Irregular LDPC Decoder Non-Uniform Scaling for Error Correction
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Solution Overview
Problem
Existing data processing systems face challenges in efficiently decoding data encoded with irregular low density parity check codes, particularly in correcting errors introduced during transmission and storage, due to limitations in error correction mechanisms.
Innovation Solution
A non-binary layered low density parity check decoder with non-uniform scaling is employed, which includes a check node processor that finds minimum, next minimum, and index of minimum values for likelihood values, and applies non-uniform scaling based on column weight and iteration numbers to improve decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If non-uniform scaling is applied to minimum and next minimum values in check node processing, then error correction capability and decoding accuracy are improved, but computational complexity and processing overhead increase
Solution Approach 1:
The patent applies non-uniform scaling to the minimum and next minimum values in the check node processing algorithm. Different scaling factors are used based on the column weight of the LDPC code, transforming the parameter values to improve decoding accuracy and error correction capability while managing computational complexity through selective application.
Solution Approach 2:
The scaling operation is applied selectively to specific values (minimum and next minimum) in the check node processing rather than uniformly to all computations. This localized application of quality enhancement focuses computational resources where they provide the most benefit to error correction performance.
2Measurement precision
If non-uniform scaling based on column weight and iteration numbers is used, then decoding accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The scaling factors are dynamically adjusted based on iteration numbers during the decoding process. The algorithm adapts the scaling applied to minimum and next minimum values as iterations progress, allowing for improved accuracy while managing processing time through iterative refinement rather than static high-cost processing.
Solution Approach 2:
The column weight-based scaling factors are pre-determined based on the LDPC code structure before decoding begins. This preliminary preparation allows the decoder to apply appropriate scaling without real-time computation of complex factors during the time-critical decoding process.
3Reliability
If minimum and next minimum values are found and scaled for each check node, then error detection capability is enhanced, but device complexity and operational difficulty increase
Solution Approach 1:
The check node processor automatically identifies and processes the minimum and next minimum values through built-in comparison logic. The system performs these operations autonomously as part of the standard check node processing workflow, eliminating the need for external intervention or complex manual configuration while enhancing error detection capability.
Data Source
AI summary
An apparatus for decoding data includes a data decoding circuit configured to decode data encoded with an irregular low density parity check code based on a parity check matrix with non-uniform column weights, and at least one scaling circuit configured to scale values in the data decoding circuit with a scaling value that is dependent at least in part on a column weight of the likelihood values being scaled.