Soft Read Value Mapping for NAND Flash Dynamic Range
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Solid state storage systems, such as NAND Flash, do not natively return soft read values like log-likelihood ratio (LLR) values, and existing techniques for generating these values do not effectively improve system performance in terms of error rate and processing efficiency.
Innovation Solution
A process and apparatus for generating soft read values that optimize dynamic range by using bin identification information and estimation functions, such as linear or non-linear functions, to determine LLR values, ensuring these values utilize the full dynamic range and are invariant to program erase cycles and data age, thereby improving error correction decoding performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If soft read values are generated using existing synthesis techniques, then soft read values can be obtained for solid state storage devices, but the system performance in terms of error rate and processing efficiency is not effectively improved
Solution Approach 1:
The patent transforms hard read values into soft read values by applying parameter transformations (log-likelihood ratio calculations) that optimize the dynamic range. This involves changing the representation parameters of read values to improve both error rate performance and processing efficiency simultaneously, rather than treating them as separate trade-offs.
Solution Approach 2:
The patent introduces an intermediary processing stage that converts hard read values into soft read values using estimation functions. This intermediary transformation layer enables the system to achieve both improved reliability and processing efficiency by mediating between the raw read values and the decoding process.
2Quantity of substance
If the dynamic range of soft read values is not optimized, then bit wastage and storage requirements increase, but decoding performance can be maintained
Solution Approach 1:
The patent optimizes the dynamic range of soft read values by applying parameter transformations that ensure the full utilization of available bit representation. The estimation functions are designed to map read values into an optimized dynamic range, reducing bit wastage while maintaining decoding performance through careful parameter selection and scaling.
Data Source
AI summary
A plurality of bins and a plurality of soft read values are stored in a lookup table where those bins that are either a leftmost bin or a rightmost bin correspond to soft read values having a maximum magnitude. Bin identification information is received for a cell in solid state storage. A soft read value is generated for the cell in solid state storage, including by: accessing the lookup table, mapping the received bin identification information to one of the plurality of bins in the lookup table, and selecting the soft read value in the lookup table that corresponds to the bin which is mapped to.