Quasi-Cyclic LDPC Base Matrix for Flexible Code Lengths and Rates
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Solution Overview
Problem
Current LDPC code implementations face challenges in supporting flexible code lengths and code rates, which limits their adaptability to varying performance requirements in communications systems, particularly in achieving optimal encoding performance and minimizing error floors.
Innovation Solution
The proposed solution involves an encoding method and apparatus that utilize a specific LDPC matrix structure, derived from a base matrix with defined lifting factors and shift values, to encode input sequences. This structure includes a base matrix with specific non-zero elements and corresponding shift values, allowing for the generation of LDPC codes with flexible code lengths and rates, and is implemented using an encoder and determining unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a conventional LDPC code scheme is used, then the decoding throughput is improved, but the adaptability to varying code lengths and code rates deteriorates
Solution Approach 1:
The LDPC base matrix is segmented into multiple sub-matrices with specific structures (e.g., identity matrices, zero matrices, and dense sub-matrices). This segmentation allows the code to support multiple code lengths and rates by selectively using different sub-matrices, while maintaining the quasi-cyclic structure that enables high throughput decoding through parallel processing.
Solution Approach 2:
The patent employs dynamic selection of lifting factors and base matrix configurations to adapt to different code lengths and rates. The base matrix structure allows dynamic reconfiguration by changing which sub-matrices are activated and how they are arranged, enabling the system to optimize performance for various communication scenarios while maintaining efficient decoding.
2Ease of manufacture
If the LDPC matrix structure is simplified for easier implementation, then the ease of manufacture is improved, but the encoding performance and error floor characteristics deteriorate
Solution Approach 1:
The base matrix employs local quality variation by using different sub-matrix types (identity matrices for systematic bits, zero matrices for punctured bits, and dense sub-matrices for parity bits) in different regions. This local differentiation optimizes encoding performance and error floor characteristics for specific code lengths and rates while maintaining overall structural simplicity through the quasi-cyclic framework.
3Device complexity
If a fixed base matrix structure is used, then the device complexity is reduced, but the flexibility to support multiple code lengths and rates deteriorates
Solution Approach 1:
The base matrix is designed with universal sub-matrices that can serve multiple functions depending on configuration. The same base matrix structure can support different code lengths and rates by dynamically selecting and arranging sub-matrices, eliminating the need for multiple dedicated base matrices and reducing overall device complexity while maintaining flexibility.
Data Source
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AI summary
This application discloses an encoding method, an apparatus, a communications device, and a communications system. The method includes: encoding an input bit sequence by using a low-density parity-check LDPC matrix, where the LDPC matrix is obtained based on a lifting factor Z and a base matrix, the base matrix includes row 0 to row 4 and column 0 to column 26 in one of matrices shown in FIG. 3b-1 to FIG. 3b-10, or the base matrix includes row 0 to row 4 and some of column 0 to column 26 in one of the matrices shown in FIG. 3b-1 to FIG. 3b-10. The encoding method, the apparatus, the communications device, and the communications system in this application can meet a channel encoding requirement.