Sum-rank-metric codes have wide applications in universal error correction and security in multishot network, space-time coding and construction of partial-MDS codes for repair in distributed storage. Fundamental properties of sum-rank-metric codes have been studied and some explicit or probabilistic constructions of good sum-rank-metric codes have been proposed. In this paper we propose three simple constructions of explicit linear sum-rank-metric codes. In finite length regime, numerous good linear sum-rank-metric codes from our construction are given. Most of them have better parameters than previous constructed sum-rank-metric codes. For example a lot of small block size better linear sum-rank-metric codes over ${\bf F}_q$ of the matrix size $2 \times 2$ are constructed for $q=2, 3, 4$. Asymptotically our constructed sum-rank-metric codes are closing to the Gilbert-Varshamov-like bound on sum-rank-metric codes for some parameters. Finally we construct a linear MSRD code over an arbitrary finite field ${\bf F}_q$ with various matrix sizes $n_1>n_2>\cdots>n_t$ satisfying $n_i \geq n_{i+1}^2+\cdots+n_t^2$ , $i=1, 2, \ldots, t-1$, for any given minimum sum-rank distance. There is no restriction on the block lengths $t$ and parameters $N=n_1+\cdots+n_t$ of these linear MSRD codes from the sizes of the fields ${\bf F}_q$. We will show that the decoding of linear sum-rank-metric codes constructed in this paper can be reduced to the decoding in the Hamming metric.
翻译:和秩度量码在多次网络的通用纠错和安全、时空编码以及分布式存储中构建部分MDS码的修复等方面有着广泛的应用。和秩度量码的基本属性已经被研究,一些显式或概率构造的好的和秩度量码也被提出。在本文中,我们提出了三种简单的显式线性和秩度量码构造方法。在有限长度的范围内,给出了大量良好的线性和秩度量码。它们大多具有比以前构造的和秩度量码更好的参数。例如,对于矩阵大小为 $2 \times 2$ 和 $q=2, 3, 4$ 的情况,我们构造了许多小块大小更好的线性和秩度量码。渐进地,我们构造的和秩度量码在某些参数下接近于Gilbert-Varshamov类和秩度量码的界限。最后,我们构造了一个线性MSRD码(矩阵秩距码)(MSRD码不同于和秩度量码,但它们都是矩阵码)在任意有限域 ${\bf F}_q$ 上,其包含多个矩阵大小 $n_1>n_2>\cdots>n_t$,且满足 $i=1,2,\cdots,t-1$ 时 $n_i \geq n_{i+1}^2+\cdots+n_t^2$,对于给定的最小和秩度量距离,而对于这些线性MSRD码的块长度 $t$ 和参数 $N=n_1+\cdots+n_t$,则没有来自域大小 ${\bf F}_q$ 的限制。我们将证明,本文中构造的线性和秩度量码的译码可以降低为汉明度量中的译码。