LDPC Base Graph Structure for Flexible 5G Code Lengths
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Solution Overview
Problem
Existing LDPC code systems face challenges in supporting encoding and decoding of information bit sequences of varying lengths and meeting flexible code length and code rate requirements in communication systems.
Innovation Solution
The proposed solution involves using a specific structure for the LDPC matrix, comprising submatrices A, B, C, and D, with a base graph that includes a bi-diagonal structure and orthogonal rows, and utilizing lifting factors to adjust the matrix dimensions, allowing for encoding and decoding of sequences of different lengths and code rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed LDPC matrix structure is used, then the decoding complexity is low, but the system cannot support information bit sequences of various lengths and flexible code rate requirements
Solution Approach 1:
The LDPC matrix is divided into multiple submatrices (first submatrix, second submatrix, third submatrix, fourth submatrix) with specific structures. This segmentation allows flexible configuration of code lengths and rates by selectively using different submatrix combinations, while each submatrix maintains a manageable structure for efficient decoding.
Solution Approach 2:
The patent employs a dynamic base graph configuration where the LDPC matrix structure can be adapted based on the information bit sequence length and desired code rate. The base graph includes parameters that can be adjusted to generate different matrix dimensions, enabling the system to dynamically match various communication requirements without fixed structure limitations.
2Adaptability or versatility
If the LDPC matrix is expanded to support various code lengths, then the versatility improves, but the decoding complexity increases
Solution Approach 1:
Different submatrices within the LDPC matrix have specialized local structures optimized for specific functions. The first and second submatrices have different structures from the third and fourth submatrices, allowing each region to contribute efficiently to the overall decoding process while supporting variable code lengths through localized structural properties.
3Device complexity
If a sparse check matrix structure is used, then the decoding complexity is reduced, but the ability to meet flexible code rate requirements is limited
Solution Approach 1:
The base graph structure serves multiple functions by enabling the generation of LDPC matrices for various code rates and lengths through parameter adjustment. The same base graph framework can produce different matrix configurations, making the decoding apparatus universally applicable to multiple code rate requirements while maintaining the sparse structure benefits.
Data Source
AI summary
A low density parity check (LDPC) channel encoding method is used in a wireless communications system. A communication device encodes an input bit sequence by using an LDPC matrix, to obtain an encoded bit sequence for transmission. The LDPC matrix is obtained based on a lifting factor Z and a base matrix. The base matrix may be one of eight exemplary designs. The encoding method can be used in various communications systems including fifth generation (5G) telecommunication systems, and can support various encoding requirements for information bit sequences with different code lengths.