Layered LDPC Decoder Precision Control for Error Floor Reduction
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Solution Overview
Problem
Low-density parity check (LDPC) codes experience higher error floors due to insufficient precision in message passing algorithms, leading to near-codeword failures and catastrophic errors, especially in the error floor region of their performance curve, which degrades data transmission reliability and rate.
Innovation Solution
Optimizing the precision of a-posteriori P type messages and Q type messages in the layered iterative decoder, such as freezing messages at saturation values or selecting finite precisions to avoid catastrophic errors, and adjusting precisions based on channel type and performance requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If finite precision is used in message passing algorithms, then computational complexity is reduced, but error floor performance deteriorates due to catastrophic errors and near-codeword failures
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the precision of message passing algorithms based on the decoding state. When messages approach saturation values, the system increases precision to avoid catastrophic errors, and reduces precision when not needed to maintain computational efficiency. This adaptive parameter adjustment resolves the contradiction between computational complexity and error floor performance.
Solution Approach 2:
The invention implements dynamics by making the precision of message passing adaptive rather than static. The system monitors message values and adjusts precision levels dynamically during decoding iterations, transitioning between different precision states based on the actual decoding progress and message saturation levels, thereby optimizing both complexity and reliability.
2Reliability
If message precision is increased to avoid catastrophic errors, then decoding reliability improves, but computational complexity and memory requirements increase
Solution Approach 1:
The patent applies local quality by differentiating precision requirements across different parts of the decoding process. Instead of uniformly high precision throughout, the system uses higher precision only for messages that are close to saturation values and lower precision for other messages, thereby improving reliability where needed while controlling overall computational complexity.
Solution Approach 2:
The invention uses parameter changes to adjust message precision based on the actual values being decoded. When messages approach saturation thresholds, the system increases precision locally for those specific messages, and maintains lower precision for messages that do not require high accuracy, optimizing the trade-off between reliability and complexity.
3Productivity
If layered update schedule is used, then decoding speed increases with half the iterations, but precision requirements increase leading to higher error floors
Solution Approach 1:
The patent applies dynamics by making the precision adaptation specific to the layered update schedule. The system monitors messages updated in each layer and adjusts precision dynamically based on saturation detection, allowing the layered schedule to maintain its speed advantage while preventing error floors through localized precision increases only when and where needed.
Solution Approach 2:
The invention uses parameter changes to adjust message precision in response to the layered update schedule's specific requirements. By detecting saturation values in messages processed during layered updates, the system increases precision parameter settings selectively, thereby maintaining decoding speed while preventing the error floor phenomenon.
4Reliability
If precision optimization is applied to avoid near-codeword failures, then error floor performance improves, but computational overhead increases
Solution Approach 1:
The patent applies partial action by implementing precision optimization only for the specific case of avoiding near-codeword failures, rather than applying high precision universally. The system detects when messages are approaching saturation values that indicate near-codeword conditions and applies precision adjustments only in those specific instances, reducing unnecessary computational overhead while improving error floor performance.
Data Source
AI summary
Systems and methods are provided for selecting precisions during iterative decoding with a low-density parity check (LDPC) decoder in order to maximize LDPC code's performance in the error floor region. The selection of the precision of the messages may be done in such a way as to avoid catastrophic errors and to minimize the number of near-codeword errors during the decoding process. Another system and method to avoid catastrophic errors in the layered (serial) LDPC decoder is provided. Lastly, a system and method that select precisions and provide circuitry that optimizes the exchange of information between a soft-input, soft-output (SISO) channel detector and an error correction code (ECC) decoder for channels with memory is provided.