LDPC Decoder Min-Sum Approximation for Lower Computing Complexity
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Solution Overview
Problem
Existing LDPC decoding methods are complex and require high computing resources, making them inefficient for error correction in digital communication systems.
Innovation Solution
A decoding method for LDPC codes that involves determining check nodes, variable nodes, and variable-to-check messages, followed by identifying a set of minimum magnitude values to generate check-to-variable messages, reducing complexity and resource requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the sum-product algorithm is used for LDPC decoding, then error correction performance is improved, but computing complexity and resource requirements increase
Solution Approach 1:
The patent transforms the sum-product algorithm's hyperbolic tangent operations into min-sum algorithm operations by changing the mathematical parameters and operations used in the check-to-variable message calculations. This parameter change maintains error correction performance while significantly reducing computing complexity by using simpler min and add operations instead of complex hyperbolic functions
Solution Approach 2:
The patent uses approximation techniques in the min-sum algorithm that sacrifice some computational precision for much lower computational cost. By using simplified message passing operations and approximate calculations, the system achieves acceptable error correction performance with dramatically reduced computing resources
2Reliability
If the sum-product algorithm is used for LDPC decoding, then error correction performance is improved, but computing resources required increase
Solution Approach 1:
The patent changes the computational parameters from complex hyperbolic tangent functions to simpler min-sum operations, which require fewer computational resources and less energy to execute while maintaining comparable error correction performance
Solution Approach 2:
The patent replaces the complex mathematical mechanism of the sum-product algorithm with the simpler min-sum algorithm mechanism, substituting hyperbolic function calculations with basic minimum and addition operations that consume fewer computing resources and energy
3Measurement precision
If the sum-product algorithm is used for LDPC decoding, then decoding accuracy is improved, but complexity increases
Solution Approach 1:
The patent changes the algorithmic parameters from precise but complex hyperbolic tangent calculations to simpler min-sum operations with adjusted approximation parameters, maintaining decoding accuracy through careful parameter selection while reducing algorithmic complexity
Solution Approach 2:
The patent uses approximate calculations in the min-sum algorithm that perform slightly less precise individual operations but achieve comparable overall decoding accuracy through iterative refinement and careful parameter tuning, while significantly reducing computational complexity
Data Source
AI summary
The present disclosure relates to a method of decoding Low-Density Parity-Check (LDPC) codes in received data. The method comprises determining check nodes, variable nodes, and variable-to-check (VTC) messages based on the LDPC codes. Three or more minimum magnitude values of the determined VTC messages are then determined to obtain a determined minimum VTC message set. A set of check node messages from the determined minimum VTC message set is also determined, wherein the determined set of check node messages and the determined minimum VTC message set are used to determine a set of check-to-variable (CTV) messages. The present disclosure also relates to a corresponding method for encoding.