A primary source of increased read time on NAND flash comes from the fact that in the presence of noise, the flash medium must be read several times using different read threshold voltages for the decoder to succeed. This paper proposes an algorithm that uses a limited number of re-reads to characterize the noise distribution and recover the stored information. Both hard and soft decoding are considered. For hard decoding, the paper attempts to find a read threshold minimizing bit-error-rate (BER) and derives an expression for the resulting codeword-error-rate. For soft decoding, it shows that minimizing BER and minimizing codeword-error-rate are competing objectives in the presence of a limited number of allowed re-reads, and proposes a trade-off between the two. The proposed method does not require any prior knowledge about the noise distribution, but can take advantage of such information when it is available. Each read threshold is chosen based on the results of previous reads, following an optimal policy derived through a dynamic programming backward recursion. The method and results are studied from the perspective of an SLC Flash memory with Gaussian noise for each level but the paper explains how the method could be extended to other scenarios.
翻译:在 NAND 闪光上增加阅读时间的一个主要来源是,在噪音存在的情况下,闪光介质必须使用不同的读阈电压进行多次阅读,使解码器成功。本文建议一种算法,使用数量有限的重新阅读来描述噪音分布和回收存储的信息。考虑的是硬和软的解码。关于硬解码,文件试图找到读阈值,最大限度地减少位eror-ro率(BER),并产生由此产生的编码-eror-ra速率的表达。关于软解码,它表明在有限的允许重新阅读的情况下,尽量减少BER和最大限度地减少编码-eror率是相互竞争的目标,并提议在两种方法之间进行权衡。拟议方法并不要求事先了解噪音分布的情况,但在有这种信息时,可以利用这些信息。每个读阈值都是根据前文的结果选择的,采用通过动态编程向后回溯生成的最佳政策。关于软解码的解码,方法和结果是从SLC 闪烁记忆的角度研究方法和结果,但从纸张向高斯 的每个水平解释如何扩大的图像。