Erasure decoding of convolutional codes using first order representations

TL;DR

This paper introduces a new erasure decoding algorithm for convolutional codes based on first order linear system representations, reducing delay and computational effort compared to existing methods.

Contribution

It develops a novel decoding algorithm utilizing state space descriptions, improving efficiency and decoding delay over prior algorithms.

Findings

The new algorithm reduces decoding delay.

It decreases computational effort in erasure recovery.

Properties for good decoding performance are identified.

Abstract

In this paper, we employ the linear systems representation of a convolutional code to develop a decoding algorithm for convolutional codes over the erasure channel. We study the decoding problem using the state space description and this provides in a natural way additional information. With respect to previously known decoding algorithms, our new algorithm has the advantage that it is able to reduce the decoding delay as well as the computational effort in the erasure recovery process. We describe which properties a convolutional code should have in order to obtain a good decoding performance and illustrate it with an example.