LDPC Layered Decoding Schedules Using Correlation-Based Layer Ordering
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Solution Overview
Problem
Current wireless communication systems face complexity and resource intensity in determining hardware sequences for LDPC layered decoding, particularly in selecting which nodes to scan and update at each hardware cycle, which is computationally demanding.
Innovation Solution
The proposed method involves partitioning layers of a submatrix into sets based on punctured columns, generating correlation tables, sorting layers by correlation values, and combining these to create a decoding schedule with the shortest schedule length for efficient LDPC layered decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional methods are used to determine hardware sequences for LDPC layered decoding, then decoding accuracy can be maintained, but computational complexity and resource usage increase significantly
Solution Approach 1:
The patent segments the set of layers into multiple subsets based on the number of punctured columns (e.g., first subset with layers having one punctured column, second subset with layers having two punctured columns). This segmentation allows independent optimization of hardware sequences for each subset, reducing overall computational complexity while maintaining decoding accuracy through structured layer ordering.
2Reliability
If comprehensive layer ordering is performed to optimize decoding performance, then error performance improves, but the time and resources required for sequence determination increase
Solution Approach 1:
The patent performs preliminary actions by pre-determining layer subsets based on punctured column characteristics and pre-calculating correlation values within each subset. This preliminary organization enables faster hardware sequence generation during actual decoding operations, reducing the time loss associated with comprehensive optimization while maintaining error performance through structured layer ordering.
3Productivity
If detailed correlation analysis is performed across all layers, then optimal layer ordering is achieved, but resource intensity increases
Solution Approach 1:
The patent divides the correlation analysis into separate subsets based on punctured column characteristics. Instead of performing detailed correlation analysis across all layers simultaneously, the method performs correlation analysis independently within each subset (e.g., first subset with one punctured column, second subset with two punctured columns). This segmentation reduces memory access patterns and computational resource usage while maintaining decoding efficiency through optimized layer ordering within each subset.
Data Source
AI summary
Methods, systems, and devices for wireless communications are described. A wireless communication system may support techniques for correlation-based hardware sequences for layered decoding. In some cases, a user equipment (UE) may partition layers of a submatrix associated with a parity check decoding procedure into a first set of layers and a second set of layers. The UE may sort each set of layers into a respective set of layer orders (e.g., a first set of layer orders and a second set of layer orders) based on an associated set of correlation values. The UE may combine the first set of layer orders and the second set of layer orders to obtain a set of combined layer orders and may select a decoding schedule from a set of decoding schedules used for decoding each of the combined layer orders based on respective schedule lengths for the set of decoding schedules.