LDPC Check Node Group Scheduling for Faster Error Correction
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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 error correction processing.
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 check nodes, 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 implemented, but the processing time and number of iterations increase due to lack of prioritization
Solution Approach 1:
The patent changes the scheduling parameter from uniform/fixed ordering to dynamic cost-function-based prioritization. By evaluating a cost function for each check node group that considers reliability values and unsatisfied check node counts, the system dynamically adjusts processing priorities to handle distorted data more efficiently, reducing iterations and processing time.
Solution Approach 2:
The patent introduces dynamic scheduling where the processing order of check node groups is not fixed but adapts based on real-time evaluation of cost functions. The system dynamically reorders processing based on current reliability values and error patterns, allowing it to respond to distorted data conditions and optimize decoding performance.
2Ease of manufacture
If all check nodes are processed equally in sequential order, then the implementation is simple, but error correction efficiency decreases for distorted data
Solution Approach 1:
The patent applies local quality by treating different check node groups differently based on their specific characteristics. Instead of uniform processing, each group is evaluated using a cost function that considers its reliability values and unsatisfied check node count, allowing targeted prioritization of groups that need more attention for error correction.
Solution Approach 2:
The patent implements feedback mechanisms where the cost function evaluation continuously monitors decoding progress through reliability values and unsatisfied check node statuses. This feedback drives the dynamic reordering of processing sequences, allowing the system to adapt and improve error correction efficiency based on actual decoding state.
Data Source
AI summary
A cost function is obtained. For each of a plurality of groups of check nodes associated with low-density parity-check (LDPC) encoded data, the cost function is evaluated using information associated with a variable node and/or information associated with a check node. One of the groups of check nodes is selecting based at least in part on the evaluated cost functions. Error correction decoding related processing is performed on the selected group of check nodes.