Multi-Dimensional ECC Decoding Using Intersection Bit Maps
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Solution Overview
Problem
The increasing density of data in nonvolatile memory modules leads to reduced storage reliability and increased storage errors, necessitating more complex error correcting codes (ECC) that degrade efficiency and throughput, while flash memory systems face challenges in error correction due to the unavailability of original source data for retransmission protocols.
Innovation Solution
A system and method for decoding multi-dimensional encoded data by using a map to locate intersection bits encoded by multiple component codes, applying error correction hypotheses to correct errors in multiple dimensions, and generating intersection maps on-the-fly for efficient error correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If more complex error correcting codes (ECC) are used to compensate for increased storage errors in high-density nonvolatile memory, then storage reliability is improved, but decoding efficiency and throughput are degraded
Solution Approach 1:
The patent segments the decoding process into multiple independent dimensions, where each dimension processes a subset of encoded data. Instead of applying complex ECC to the entire data set at once, the data is divided into multiple code blocks that can be decoded in parallel across different dimensions, reducing the computational complexity per dimension while maintaining overall error correction capability.
Solution Approach 2:
The patent introduces a multi-dimensional decoding approach where data is encoded and decoded across multiple dimensions rather than a single dimension. Each dimension applies a simpler component code, and the intersection of multiple dimensions provides enhanced error correction. This dimensional expansion allows the system to achieve high reliability through the combination of multiple simpler codes rather than relying on a single complex code.
2Reliability
If higher reliability standards are enforced in flash memory output streams compared to communication transmissions, then data integrity is improved, but system complexity increases due to the inability to use retransmission protocols
Solution Approach 1:
The patent creates multiple encoding dimensions where each dimension provides an independent encoding of the data. The intersection bits that appear in multiple dimensions serve as redundant checks, enabling the system to detect and correct errors with high confidence without needing retransmission. This multi-dimensional approach achieves communication-grade reliability in storage where retransmission is not feasible.
Solution Approach 2:
The patent uses intersection bits as intermediaries between multiple component codes. These intersection bits serve as a mediator that connects different encoding dimensions and provides a mechanism for cross-validation. By using these intermediary elements, the system can achieve high reliability through layered verification without requiring complex centralized error correction mechanisms.
3Reliability
If multiple different component codes are used to encode each input bit in multiple different encoding dimensions, then error correction capability is enhanced, but computational complexity increases
Solution Approach 1:
The patent segments both the data and the decoding process into multiple manageable dimensions. Each dimension uses a component code that is designed to be computationally efficient, and the overall error correction capability emerges from the combination of these segmented approaches. This segmentation allows the use of multiple different component codes without requiring the system to handle their full computational complexity simultaneously.
Solution Approach 2:
The patent applies partial error correction in each dimension rather than attempting complete error correction across all dimensions simultaneously. Each component code performs partial error correction on its subset of data, and the intersection of multiple partial corrections achieves the desired overall error correction capability. This partial action approach reduces the computational burden compared to exhaustive error correction methods.
Data Source
AI summary
A system and method for decoding multi-dimensional encoded data. A set of multi-dimensional encoded data may be received encoding each input bit in a set of input bits by multiple different component codes in multiple different encoding dimensions. The multi-dimensional data may potentially have errors. A map may be used to locate each set of intersection bits that encode the same input bit by multiple unsolved component codes. The unsolved component codes may be decoded using one or a plurality of tested error correction hypotheses that yields a decoding success, where each hypothesis correcting a different set of intersection bits for a different input bit. The successful hypothesis may be applied for correcting the multi-dimensional encoded data.