Encoding Matrix Selection for Short Code Blocks in MCS-Based Communication
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Solution Overview
Problem
Current communication systems face challenges in efficiently determining the optimal encoding matrix type for encoding sequences, leading to increased decoding delays and reduced decoding performance, particularly in systems with varying sequence lengths and modulation and coding schemes (MCS) indexes.
Innovation Solution
A communication method that determines the encoding matrix type based on the length of the sequence and MCS index, using a correspondence table to select the appropriate matrix type, thereby reducing decoding delays and improving performance by aligning MCS indexes and ensuring robust system operation.
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 encoding matrix type is dynamically selected based on the sequence length and MCS index. The system transitions from a static fixed matrix approach to a dynamic selection mechanism that adapts to different transmission conditions, thereby improving decoding performance without significantly increasing device complexity through standardized selection criteria.
Solution Approach 2:
The selection of encoding matrix type is based on changing parameters (sequence length and MCS index). By using these variable parameters to determine the appropriate matrix type, the system optimizes decoding performance for different transmission scenarios while maintaining a manageable complexity through predefined selection rules.
2Device complexity
If the encoding matrix type is determined without considering sequence length and MCS index, then device complexity is reduced, but decoding delay increases
Solution Approach 1:
The system performs preliminary determination of the encoding matrix type based on the sequence length and MCS index before the actual decoding process. This advance selection, guided by predefined correspondence relationships, eliminates the need for complex real-time analysis during decoding, thereby reducing decoding delay while maintaining manageable device complexity.
3Reliability
If different encoding matrix types are used for different sequence lengths and MCS indexes, then decoding performance is improved, but device complexity increases
Solution Approach 1:
The system uses specific parameters (sequence length and MCS index) to determine the encoding matrix type. By establishing predefined correspondence relationships between these parameters and matrix types, the system achieves optimized decoding performance for different transmission conditions while controlling device complexity through systematic selection criteria rather than arbitrary choices.
Data Source
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 associated with the encoding matrix type. According to the application, the encoding matrix type can be properly selected for encoding.