LDPC Decoding Early Termination Using Syndrome Weight Thresholds
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Solution Overview
Problem
Existing LDPC decoding processes face challenges in meeting latency and processing performance requirements due to their iterative nature, which can lead to increased latency and processing burden, especially in applications where decoding must be completed within a short time or with limited processing resources.
Innovation Solution
The implementation of an early termination mechanism for LDPC iterative decoding, using parameters such as the number of iterations and the weight of the syndrome, allows for termination before reaching the maximum number of iterations, based on thresholds for the iteration number and checksum, thereby improving latency and reducing processing burden without significant degradation in error correction capability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the maximum number of iterations is used for LDPC decoding, then the error correction capability is improved, but the latency and processing burden increase
Solution Approach 1:
The patent implements a feedback mechanism by monitoring the syndrome weight at each iteration and comparing it to a threshold. When the syndrome weight becomes sufficiently small (below the threshold), the decoding process receives feedback to terminate early, avoiding unnecessary additional iterations. This feedback loop enables the system to adaptively stop decoding when the desired error correction capability is achieved, thereby reducing latency without compromising reliability.
Solution Approach 2:
The patent applies partial action by performing only the necessary number of iterations required to achieve adequate error correction, rather than always executing the maximum number of iterations. By using the syndrome weight threshold to determine when to stop, the system performs just enough decoding work to achieve the required reliability, avoiding excessive iterations that would only increase latency without providing significant additional error correction benefit.
2Reliability
If the maximum number of iterations is used for LDPC decoding, then the error correction capability is improved, but the processing burden increases
Solution Approach 1:
The feedback mechanism monitors the syndrome weight and provides termination signals when the error correction capability is sufficient. This reduces the processing burden by avoiding unnecessary iterations while maintaining the required reliability through adaptive stopping based on actual decoding progress.
Solution Approach 2:
By performing only the partial number of iterations needed to achieve the threshold syndrome weight, the system reduces processing burden significantly compared to always executing the maximum iterations, while still achieving the necessary error correction capability.
3Loss of time
If early termination is implemented based on syndrome weight threshold, then the latency is reduced, but the error correction capability may be compromised
Solution Approach 1:
The patent changes the parameter being monitored from a fixed iteration count to a dynamic syndrome weight threshold. By using the syndrome weight (a parameter that directly reflects decoding progress and error correction status) as the termination criterion, the system can early-terminate with confidence that the required error correction capability has been achieved, thus reducing latency without compromising reliability.
Data Source
AI summary
Techniques for improving the latency or processing performance of an error correction system are described. In an example, the error correction system implements LDPC decoding and uses an early termination rule to determine whether the LDPC decoding should be terminated prior to reaching a maximum number of iterations. The early termination rule involves various parameters that relate to the syndrome of the decoded LDPC codeword at each iteration. These parameters include the number of the current decoding iteration and the weight of the syndrome at the current iteration. For example, the early termination rule specifies that the LDPC decoding should be terminated prior to the maximum number of iterations either when the weight of the syndrome is zero, or when the current number of iterations reaches an iteration number threshold and the weight of the syndrome equals or exceeds a checksum threshold.