Improved Soft-aided Decoding of Product Codes with Dynamic Reliability Scores
Sisi Miao, Lukas Rapp, and Laurent Schmalen

TL;DR
This paper introduces a low-complexity hybrid decoding algorithm for product codes that uses dynamic reliability scores to reduce miscorrections and improve performance, achieving up to 1.2 dB gain over traditional iBDD.
Contribution
A novel hybrid decoding method combining error-and-erasure decoding with dynamic reliability scores for product codes, enhancing performance with minimal complexity increase.
Findings
Significant reduction in miscorrection rate.
Coding gains up to 1.2 dB over conventional iBDD.
Requires only ternary message passing.
Abstract
Products codes (PCs) are conventionally decoded with efficient iterative bounded-distance decoding (iBDD) based on hard-decision channel outputs which entails a performance loss compared to a soft-decision decoder. Recently, several hybrid algorithms have been proposed aimed to improve the performance of iBDD decoders via the aid of a certain amount of soft information while keeping the decoding complexity similarly low as in iBDD. We propose a novel hybrid low-complexity decoder for PCs based on error-and-erasure (EaE) decoding and dynamic reliability scores (DRSs). This decoder is based on a novel EaE component code decoder, which is able to decode beyond the designed distance of the component code but suffers from an increased miscorrection probability. The DRSs, reflecting the reliability of a codeword bit, are used to detect and avoid miscorrections. Simulation results show that…
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