LDPC Channel Coding for Flexible Code Length and Rate
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Solution Overview
Problem
Current channel coding methods, particularly in communication systems, face challenges in supporting flexible code length and code rate requirements, which limits their adaptability and performance in varying communication scenarios.
Innovation Solution
The implementation of a Low Density Parity Check (LDPC) code system with specific matrix structures, including submatrices A and B, and the use of lifting factors to generate base matrices that support different block lengths and code rates, enabling flexible encoding and decoding of information bit sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional channel coding methods are used, then the system structure is simple, but the system cannot support flexible code length and code rate requirements
Solution Approach 1:
The LDPC code is segmented into information bits and parity bits with distinct functional roles. The encoding process is divided into systematic encoding steps that separately handle information bit placement and parity bit generation, allowing independent optimization of each segment for different code lengths and rates
Solution Approach 2:
The LDPC encoder is designed with universal functionality to support multiple code lengths and code rates through a unified encoding framework. The same encoder structure can accommodate various communication scenarios by adjusting parameters such as the number of information bits, parity bits, and the specific LDPC matrix used, without requiring separate dedicated encoders for each configuration
2Reliability
If LDPC code with specific matrix structures is implemented, then encoding and decoding performance is improved, but implementation complexity increases
Solution Approach 1:
Different submatrices within the LDPC parity check matrix are assigned different structural properties optimized for their specific functions. For example, certain submatrices have cyclic structures that facilitate efficient encoding, while others have properties that enhance decoding convergence. This local optimization of matrix quality improves overall error correction performance without requiring the entire matrix to be uniformly complex
Solution Approach 2:
The LDPC matrix structure is designed to be dynamically adaptable to different communication requirements. The encoder can select from multiple pre-defined LDPC matrices with different densities and structures based on the desired code rate and block length, allowing the system to optimize performance for each specific scenario rather than using a fixed static matrix structure
3Loss of information
If systematic encoding is used, then information bit preservation is improved, but encoding process complexity increases
Solution Approach 1:
The systematic encoding process performs preliminary placement of information bits into their designated positions in the codeword before generating parity bits. This preliminary action ensures that information bits are preserved in their original form and position, making the encoding process straightforward and reducing the need for complex post-processing operations to recover or reconstruct information bits
Solution Approach 2:
Systematic encoding creates a copy of the information bits that are placed directly into the codeword structure. The information bits are effectively copied from the input sequence and positioned in the output codeword without transformation, while separate parity bit copies are generated and appended. This copying approach ensures information preservation while maintaining a relatively simple encoding process
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 H is 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.