Title :
Insufficiency of linear coding in network information flow
Author :
Dougherty, Randall ; Freiling, Christopher ; Zeger, Kenneth
Author_Institution :
Center for Commun. Res., San Diego, CA, USA
Abstract :
It is known that every solvable multicast network has a scalar linear solution over a sufficiently large finite-field alphabet. It is also known that this result does not generalize to arbitrary networks. There are several examples in the literature of solvable networks with no scalar linear solution over any finite field. However, each example has a linear solution for some vector dimension greater than one. It has been conjectured that every solvable network has a linear solution over some finite-field alphabet and some vector dimension. We provide a counterexample to this conjecture. We also show that if a network has no linear solution over any finite field, then it has no linear solution over any finite commutative ring with identity. Our counterexample network has no linear solution even in the more general algebraic context of modules, which includes as special cases all finite rings and Abelian groups. Furthermore, we show that the network coding capacity of this network is strictly greater than the maximum linear coding capacity over any finite field (exactly 10% greater), so the network is not even asymptotically linearly solvable. It follows that, even for more general versions of linearity such as convolutional coding, filter-bank coding, or linear time sharing, the network has no linear solution.
Keywords :
channel capacity; channel coding; linear codes; multicast communication; telecommunication network routing; large finite-field alphabet; linear coding; multicast network; network coding capacity; network information flow; network routing; Convolutional codes; Galois fields; Information theory; Intelligent networks; Linearity; Modules (abstract algebra); Network coding; Nonlinear filters; Routing; Vectors; Asymptotics; flows; linear coding; network information theory; routing;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2005.851744