LDPC Encoder Matrix Layout for Parallel Parity Generation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing LDPC encoding processes have high calculation complexity, particularly in the encoding phase, which limits processing rate and efficiency, especially when generating parity symbol sequences, and are not well-suited for parallel processing due to sequential calculation requirements.
Innovation Solution
The proposed encoding apparatus reduces calculation complexity by structuring the parity check matrix with specific submatrices, including a lower triangular matrix and sparse matrices, allowing for the generation of parity symbol sequences in a way that facilitates parallel processing, and optimizing the structure to enhance encoding rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If LDPC encoding is performed by multiplying data symbol sequence with generator matrix, then encoding can be realized, but calculation complexity becomes order O(n2) which is too high
Solution Approach 1:
The parity check matrix H is segmented into submatrices with specific structures (lower triangular matrix Q, diagonal matrix R, and zero matrix S). This segmentation allows the encoding process to be divided into independent parallel operations, reducing calculation complexity from O(n2) to O(n) while maintaining encoding functionality.
Solution Approach 2:
The patent changes the structural parameters of the parity check matrix by enforcing specific patterns (lower triangular structure for Q, diagonal structure for R). This parameter change enables the use of efficient algorithms that exploit the matrix structure, significantly reducing the computational burden of encoding operations.
2Productivity
If sequential calculation is used for encoding, then calculation can be performed, but processing rate is limited and parallel processing is not suitable
Solution Approach 1:
By segmenting the parity check matrix into independent submatrices (Q, R, S) with defined structures, the patent enables the encoding process to be split into parallel computational streams. Each submatrix operation can be performed simultaneously, making the system suitable for parallel processing architectures and significantly improving processing rate.
3Reliability
If general LDPC encoding method is used, then encoding can be performed, but calculation complexity is high which limits efficiency
Solution Approach 1:
The patent modifies the parameters of the parity check matrix by imposing specific structural constraints (lower triangular form for Q, diagonal form for R). These parameter changes maintain the error correction capabilities of LDPC codes while enabling more efficient encoding algorithms that reduce calculation complexity from O(n2) to O(n), thereby improving overall encoding efficiency.
Data Source
AI summary
According to one embodiment, an encoding apparatus includes an input unit and a generation unit. The input unit inputs a data symbol sequence containing q(N−J) symbols (q, J, and N are integers, N>J). The generation unit generates a codeword containing qN symbols by adding a parity symbol sequence containing qJ symbols to the data symbol sequence. The codeword satisfies parity check equations of a parity check matrix of qJ rows×qN columns. A first submatrix of qJ rows×qJ columns that corresponds to the parity symbol sequence in the parity check matrix includes a second submatrix. The second submatrix includes a first identity matrix of qL rows×qL columns (L is an integer, J>L) and a first non-zero matrix of q(J−L) rows×qL columns.