Nonvolatile Memory Decoding With Selective Euclid Distance Pruning
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Solution Overview
Problem
In memory systems, soft decision decoding methods face a challenge in reducing delay time during data reading without degrading error correction capability, as they require extensive calculations for Euclid distances across all code words, which can lead to prolonged processing times.
Innovation Solution
The memory system incorporates a list generating unit and a test pattern reducing unit to exclude test patterns with no possibility of having a shorter Euclid distance than the existing maximum likelihood decoding word candidate, and a test pattern execution determining unit to skip decoding for patterns that cannot update the maximum likelihood decoding word candidate, thereby reducing the amount of calculation and shortening delay time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If extensive calculations for Euclid distances across all code words are performed to maintain error correction capability, then error correction capability is maintained, but delay time increases
Solution Approach 1:
The patent applies partial action by performing Euclid distance calculations only for selected test patterns rather than all code words. The test pattern reducing unit identifies and excludes test patterns that cannot possibly have a shorter Euclid distance than the current maximum likelihood decoding word candidate, thereby performing calculations only on the necessary subset of test patterns while maintaining error correction capability.
Solution Approach 2:
The patent segments the decoding process into distinct stages: test pattern generation, test pattern reduction, selective decoding execution, and maximum likelihood word selection. By dividing the calculation process into these segments and applying reduction criteria at the test pattern selection stage, the system reduces overall computational load while preserving accuracy.
2Measurement precision
If decoding is performed for all test patterns to ensure accurate maximum likelihood decoding, then decoding accuracy is maintained, but calculation amount increases
Solution Approach 1:
The patent applies preliminary action by performing test pattern reduction before the actual decoding calculations. The test pattern reducing unit pre-identifies and excludes test patterns that cannot improve the maximum likelihood decoding result, so that subsequent decoding operations are performed only on the reduced set of relevant test patterns, reducing calculation amount while maintaining accuracy.
Solution Approach 2:
The patent extracts and removes unnecessary test patterns from the calculation process. By identifying test patterns that cannot possibly have a shorter Euclid distance than the current candidate and excluding them beforehand, the system performs decoding only on the essential subset of test patterns, reducing computational complexity without sacrificing decoding accuracy.
Data Source
AI summary
According to an embodiment, a memory system includes: a test pattern decoding unit that detects an intermediate decoding word from a plurality of test patterns; a Euclid distance calculating unit that calculates a Euclid distance between the intermediate decoding word and a received word; and a maximum likelihood decoding word selecting unit that maintains a maximum likelihood decoding word candidate. In a case where a Euclid distance of the intermediate decoding word is shorter than a Euclid distance of the maximum likelihood decoding word candidate, the maximum likelihood decoding word selecting unit updates the maximum likelihood decoding word candidate by using the intermediate decoding word and the test pattern decoding unit does not execute decoding of a test pattern having no possibility that the Euclid distance of the intermediate decoding word becomes shorter than the Euclid distance of the maximum likelihood decoding word candidate.