# IRA codes derived from Gruenbaum graph

## TL;DR

This paper introduces a novel interleaver for IRA codes based on the Gruenbaum graph, achieving significant performance gains in short data frame coding.

## Contribution

A new interleaver derived from the Gruenbaum graph for IRA codes, improving decoding performance for short data frames.

## Key findings

- Achieved 0.7-0.8 dB gain over convolutional codes decoded by Viterbi.
- Proposed interleaver based on Hamiltonian path in Gruenbaum graph.
- Enhanced coding performance for 192-bit data frames.

## Abstract

In this paper, we consider coding of short data frames (192 bits) by IRA codes. A new interleaver for the IRA codes based on a Gruenbaum graph is proposed. The difference of the proposed algorithm from known methods consists in the following: permutation is performed by using a match smaller interleaver which is derived from the Gruenbaum graph by finding in this graph a Hamiltonian path, enumerating the passed vertices in ascending order and passing them again in the permuted order through the edges which are not included in the Hamiltonian path. For the IRA code the obtained interleaver provides 0.7-0.8 db gain over a convolutional code decoded by Viterbi algorithm.

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Source: https://tomesphere.com/paper/1701.02009