Sparse Network Coding with Overlapping Classes

TL;DR

This paper introduces overlapping classes in network coding to improve decoding efficiency and performance, combining fountain and network coding techniques, with simulation results supporting its effectiveness.

Contribution

It proposes a novel overlapping class approach in network coding, enhancing decoding performance and complexity management compared to traditional disjoint class methods.

Findings

Overlapping classes improve decoding performance.

The approach reduces decoding complexity.

Simulation results demonstrate effectiveness.

Abstract

This paper presents a novel approach to network coding for distribution of large files. Instead of the usual approach of splitting packets into disjoint classes (also known as generations) we propose the use of overlapping classes. The overlapping allows the decoder to alternate between Gaussian elimination and back substitution, simultaneously boosting the performance and reducing the decoding complexity. Our approach can be seen as a combination of fountain coding and network coding. Simulation results are presented that demonstrate the promise of our approach.