LDPC Base Matrix Coding for Flexible Block Lengths
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Solution Overview
Problem
Existing communication systems face challenges in efficiently encoding and decoding information bit sequences of varying lengths, particularly in meeting flexible code length and code rate requirements.
Innovation Solution
The implementation of a low density parity check (LDPC) matrix with a base graph comprising submatrices A and B, along with optional submatrices C, D, and E, to support encoding and decoding of information bit sequences of various lengths and meet flexible code length and code rate requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a conventional turbo code is used for channel coding, then the decoding complexity is low, but the throughput is lower compared to LDPC code
Solution Approach 1:
The patent changes the fundamental parameters of the channel coding scheme by transitioning from turbo code to LDPC code with specific base graph configurations (27 columns, 5 rows). This parameter change enables higher throughput while maintaining acceptable decoding complexity through the sparse structure of the LDPC matrix and iterative decoding algorithm.
2Adaptability or versatility
If the LDPC matrix structure is fixed, then the encoding and decoding process is simple, but it cannot meet flexible code length and code rate requirements
Solution Approach 1:
The LDPC matrix is segmented into a base graph with 5 rows and 27 columns, which can be systematically expanded to support various code lengths and rates. This segmentation allows the matrix to be adapted to different communication requirements while maintaining a manageable base structure that simplifies implementation.
Solution Approach 2:
The patent implements a dynamic matrix structure where the base graph can be expanded and configured differently based on required code length and rate. This dynamic adaptability allows the same base structure to serve multiple coding scenarios, achieving flexibility without proportionally increasing complexity.
3Adaptability or versatility
If information bit sequences of various lengths are supported, then the communication system becomes more versatile, but the encoding and decoding efficiency decreases
Solution Approach 1:
The base graph with 5 rows and 27 columns serves as a universal structure that can handle information bit sequences of various lengths through systematic expansion. This multi-functional design allows a single base structure to efficiently support multiple code configurations, maintaining encoding and decoding efficiency across different sequence lengths.
Data Source
AI summary
This application relates to communicating information between communication devices. A channel coding method is disclosed. A communication device obtains an input sequence of K bits. The communication device encodes the input sequence using a low density parity check (LDPC) matrix H, to obtain an encoded sequence. The LDPC matrix His determined according to a base matrix and a lifting factor Z. The base matrix includes m rows and n columns, m is greater than or equal to 5, and n is greater than or equal to 27. The lifting factor Z satisfies a relationship of 22*Z≥K. According to the encoding method provided in the embodiments, information bit sequences of a plurality of lengths can be encoded for transmission between the communication devices.