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Weight Enumerating Function, Number of Full Rank Sub-matrices and Network Coding

机译:权重枚举函数,满秩子矩阵的数量和网络编码

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In most of the network coding problems with k messages, the existence of binary network coding solution over ${mathbb{F}_2}$ depends on the existence of adequate sets of k-dimensional binary vectors such that each set comprises of linearly independent vectors. In a given k×n (n ≥ k) binary matrix, there exist $ inom{n}{k}$ binary sub-matrices of size k×k. Every possible k×k submatrix may be of full rank or singular depending on the columns present in the matrix. In this work, for full rank binary matrix G of size k×n satisfying certain condition on minimum Hamming weight, we establish a relation between the number of full rank sub-matrices of size k×k and the weight enumerating function of the error correcting code with G as the generator matrix. We give an algorithm to compute the number of full rank k×k submatrices.
机译:在大多数带有k条消息的网络编码问题中,$ {\ mathbb {F} _2} $之上的二进制网络编码解决方案的存在取决于存在的适当的k维二进制向量集合,从而每个集合都包含线性独立的向量。在给定的k×n(n≥k)个二进制矩阵中,存在大小为k×k的$ \ binom {n} {k} $个二进制子矩阵。取决于矩阵中存在的列,每个可能的k×k子矩阵都可以是满秩或奇异的。在这项工作中,对于在最小汉明权重上满足一定条件的,大小为k×n的满秩二进制矩阵G,我们建立了大小为k×k的满秩子矩阵的数目与纠错的权重枚举函数之间的关系。 G作为生成器矩阵的代码。我们给出一种算法来计算满秩k×k子矩阵的数量。

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