Differentiated Channel Coding for Mixed Semantic Data Transmission
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Solution Overview
Problem
Existing communication systems face limitations in maximizing data transmission rates due to channel capacity constraints and the inability to effectively handle data types that do not support semantic communication, leading to resource waste and inefficiencies.
Innovation Solution
Implement differentiated encoding for data types that do and do not support transmission error correction based on meaning, using distinct code rates to enhance reliability and efficiency, and provide indication information for accurate decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If differentiated encoding with different code rates is applied to first data and second data, then transmission efficiency is improved and resource waste is reduced, but device complexity increases
Solution Approach 1:
The transport block is segmented into first data (supporting semantic error correction) and second data (not supporting semantic error correction). Different encoding strategies are applied to each segment: first data uses higher code rate with semantic redundancy, while second data uses lower code rate with traditional redundancy, optimizing overall transmission efficiency
Solution Approach 2:
Different code rates are applied to different parts of the data based on their error correction capabilities. First data receives higher code rate (more redundancy) leveraging semantic error correction, while second data receives lower code rate (less redundancy) relying on traditional error correction, achieving localized optimization
2Productivity
If higher code rate is used for first data to improve transmission efficiency, then resource waste is reduced, but transmission reliability for second data deteriorates
Solution Approach 1:
The code rate parameter is changed based on data type: first data uses higher code rate (e.g., 0.5-0.75) to improve efficiency, while second data uses lower code rate (e.g., 0.25-0.5) to ensure reliability. This parameter adaptation resolves the contradiction between efficiency and reliability
3Productivity
If semantic communication technology is applied to all data types, then transmission rate is improved, but resource waste increases for data not supporting semantic correction
Solution Approach 1:
Semantic communication technology is applied partially only to first data that supports semantic error correction, rather than excessively applying it to all data types including second data. This partial application avoids generating unnecessary redundant data for incompatible data types, reducing resource waste while maintaining transmission rate benefits
Data Source
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AI summary
This application provides a data transmission method and a communication apparatus. The method includes: A first communication apparatus obtains first data and second data, where the first data supports transmission error correction based on a meaning represented by data, and the second data does not support transmission error correction based on a meaning represented by data. The first communication apparatus sends encoded data to a second communication apparatus, where the encoded data is obtained by encoding a transport block, the transport block includes the first data and the second data, a code rate of the first data is a first code rate, a code rate of the second data is a second code rate, and the first code rate is greater than the second code rate. In this way, data transmission efficiency can be improved, and a resource waste can be reduced.