LDPC Check-Node Scheduling Using Reliability Cost Functions
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Solution Overview
Problem
Current LDPC decoding techniques face inefficiencies in processing time and number of iterations, particularly in handling distorted LDPC encoded data, as they often rely on flooding or sequential scheduling methods that do not effectively prioritize processing based on error correction needs.
Innovation Solution
Implementing a cost function-based approach to selectively schedule the processing of check nodes, where a cost function evaluates and prioritizes groups of check nodes based on reliability values and unsatisfied parity checks, allowing for more focused error correction decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If flooding scheduling or sequential scheduling methods are used for LDPC decoding, then the decoding process can be completed, but the processing time and number of iterations are excessive
Solution Approach 1:
The patent changes the scheduling parameter from fixed (flooding) or simple sequential (HSS/VSS) to dynamic cost-function-based scheduling. The cost function evaluates multiple parameters including reliability values, unsatisfied parity checks, and iteration counts to determine the optimal processing order of check nodes, thereby reducing processing time and iterations.
Solution Approach 2:
The patent introduces dynamic scheduling where the processing order of check nodes is adjusted based on real-time decoding status. The cost function is recalculated after each iteration, and check nodes are re-prioritized based on current reliability values and unsatisfied parity check patterns, making the decoding process adaptive rather than static.
2Duration of action of moving object
If all check nodes are processed in parallel (flooding), then throughput is maintained, but processing time increases due to unnecessary iterations
Solution Approach 1:
The patent applies local quality by treating different check nodes differently based on their specific characteristics. Instead of uniform parallel processing, the cost function identifies which check nodes have higher priority based on local metrics such as reliability values and their contribution to satisfying unsatisfied parity checks, concentrating computational effort where it is most needed.
Solution Approach 2:
The patent uses partial action by selectively processing only the most critical check nodes in each iteration based on cost function evaluation. Rather than processing all check nodes equally, the method focuses computational resources on a subset of check nodes that will provide the greatest reduction in unsatisfied parity checks, reducing overall decoding duration.
3Reliability
If sequential scheduling (HSS/VSS) is used, then memory access patterns are improved, but the number of iterations increases
Solution Approach 1:
The patent changes the scheduling criterion from simple sequential indexing (HSS/VSS) to a multi-parameter cost function that considers reliability values, unsatisfied parity check counts, and iteration history. This parameter change enables the system to prioritize check nodes that are most likely to resolve errors, reducing iteration count while maintaining decoding reliability.
Data Source
AI summary
A cost function is obtained. For each of a plurality of groups of nodes, the cost function is evaluated by obtaining, for a given group of nodes, one or more reliability values associated with the given group of nodes; the one or more reliability values include sign and magnitude. For a given group of nodes, a reliability value with a smallest magnitude is selected where the evaluated cost function for the given group of nodes is set to the smallest magnitude. One of the plurality of groups of nodes is selected based at least in part on the evaluated cost functions. Error correction decoding related processing is performed on the selected group of nodes.