Year: 2004
Type: conference-paper
Abstract: The min-cut, max-flow theorem states that a source node can send a commodity through a network to a sink node at the rate determined by the flow of the min-cut separating the source and the sink. Recently it has been shown that by linear re-encoding at nodes in communication networks, the min-cut rate can be also achieved in multicasting to several sinks. In this paper we discuss connections between such coding schemes and convolutional codes. We propose a method to simplify the convolutional encoder design that is based on a subtree decomposition of the network line graph, describe the structure of the associated matrices, investigate methods to reduce decoding complexity and discuss possible binary implementation.
Authors: C. Fragouli, E. Soljanin
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2155113000