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Quantization and reliability-aware iterative majority-logic decoding algorithm for LDPC code in TLC NAND flash memory

Authors: Lingjun Kong; Jiaying Wen; Guojun Han; Shengmei Zhao; Ming Jiang 0012; Chunming Zhao 0001;

Quantization and reliability-aware iterative majority-logic decoding algorithm for LDPC code in TLC NAND flash memory

Abstract

Multi-level per cell (MLC) /Triple-Level per cell (TLC) technique significantly improves storage density with low cost increases, which stores more than one bit per cell, but also drastically decreases reliability in NAND flash memory. As the bit number per cell increases, correspondingly cell-to-cell interference (CCI) becomes the major challenge for NAND flash memory technology scaling. Recently, low-density parity-check (LDPC) code is considered as the most appropriate scheme of next generation Error Correcting Code (ECC) in NAND flash memory. In this paper, by exploiting the intra-cell characteristics in TLC NAND flash memory channels, a low-complexity quantization and reliability-Aware iterative majority-logic decoding (QR-IMLGD) algorithm for LDPC code is proposed to reduce the memory read latency and effectively improve the throughput of LDPC decoding. The proposed algorithm takes advantage of highly unequal error probability of input log-likelihood-ratios (LLRs) in the same cells, employ small bit-level quantizer and update only less reliable variable nodes that are initiated with higher error probability LLR values. Simulation results show that the proposed QR-IMLGD algorithm can yield a noticeable improvement in decoding convergence rate without compromising the error performance in TLC NAND flash memory channels.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
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