Iterative Error Correction Decoder for Memory Error Floor Mitigation
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Solution Overview
Problem
Conventional error correction systems often encounter the error floor phenomenon, where error correction decoding fails at specific error levels, leading to a sudden flattening of signal-to-noise ratio versus bit error rate curves, which existing technologies struggle to mitigate effectively.
Innovation Solution
An error correction decoder and memory controller system that includes a node processor for iterative decoding, a reliability information generator, and a parameter adjuster. The system adjusts parameters based on reliability information to manage iterative decoding processes, specifically adjusting initial LLR values and scaling factors to overcome decoding failures and prevent error floor phenomena.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional error correction decoding is performed without parameter adjustment, then the decoding process is simple and fast, but error correction fails at specific error levels causing error floor phenomenon
Solution Approach 1:
The patent implements dynamic parameter adjustment during iterative decoding by introducing a parameter adjuster that modifies scaling factors and node processor operations based on real-time decoding performance. The system dynamically changes decoding parameters across iterations rather than using fixed parameters, allowing adaptation to varying error conditions and preventing error floor phenomenon.
Solution Approach 2:
The patent changes physical or operational parameters of the decoding system by adjusting scaling factors applied to log-likelihood ratios (LLRs) and modifying node processor parameters based on reliability information from previous iterations. This parameter adaptation enables the system to overcome error floors by tailoring decoding behavior to the specific error characteristics of the received signal.
2Reliability
If iterative decoding with multiple parameters is used, then error correction capability is improved, but decoding complexity and processing time increase
Solution Approach 1:
The patent implements feedback mechanisms where reliability information from each decoding iteration is fed back to the parameter adjuster, which then modifies parameters for subsequent iterations. This closed-loop control allows the system to adapt parameters based on actual decoding progress, avoiding unnecessary computational overhead when decoding succeeds early while enabling parameter adjustments when additional iterations are needed to overcome error floors.
3Reliability
If parameter adjustment based on reliability information is implemented, then error floor phenomenon is mitigated, but system complexity and computational overhead increase
Solution Approach 1:
The patent introduces a parameter adjuster as an intermediary component that sits between the node processor and the rest of the decoding system. This intermediary receives reliability information, determines appropriate parameter adjustments, and applies them to the node processor operations. By localizing the complexity in this dedicated intermediary module, the system achieves error floor mitigation while maintaining a structured and manageable architecture.
Data Source
AI summary
There are provided an error correction decoder and a memory system having the same. The error correction decoder includes a node processor for performing at least one iteration of an error correction decoding based on at least one parameter used for an iterative decoding, a reliability information generator for generating reliability information corresponding to a current iteration upon a determination that the error correction decoding corresponding to the current iteration has been unsuccessful, and a parameter adjuster for adjusting the at least one parameter upon a determination that the reliability information satisfies a predetermined condition, and controlling the node processor to perform a next iteration based on the adjusted.