Weighted Data Averaging for Storage Retry Quality
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In storage devices, averaging retry processes face challenges in optimizing sample values for data recovery due to noise, head path differences, and signal sampling failures, leading to reduced data quality.
Innovation Solution
A storage device and controller system that performs weighted averaging of data read multiple times, with weights decreasing as data quality decreases, using a configuration that includes a read channel with buffers, filters, and quality detectors to calculate and apply weights based on status and quality information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If averaging retry is performed by reading sample values multiple times and calculating simple average, then noise reduction is achieved, but data quality deteriorates when sample values contain errors from head path deviations or sampling failures
Solution Approach 1:
The patent applies local quality by assigning different weights to different sample values based on their individual quality assessments. Instead of treating all sample values equally in the averaging process, the system evaluates each sample's quality metrics (such as signal-to-noise ratio, error correction status, and head positioning accuracy) and applies weighted averaging where high-quality samples contribute more to the final result while low-quality samples contribute less or are excluded entirely.
2Ease of operation
If all sample values are treated equally in averaging calculation, then processing simplicity is maintained, but recovery success rate decreases when some samples have poor quality
Solution Approach 1:
The patent changes the parameter of equal weighting to variable weighting based on quality metrics. The system introduces quality assessment parameters (such as signal strength, error rates, and sampling conditions) and uses these parameters to dynamically adjust the weight of each sample value in the averaging calculation. This transforms the simple averaging process into a quality-aware weighted averaging process that improves recovery success rate while maintaining reasonable processing complexity through automated quality evaluation.
Data Source
AI summary
According to one embodiment, in the case of rereading of data from a storage area of a storage is performed, data is read from the storage area a plurality of times, and a weighted average of pieces of the data read from the storage area the plurality of times is calculated, according to weights added to the pieces of data, as data reread from the storage area, in which the weights decreases as quality of the pieces of data read from the storage area decreases.