English

Linear Network Coding, Linear Index Coding and Representable Discrete Polymatroids

Information Theory 2016-03-22 v3 math.IT

Abstract

Discrete polymatroids are the multi-set analogue of matroids. In this paper, we explore the connections among linear network coding, linear index coding and representable discrete polymatroids. We consider vector linear solutions of networks over a field Fq,\mathbb{F}_q, with possibly different message and edge vector dimensions, which are referred to as linear fractional solutions. We define a \textit{discrete polymatroidal} network and show that a linear fractional solution over a field Fq,\mathbb{F}_q, exists for a network if and only if the network is discrete polymatroidal with respect to a discrete polymatroid representable over Fq.\mathbb{F}_q. An algorithm to construct networks starting from certain class of discrete polymatroids is provided. Every representation over Fq\mathbb{F}_q for the discrete polymatroid, results in a linear fractional solution over Fq\mathbb{F}_q for the constructed network. Next, we consider the index coding problem and show that a linear solution to an index coding problem exists if and only if there exists a representable discrete polymatroid satisfying certain conditions which are determined by the index coding problem considered. El Rouayheb et. al. showed that the problem of finding a multi-linear representation for a matroid can be reduced to finding a \textit{perfect linear index coding solution} for an index coding problem obtained from that matroid. We generalize the result of El Rouayheb et. al. by showing that the problem of finding a representation for a discrete polymatroid can be reduced to finding a perfect linear index coding solution for an index coding problem obtained from that discrete polymatroid.

Keywords

Cite

@article{arxiv.1306.1157,
  title  = {Linear Network Coding, Linear Index Coding and Representable Discrete Polymatroids},
  author = {Vijayvaradharaj T. Muralidharan and B. Sundar Rajan},
  journal= {arXiv preprint arXiv:1306.1157},
  year   = {2016}
}

Comments

24 pages, 6 figures, 4 tables, some sections reorganized, Section VI newly added, accepted for publication in IEEE Transactions on Information Theory

R2 v1 2026-06-22T00:28:37.064Z