Pilot-Based Signal Coding with Hierarchical Data Grouping
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Solution Overview
Problem
Current signal processing techniques fail to maximize transmission efficiency, especially in complex communication environments, and there is a need for improved methods to efficiently code and decode data for enhanced audio recovery.
Innovation Solution
The method involves grouping data into pilot reference values and difference values through first and internal groupings in the frequency domain, using schemes like Pulse Code Modulation (PCM), Pilot Based Coding (PBC), and Differential Coding (DIFF), to optimize data coding and entropy coding, thereby enhancing transmission efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional signal compression techniques are used, then data can be compressed, but transmission efficiency is not maximized in complex communication environments
Solution Approach 1:
The patent divides frequency domain data into multiple groups (first grouping and internal grouping) with different group sizes. This segmentation allows different coding schemes to be applied to different groups, optimizing transmission efficiency for various data characteristics while adapting to complex communication environments.
Solution Approach 2:
The patent dynamically selects coding schemes (PCM, PBC, or DIFF) for different data groups based on their characteristics. This dynamic adaptation enables the system to optimize transmission efficiency for each group while maintaining versatility in complex communication environments.
2Productivity
If data is grouped into larger groups for coding, then coding efficiency improves, but the complexity of managing different group sizes increases
Solution Approach 1:
The patent implements a two-level grouping structure (first grouping and internal grouping) where larger groups are divided into smaller internal groups. This segmentation improves coding efficiency by allowing different coding schemes for different groups while managing complexity through a systematic hierarchical approach.
Solution Approach 2:
The patent applies coding schemes selectively to different groups based on their characteristics rather than uniformly to all data. This partial action approach improves coding efficiency for suitable groups while avoiding unnecessary complexity for groups where simpler schemes suffice.
Data Source
AI summary
Data coding and entropy coding are performed with interconnection, and grouping is used to enhance coding efficiency. The present invention includes the steps of obtaining a group reference value corresponding to a plurality of data included in one group and a difference value corresponding to the group reference value through first grouping and internal grouping for the first grouping and obtaining the data using the group reference value and the difference value.