Trapping-set database for a low-density parity-check decoder

Abstract

A machine-implemented method of generating trapping-set information for use in LDPC-decoding processing of read signals generated, e.g., by sensing a storage medium, such as a magnetic platter. In one embodiment, the method can be implemented as an add-on to any other trapping-set search method in which the discovered trapping sets are evaluated to determine their influence on the overall bit-error rate and/or error-floor characteristics of the LDPC decoder. The method can advantageously reuse at least some of the computational results obtained during this evaluation, thereby requiring a relatively small amount of additional computations, while providing a significant benefit of discovering many more trapping sets in addition to the ones that are being evaluated.

Aleksandr Petiushko Александр Петюшко
Aleksandr Petiushko Александр Петюшко
Head of AI / Vice President, Head of RnD / Adjunct Professor / PhD

Principal R&D Researcher (20 years of experience), R&D Technical Leader (15 years of experience), and R&D Manager (10 years of experience). Running and managing industrial research and academic collaboration (45 publications, 40 patents). Hiring and transforming AI/ML teams. Inspired by theoretical computer science and how it changes the world.