LDPC Encoding Matrix Selection for Short Code Block Decoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current communication systems face challenges in efficiently determining the appropriate encoding matrix type for optimal decoding performance and system robustness, particularly in varying channel conditions and code block lengths.
Innovation Solution
A method is introduced to determine the encoding matrix type based on the length of a sequence and the Modulation and Coding Scheme (MCS) index, using a correspondence table to select between different encoding matrix types, thereby reducing decoding delay and improving performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed encoding matrix type is used for all sequence lengths, then device complexity is reduced, but decoding performance deteriorates
Solution Approach 1:
The patent changes the parameter of encoding matrix type based on the sequence length parameter. Different encoding matrix types (e.g., different base graphs in LDPC codes) are selected according to the length of the sequence to be encoded, optimizing decoding performance for different block sizes while maintaining manageable system complexity through standardized selection rules.
2Reliability
If different encoding matrix types are selected for different sequence lengths, then decoding performance is improved, but device complexity increases
Solution Approach 1:
The encoding matrix type is dynamically selected based on the sequence length parameter, allowing the system to adapt to different decoding performance requirements while maintaining a finite set of standardized matrix types for manageable complexity.
Solution Approach 2:
Different encoding matrix types are applied to different sequence length ranges, optimizing the local decoding performance for each specific length category rather than using a single universal matrix type for all lengths.
3Device complexity
If encoding matrix type is not properly selected, then device complexity is reduced, but system robustness deteriorates
Solution Approach 1:
The system robustness is improved by adapting the encoding matrix type parameter to match the sequence length parameter, ensuring optimal performance across varying channel conditions and block sizes while maintaining a standardized selection process.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Embodiments of this application disclose a communication method and a communications apparatus. The method includes: determining an encoding matrix type of a first sequence based on a modulation and encoding scheme MCS index, where the first sequence is obtained after code block segmentation is performed on a second sequence, a length of the second sequence is related to the MCS index, and a length of the first sequence is less than or equal to a first threshold; and encoding the first sequence based on the encoding matrix corresponding to the encoding matrix type. In the foregoing solution, the encoding matrix type can be properly selected for encoding.