Neural Normalized Min-Sum Message-Passing vs. Viterbi Decoding for the CCSDS Line Product Code
Abstract
The Consultative Committee for Space Data Systems (CCSDS) 141.11-O-1 Line Product Code (LPC) provides a rare opportunity to compare maximum-likelihood decoding and message passing. The LPC considered in this paper is intended to serve as the inner code in conjunction with a (255,239) Reed Solomon (RS) code whose symbols are bytes of data. This paper represents the 141.11-O-1 LPC as a bipartite graph and uses that graph to formulate both maximum likelihood (ML) and message passing algorithms. ML decoding must, of course, have the best frame error rate (FER) performance. However, a fixed point implementation of a Neural-Normalized MinSum (N-NMS) message passing decoder closely approaches ML performance with a significantly lower complexity.
Cite
@article{arxiv.2111.07959,
title = {Neural Normalized Min-Sum Message-Passing vs. Viterbi Decoding for the CCSDS Line Product Code},
author = {Jonathan Nguyen and Linfang Wang and Chester Hulse and Sahil Dani and Amaael Antonini and Todd Chauvin and Divsalar Dariush and Richard Wesel},
journal= {arXiv preprint arXiv:2111.07959},
year = {2021}
}
Comments
This paper has been submitted to ICC 2022