Multi-Pass LDPC Decoding with Selective Symbol Modification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data processing systems face challenges with error correction, particularly with high rate low density parity check codes, where short cycles lead to performance degradation in belief propagation decoders, and maximum likelihood decoders are too complex for practical implementation.
Innovation Solution
The system employs a data decoder circuit with a partial maximum likelihood decode value modification circuit to selectively modify outputs of a low complexity decoder, such as a belief propagation decoder, to correct errors by identifying and modifying symbols associated with unsatisfied checks, thereby reducing the complexity of the decoding process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a belief propagation decoder is used for high rate low density parity check codes, then the decoding complexity is reduced, but the performance degrades due to short cycles causing message correlation
Solution Approach 1:
The patent introduces an intermediary component called the 'decode value modification circuit' that sits between the belief propagation decoder and the final decoded output. This circuit identifies symbols associated with unsatisfied parity checks and modifies their values to break the harmful message correlation caused by short cycles, thereby improving decoding performance without significantly increasing overall system complexity.
Solution Approach 2:
Instead of modifying the entire decoding process uniformly, the patent applies local quality by selectively modifying only those decode values that are associated with unsatisfied parity checks. The decode value modification circuit identifies specific symbols contributing to failed parity checks and modifies only those local regions of the decoded data, rather than reprocessing all data through a completely different decoding algorithm.
2Reliability
If a maximum likelihood decoder is used, then decoding performance is improved, but the device complexity becomes too high for practical implementation
Solution Approach 1:
The patent applies partial action by implementing a modified belief propagation decoder that performs most of the decoding work using the low-complexity belief propagation algorithm, then applies additional modifications only to the extent necessary to correct errors associated with unsatisfied parity checks. This avoids the excessive complexity of a full maximum likelihood decoder while achieving improved performance through targeted corrections.
Solution Approach 2:
The decoding process is segmented into two distinct stages: first, a belief propagation decoder performs initial decoding to produce a preliminary decoded output; second, a decode value modification circuit processes specific portions of this output that are associated with unsatisfied parity checks. This segmentation allows the system to combine the low complexity of belief propagation with the improved performance of more sophisticated decoding approaches.
Data Source
AI summary
Various embodiments of the present invention provide systems and methods for data processing. For example, data decoding systems are disclosed that include a data decoder circuit and a decode value modification circuit.