Grouped Signal Encoding Using Reference and Difference Values
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Solution Overview
Problem
Current signal processing techniques face limitations in maximizing transmission efficiency, particularly in complex communication environments, where existing methods do not fully optimize data coding and decoding for efficient data transmission.
Innovation Solution
The proposed solution involves an apparatus and method for signal processing that uses grouping techniques to obtain group reference values and difference values, allowing for efficient data coding and decoding, specifically employing pilot-based coding (PBC) and differential coding (DIFF) schemes to optimize data transmission efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional signal processing techniques are used, then basic transmission is achieved, but transmission efficiency cannot be maximized in complex communication environments
Solution Approach 1:
The patent divides signal processing into separate functional modules: grouping unit (dividing parameters into groups), reference value determination unit (selecting pilot parameters as references), difference calculation unit (computing differences between parameters and references), and encoding unit (entropy encoding the differences). This segmentation allows each module to perform its function independently, improving transmission efficiency while managing complexity through modular design.
Solution Approach 2:
The patent transforms the original signal parameters into difference values relative to pilot parameters. By changing the parameter representation from absolute values to relative differences, the encoding efficiency is improved because difference values typically have smaller magnitudes and better statistical properties for entropy coding, thereby maximizing transmission efficiency.
2Productivity
If data is coded without grouping techniques, then coding process is simpler, but data compression and recovery efficiency is reduced
Solution Approach 1:
The patent segments parameters into multiple groups based on their characteristics and relationships. Within each group, a pilot parameter is selected as reference, and other parameters are encoded as differences from this pilot. This grouping strategy enables efficient compression by exploiting local correlations within groups while keeping the decoding process systematic and manageable.
Solution Approach 2:
The patent introduces pilot parameters as intermediary reference values that mediate between the original parameters and their encoded representations. These pilot parameters serve as intermediaries that capture the essential characteristics of each group, allowing other parameters to be efficiently represented as deviations from these intermediaries, thereby improving coding efficiency without excessive complexity.
3Productivity
If pilot-based coding and differential coding schemes are employed, then transmission efficiency is optimized, but the processing and decoding complexity increases
Solution Approach 1:
The patent divides the processing into distinct sequential stages: grouping parameters, selecting pilots, calculating differences, and entropy encoding. The decoding mirrors this structure by reversing the operations in sequence. This segmentation makes the complex process more manageable and easier to implement, as each stage can be independently optimized and debugged.
Solution Approach 2:
The patent employs entropy encoding which is inherently adaptive to the statistical properties of the difference values. The encoding scheme automatically adjusts to the characteristics of the data being encoded, reducing the need for manual parameter tuning and making the system easier to operate while maintaining high transmission efficiency.
Data Source
AI summary
An apparatus for processing a signal and method thereof are disclosed. 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 through grouping and a difference value corresponding to the group reference value and obtaining the data using the group reference value and the difference value.