Initialization Algorithms For Convolutional Network Coding

TL;DR

This paper introduces algorithms for initializing convolutional network coding in cyclic networks, enabling decoding and rate determination despite interference and infinite impulse responses.

Contribution

It proposes new initialization algorithms specifically designed for cyclic networks, addressing challenges of interference and infinite impulse responses.

Findings

Algorithms successfully initialize cyclic network coding schemes.

Impulse response measurement enables decoding and rate calculation.

Initialization process accounts for interference in cyclic networks.

Abstract

We present algorithms for initializing a convolutional network coding scheme in networks that may contain cycles. An initialization process is needed if the network is unknown or if local encoding kernels are chosen randomly. During the initialization process every source node transmits basis vectors and every sink node measures the impulse response of the network. The impulse response is then used to find a relationship between the transmitted and the received symbols, which is needed for a decoding algorithm and to find the set of all achievable rates. Unlike acyclic networks, for which it is enough to transmit basis vectors one after another, the initialization of cyclic networks is more involved, as pilot symbols interfere with each other and the impulse response is of infinite duration.