Protograph LDPC Parity-Check Matrix Layout for Low-Latency Decoding
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Solution Overview
Problem
Current wireless communication systems face challenges in achieving efficient low-density parity check (LDPC) coding for super ultra-reliable and low-latency communications, particularly in 5G wireless communication systems, where decoding delay and complexity are significant issues.
Innovation Solution
The method involves obtaining a protomatrix related to a protograph, generating permuted vectors based on weights and lifting factors, distributing these vectors to create lifted submatrices, and generating a base graph to produce a parity check matrix for LDPC coding, which maximizes parallelism in layered decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional LDPC coding methods are used in 5G wireless communication systems, then channel coding performance is achieved, but decoding delay and processing time increase
Solution Approach 1:
The parity check matrix is segmented into multiple submatrices through the lifting process, where each submatrix corresponds to a specific element of the protomatrix. This segmentation enables parallel processing during decoding operations, reducing overall decoding delay while maintaining the error correction performance of the complete LDPC code structure.
Solution Approach 2:
The patent transforms the one-dimensional parity check matrix into a two-dimensional structure through the lifting factor Z, creating a base graph that is then expanded into a larger parity check matrix. This dimensional transformation allows for optimized decoding algorithms that can process multiple bits simultaneously, reducing decoding time while preserving coding performance.
2Reliability
If conventional LDPC coding methods are used in 5G wireless communication systems, then channel coding performance is achieved, but processing complexity increases
Solution Approach 1:
By dividing the large parity check matrix into smaller submatrices through lifting, the patent enables modular processing where each submatrix can be handled independently or in parallel. This segmentation reduces the computational complexity of individual processing steps while maintaining the overall coding performance through the coordinated operation of all submatrices.
Solution Approach 2:
The patent employs dynamic permuted vectors that can be adapted based on the specific requirements of the communication scenario. The lifting factor and permuted vectors can be adjusted to balance between processing complexity and performance requirements, allowing the system to optimize its operation dynamically based on channel conditions and traffic patterns.
Data Source
AI summary
A method for performing low density parity check (LDPC) coding of a transmitter in a wireless communication system, according to the present disclosure, may comprise the steps of: acquiring a proto-matrix corresponding to a protograph; on the basis of weights and lifting factors of columns of the proto-matrix, acquiring one or more permuted vectors corresponding to each of the columns, a first permuted vector included in the one or more permuted vectors having been randomly generated; distributing the one or more permuted vectors for each row of a corresponding column; on the basis of the distributed one or more permuted vectors, acquiring a plurality of lifted sub matrices corresponding to a plurality of elements of the proto-matrix; generating a base graph on the basis of the plurality of lifted sub matrices; generating a parity check matrix (PCM) on the basis of the base graph; and performing LDPC coding by using the PCM.