Approaching Capacity at High-Rates with Iterative Hard-Decision Decoding
Abstract
A variety of low-density parity-check (LDPC) ensembles have now been observed to approach capacity with message-passing decoding. However, all of them use soft (i.e., non-binary) messages and a posteriori probability (APP) decoding of their component codes. In this paper, we show that one can approach capacity at high rates using iterative hard-decision decoding (HDD) of generalized product codes. Specifically, a class of spatially-coupled GLDPC codes with BCH component codes is considered, and it is observed that, in the high-rate regime, they can approach capacity under the proposed iterative HDD. These codes can be seen as generalized product codes and are closely related to braided block codes. An iterative HDD algorithm is proposed that enables one to analyze the performance of these codes via density evolution (DE).
Cite
@article{arxiv.1202.6095,
title = {Approaching Capacity at High-Rates with Iterative Hard-Decision Decoding},
author = {Yung-Yih Jian and Henry D. Pfister and Krishna R. Narayanan},
journal= {arXiv preprint arXiv:1202.6095},
year = {2017}
}
Comments
22 pages, this version accepted to the IEEE Transactions on Information Theory