有害,本文研究了秩度量码和CDC的有界距离解码器(BDD)的解码器错误概率(DEP)。对于秩度量码,我们考虑了网络编码激励的信道,其中具有相同行空间的错误是等概率的。在这样的渠道,我们建立上界的DEP的BDD,确定确切的DEP的BDD的最大秩距离(MRD)的代码,并显示MRD代码具有最大的DEP的标量。为了评估CDC的BDD的DEP,我们首先建立了一些基本的几何性质的射影空间。使用这些几何特性,然后,我们认为BDD在子空间和注入度量和推导出的解析表达式的DEP的CDC,在一个对称的运营商通道,作为其距离分布的函数。最后,我们专注于提升秩度量码得到的CDC,并建立了两个重要的结果:第一,我们得到了渐近紧上界的DEP在这两个度量;第二,我们证明了KK码的DEP是最大的提升秩度量码得到的CDC中的标量。

英文摘要:

Rank metric codes and constant-dimension codes (CDCs) have been considered for error control in random network coding. Since decoder errors are more detrimental to system performance than decoder failures, in this paper we investigate the decoder error probability (DEP) of bounded distance decoders (BDDs) for rank metric codes and CDCs. For rank metric codes, we consider a channel motivated by network coding, where errors with the same row space are equiprobable. Over such channels, we establish upper bounds on the DEPs of BDDs, determine the exact DEP of BDDs for maximum rank distance (MRD) codes, and show that MRD codes have the greatest DEPs up to a scalar. To evaluate the DEPs of BDDs for CDCs, we first establish some fundamental geometric properties of the projective space. Using these geometric properties, we then consider BDDs in both subspace and injection metrics and derive analytical expressions of their DEPs for CDCs, over a symmetric operator channel, as functions of their distance distributions. Finally, we focus on CDCs obtained by lifting rank metric codes and establish two important results: First, we derive asymptotically tight upper bounds on the DEPs of BDDs in both metrics; Second, we show that the DEPs for KK codes are the greatest up to a scalar among all CDCs obtained by lifting rank metric codes.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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