QC-LDPC Base Matrix Encoding for Flexible Code Lengths
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Solution Overview
Problem
Current LDPC code systems face challenges in supporting diverse code block lengths and code rates, which limits their flexibility and performance in various communication systems.
Innovation Solution
The proposed method involves using a lifting factor Z and a base matrix to generate LDPC matrices that can support different code block lengths, achieved by determining the appropriate lifting factor based on the input sequence length and using specific base matrices with row and column permutations to create parity-check matrices with varying structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed LDPC matrix is used, then the decoding structure is simple, but the system cannot support diverse code block lengths and code rates
Solution Approach 1:
The LDPC matrix is segmented into a base matrix and multiple permutation matrices. The base matrix contains the essential structure, while permutation matrices provide flexibility through row and column permutations. This segmentation allows the system to support diverse code block lengths and code rates by selectively permuting the base matrix without fundamentally changing the decoding structure.
Solution Approach 2:
The patent changes parameters of the LDPC matrix by applying different row and column permutation operations to the base matrix. By varying the permutation parameters (row permutations and column permutations), the system can generate different LDPC matrices suitable for different code block lengths and code rates while maintaining a consistent base structure that simplifies decoding.
2Adaptability or versatility
If different LDPC matrices are designed for different code block lengths, then the system supports diverse lengths, but the complexity of matrix design and management increases
Solution Approach 1:
A single base matrix is designed to serve multiple functions by supporting different code block lengths and code rates through permutation operations. Instead of designing separate LDPC matrices for each code block length, the universal base matrix can be transformed into various specific matrices by applying appropriate row and column permutations, thereby reducing matrix design and management complexity.
Solution Approach 2:
The LDPC matrix structure is made dynamic through the use of permutation operations. The base matrix remains static and simple, but its row and column permutations can be dynamically adjusted according to the required code block length and code rate. This dynamic approach allows flexible adaptation without increasing the complexity of the base matrix design.
3Productivity
If QC-LDPC matrices with high parallelism are used, then throughput increases, but the hardware complexity increases
Solution Approach 1:
The QC-LDPC matrix structure is segmented into a base matrix and permutation components, allowing the parallelism to be implemented in a structured manner. The base matrix provides a regular structure that can be efficiently implemented in hardware with high parallelism, while the permutation operations can be performed in a systematic way that manages hardware complexity.
Solution Approach 2:
Hardware parameters such as the size and structure of the base matrix can be changed to optimize for different throughput requirements. By adjusting the permutation parameters and base matrix dimensions, the system can achieve high parallelism and throughput while managing hardware complexity through parameter optimization rather than fundamental structural changes.
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.