QC-LDPC Channel Coding with Block Size Grouped Parity Matrices
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Solution Overview
Problem
Current LDPC encoding techniques face limitations in supporting various input lengths and code rates, particularly in designing parity-check matrices that maintain excellent performance and flexibility for diverse communication systems, including 5G networks, where high data throughput and reliability are crucial.
Innovation Solution
The development of a method and apparatus for LDPC encoding/decoding using quasi-cyclic low-density parity-check (QC-LDPC) codes, which employ a lifting method to generate parity-check matrices with various lengths from a given exponent matrix, allowing for flexible code design and improved error floor characteristics, while also simplifying the implementation by dividing block sizes into groups with appropriate granularity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed parity-check matrix is used for LDPC encoding, then the encoding structure is simple, but the code cannot support various input lengths and code rates
Solution Approach 1:
The parity-check matrix is segmented into multiple sub-matrices with specific structures (e.g., identity matrices, zero matrices, and circulant matrices). This segmentation allows the overall matrix to support various code rates and lengths by selectively activating different segments, while each segment maintains a simple structure for efficient encoding.
Solution Approach 2:
The proposed parity-check matrix design uses a universal structure that can generate multiple code rates and code lengths from a single base matrix. By applying column selection and row selection to the base matrix, the system can adapt to different input lengths and code rates without requiring separate matrices for each configuration.
2Adaptability or versatility
If the parity-check matrix is designed to support various code lengths, then the flexibility increases, but the cycle characteristics and error floor performance deteriorate
Solution Approach 1:
Different segments of the parity-check matrix are designed with different local structures optimized for specific functions. Identity matrix segments provide good cycle characteristics, while circulant matrix segments enable flexibility for various code lengths. Each local segment contributes to overall reliability while the combination provides adaptability.
Solution Approach 2:
The parity-check matrix structure incorporates dynamic elements such as circulant matrices with shift parameters that can be adjusted based on the desired code length. This dynamic structure allows the matrix to adapt to different block sizes while maintaining good cycle characteristics through proper parameter selection.
3Productivity
If LDPC codes are designed for high data throughput, then the coding gain improves, but the system complexity increases
Solution Approach 1:
The encoding process is segmented into systematic steps that process data in manageable blocks. The parity-check matrix is divided into segments that can be processed independently, enabling parallel computation and improving throughput while keeping each processing unit relatively simple.
Solution Approach 2:
The system uses parameter changes in the parity-check matrix (such as column selection vectors and row selection vectors) to adapt the coding scheme for different throughput requirements. By changing these parameters, the system can optimize coding gain for high throughput scenarios without fundamentally changing the overall encoding structure.
Data Source
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AI summary
The present disclosure relates to a pre-5th-Generation (5G) or 5G communication system to be provided for supporting higher data rates Beyond 4th-Generation (4G) communication system such as Long Term Evolution (LTE). An apparatus and a method for channel encoding and decoding in a communication or broadcasting system is provided. According to the present disclosure, the method for channel encoding in a communication or broadcasting system includes determining a block size Z, and performing encoding based on the block size and a parity check matrix corresponding to the block size, in which the block size is included in any one of the plurality of block size groups and the parity check matrix is different for each block size group.