Selective Signal Compression Using Data Distribution Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for determining whether to transmit signals in compressed form often require initial compression of a test signal, leading to resource waste and inability to resume the original state if compression is not applied, especially for non-compressible signals.
Innovation Solution
A method that determines whether a communication signal has a non-random distribution by applying accumulative statistics or counting symbol instances, allowing for efficient selection and application of a compression algorithm to convey the signal in its compressed form.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a compression algorithm is applied to determine compressibility by initially compressing a test signal, then compression effectiveness can be evaluated, but resource waste occurs and the original state cannot be resumed if compression is not applied
Solution Approach 1:
The patent applies preliminary analysis actions (counting symbol instances, applying accumulative statistics) to determine data compressibility before actually performing compression. This allows the system to evaluate whether compression is worthwhile without committing resources to full compression processing, thereby resolving the contradiction between accurate evaluation and resource waste.
Solution Approach 2:
The patent extracts only the essential information needed to determine compressibility (symbol frequency distributions, statistical patterns) without performing the full compression process. By taking out just the necessary diagnostic elements rather than the entire compression operation, the system achieves evaluation without resource waste.
2Productivity
If compression is applied to all signals to maximize bandwidth utilization, then transmission efficiency improves, but non-compressible signals consume unnecessary processing resources
Solution Approach 1:
The patent applies different processing qualities to different data segments based on their compressibility characteristics. Signals with non-random distributions (high compressibility) receive full compression processing, while signals with random distributions (low compressibility) are identified and transmitted without compression. This local differentiation resolves the contradiction between maximizing transmission efficiency and minimizing processing resource consumption.
Solution Approach 2:
The patent performs only the minimal necessary action (statistical analysis of symbol distribution) to determine compressibility, rather than applying full compression to all signals. This partial action approach allows the system to achieve efficient resource allocation by identifying compressible signals without the excessive processing cost of compressing everything.
3Reliability
If lossless compression is used to ensure exact reconstruction, then data integrity is maintained, but compression ratio is greatly reduced compared to lossy compression
Solution Approach 1:
The patent dynamically selects between lossless and lossy compression modes based on the measured compressibility of each signal. For signals with high compressibility (non-random distributions), lossless compression is applied to maintain data integrity. For signals with low compressibility (random distributions), the system may opt for lossy compression or no compression to avoid the penalty of poor compression ratios. This dynamic adaptation resolves the contradiction between data integrity and compression efficiency.
Data Source
AI summary
A method and apparatus are described for determining whether to convey a communication signal in a compressed form along a communication path. The method comprises the steps of: (i) providing the communication signal that should be conveyed along said communication path; (ii) determining whether at least part of the communication signal comprises data having a non-random distribution; (iii) if the at least part of the communication signal is determined to comprise data having at least partially a non-random distribution, applying a compression algorithm onto that at least part of the communication signal to form a compressed form of the communication signal provided; and (iv) conveying the communication signal in its compressed form along the communication path.