LLR-Distribution-Based Non-Uniform Quantization for RBI-MSD Algorithm in MLC Flash Memory

Multi-level cell (MLC) technique has been widely used to improve the storage capacity of NAND flash memory at the price of sacrificing some storage reliability. As a type of excellent error-correction codes, low-density parity-check (LDPC) codes can significantly enhance the performance of flash mem...

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Bibliographic Details
Published in:IEEE communications letters Vol. 22; no. 1; pp. 45 - 48
Main Authors: Ouyang, Shijie, Han, Guojun, Fang, Yi, Liu, Wenjie
Format: Journal Article
Language:English
Published: IEEE 01.01.2018
Subjects:
Complexity theory
Decoding
Iterative decoding
LDPC codes
NAND flash memory
non-uniform quantization
Quantization (signal)
Reliability
reliability-based iterative min-sum decoding
Threshold voltage
ISSN:1089-7798
Online Access:Get full text
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Summary:Multi-level cell (MLC) technique has been widely used to improve the storage capacity of NAND flash memory at the price of sacrificing some storage reliability. As a type of excellent error-correction codes, low-density parity-check (LDPC) codes can significantly enhance the performance of flash memory. However, the conventional decoding algorithms for LDPC codes suffer from the drawback of high complexity. To address this problem, we propose a serial reliability-based iterative min-sum decoding (RBI-MSD) algorithm for LDPC-coded MLC flash memory systems to strike a desirable trade-off between the performance and complexity. Furthermore, we conceive a novel log-likelihood-ratio (LLR)-distribution-based non-uniform quantization method for the RBI-MSD algorithm. Unlike conventional quantization methods, the proposed non-uniform quantization method substantially exploits the distribution characteristics of channel initial LLRs in MLC flash memory. Simulation results indicate that the proposed non-uniform quantization method not only exhibits more excellent error performance than the conventional non-uniform and uniform counterparts, but also is applicable to other RBI decoding algorithms.
ISSN:1089-7798
DOI:10.1109/LCOMM.2017.2755023