List Decode Result Screening for Reed-Solomon Error Selection
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Solution Overview
Problem
Reed-Solomon codes face challenges in correcting a larger number of symbol errors, particularly when error patterns exceed the code distance (τ≥D/2), as existing methods produce a large and varied list of potential error patterns, making it difficult to select the most likely correctable error pattern.
Innovation Solution
The implementation of a list decode management circuit that filters out unlikely error patterns and assigns error weights based on bit errors, using a set of error pattern screens and weighting schemas to select the most likely error pattern for correction, incorporating error pattern screening, weighting, and adjustment circuits to manage results from list decode methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If list decode methods are used to correct a larger number of symbol errors (τ≥D/2), then error correction capability is improved, but the number of potential error patterns increases making it difficult to select the most likely correctable error pattern
Solution Approach 1:
The patent segments the large list of potential error patterns into multiple subsets or groups, making it easier to manage and select from. By dividing the comprehensive error pattern list into smaller segments, the system can more efficiently identify and select the most likely correctable error pattern without being overwhelmed by the total number of possibilities.
Solution Approach 2:
The patent changes parameters of error patterns by assigning different weights to various error patterns based on their likelihood. This weighting system transforms the selection process from a simple enumeration problem to a ranked selection problem, where error patterns are ordered by their probability of being the actual error pattern, facilitating easier identification of the most likely candidate.
2Reliability
If multiple list decode methods are used to generate potential error patterns, then error correction coverage is improved, but the quantity of potential error patterns increases
Solution Approach 1:
The patent merges the results from multiple list decode methods into a unified error pattern list. By combining the output of different decoding algorithms and methods, the system achieves comprehensive error correction coverage while managing the total quantity of error patterns through systematic integration and deduplication processes.
Solution Approach 2:
The patent discards duplicate or highly improbable error patterns from the combined list while recovering and retaining unique valuable patterns. This filtering process reduces the quantity of potential error patterns by eliminating redundancies and focusing on distinct, plausible error scenarios that require correction.
3Measurement precision
If error pattern screening and weighting is applied, then selection accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent applies preliminary screening and weighting actions to error patterns before final selection. By pre-processing the error pattern list to assign weights and filter patterns based on initial criteria, the system improves selection accuracy in advance, reducing the computational burden during the final selection phase and managing processing complexity through staged evaluation.
Data Source
AI summary
Examples disclosed herein relate to very large-scale integration (VLSI) circuit implementations of circuits for managing results from list decode methods. In accordance with some examples disclosed herein, a plurality of potential error patterns for correcting errors in a codeword may be received. The plurality of potential error patterns may be generated using a plurality of different list decode methods. Error patterns among the plurality of potential error patterns may be determined and marked as candidate error patterns using a set of error pattern screens. Error weights may be assigned to the candidate error patterns based on a quantity of bit errors in each symbol included therein. Weights for candidate error patterns that are indicative of a memory device failure may be adjusted using a scaling factor. An error pattern among the candidate error patterns may be selected to correct the errors in the codeword based on the assigned error weights.