Channel Quality Determination via Mean Squared Error Calculation
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Solution Overview
Problem
Existing data processing systems require significant time and resources to identify optimal modifiable variables, leading to increased manufacturing costs due to the need for known data patterns and error rate monitoring.
Innovation Solution
A data processing system comprising a data detector circuit, filter circuit, and mean squared calculation circuit that calculates a quality indicator based on the mean squared error value, allowing for the adaptive tuning of parameters to improve processing performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If known data patterns are provided to the data processing circuitry and error rate is monitored while modifiable variables are changed, then optimal parameters can be identified, but storage area is consumed and manufacturing time is increased
Solution Approach 1:
The patent extracts the parameter optimization process from the manufacturing phase and moves it to the operational phase. Instead of tuning parameters during manufacturing using known data patterns, the system uses actual received data patterns during normal operation to automatically adjust parameters, eliminating the need for time-consuming manufacturing characterization.
Solution Approach 2:
The data processing system performs self-tuning by automatically monitoring its own performance using actual received data and adjusting parameters without external intervention. The system monitors error rates and adjusts modifiable variables based on real operational data, enabling autonomous optimization during normal operation rather than requiring manual manufacturing tuning.
2Manufacturing precision
If known data patterns are provided to the data processing circuitry and error rate is monitored while modifiable variables are changed, then optimal parameters can be identified, but manufacturing costs are increased
Solution Approach 1:
The patent extracts the parameter optimization process from the manufacturing phase and moves it to the operational phase. Instead of tuning parameters during manufacturing using known data patterns, the system uses actual received data patterns during normal operation to automatically adjust parameters, eliminating the need for time-consuming manufacturing characterization.
Solution Approach 2:
The data processing system performs self-tuning by automatically monitoring its own performance using actual received data and adjusting parameters without external intervention. The system monitors error rates and adjusts modifiable variables based on real operational data, enabling autonomous optimization during normal operation rather than requiring manual manufacturing tuning.
3Productivity
If modifiable variables are changed to improve processing performance, then processing efficiency can be enhanced, but time is required to identify acceptable values
Solution Approach 1:
The patent implements continuous parameter optimization during normal data processing operations. Instead of discrete parameter tuning sessions, the system continuously monitors error rates and adjusts modifiable variables in real-time as data is received, making the optimization process an ongoing activity that occurs during productive operations rather than requiring separate time for identification.
Solution Approach 2:
The data processing system performs self-tuning by automatically monitoring its own performance using actual received data and adjusting parameters without external intervention. The system monitors error rates and adjusts modifiable variables based on real operational data, enabling autonomous optimization during normal operation rather than requiring manual manufacturing tuning.
Data Source
AI summary
Various embodiments of the present invention provide systems and methods for data processing. For example, a data processing system is disclosed that includes: a data detector circuit, a filter circuit, and a mean squared calculation circuit. The data detector circuit is operable to apply a data detection algorithm to a data set to yield a detected output. The filter circuit is operable to filter the detected output to yield a filtered output. The mean squared calculation circuit is operable to calculate a mean squared error value based at least in part on the data set and the filtered output. A quality indicator is generated at least in part on the mean squared error value.