On the Gap between Scalar and Vector Solutions of Generalized Combination Networks
We study scalar-linear and vector-linear solutions of the generalized combination network. We derive new upper and lower bounds on the maximum number of nodes in the middle layer, depending on the network parameters and the alphabet size. These bounds improve and extend the parameter range of known bounds. Using these new bounds we present a lower bound and an upper bound on the gap in the alphabet size between optimal scalar-linear and optimal vector-linear network coding solutions. For a fixed network structure, while varying the number of middle-layer nodes $r$, the asymptotic behavior of the upper and lower bounds shows that the gap is in $\Theta(\log(r))$.
PDF AbstractCategories
Information Theory
Networking and Internet Architecture
Social and Information Networks
Combinatorics
Information Theory
Datasets
Add Datasets
introduced or used in this paper
