Multi-Read Sample Combining for Failed Data Segment Recovery
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Solution Overview
Problem
Existing data storage systems face challenges in efficiently recovering data from failed segments due to errors, as they often rely on single-read samples and lack effective methods for iterative error correction, particularly in the presence of adjacent track interference and noise.
Innovation Solution
The implementation of a circuit that generates equalized combined samples for failed data segments by averaging first and second samples, and performs iterative outer code recovery using these samples, incorporating techniques like X-averaging and adjacent track interference cancellation to improve data recovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If single-read samples are used for data recovery, then the data recovery process is simple and fast, but the error correction capability is insufficient and reliability is low
Solution Approach 1:
The patent combines multiple read samples (first samples and second samples from different reads) to generate equalized combined samples for failed data segments. This merging of multiple samples improves the signal quality and error correction capability, thereby enhancing data recovery reliability while managing the increased processing complexity through systematic combination methods.
Solution Approach 2:
The patent performs preliminary actions by reading and storing multiple samples from adjacent tracks and data units before the actual data recovery process. These preliminary samples are processed in advance to create equalized combined samples, which are then used during iterative outer code recovery. This preliminary sampling and processing improves recovery reliability by having high-quality reference data ready before the critical recovery operation.
2Measurement precision
If multiple reads and adjacent track samples are used, then error correction capability improves, but processing time and computational complexity increase
Solution Approach 1:
The patent applies partial action by selectively using samples from adjacent tracks and data units only when needed for recovering failed segments. Instead of processing all possible samples uniformly, the system focuses computational resources on generating equalized combined samples specifically for failed data segments, thereby improving error detection precision while limiting unnecessary processing time expenditure.
Solution Approach 2:
The patent changes the parameter of sample quality by applying equalization processing to combine multiple samples. The equalization process optimizes the weighted combination of first samples and second samples based on their respective quality characteristics, improving measurement precision for error detection while managing processing time through parameter-optimized combination strategies.
3Reliability
If iterative outer code recovery is performed with equalized combined samples, then data recovery success rate increases, but computational complexity and processing overhead increase
Solution Approach 1:
The patent implements feedback mechanisms in the iterative outer code recovery process. The system performs multiple iterations where each iteration uses the results from the previous iteration to refine the recovery of failed data segments. The equalized combined samples from multiple reads provide feedback information that improves the success rate of data recovery, while the iterative process systematically manages computational complexity by building upon previous computational results.
Solution Approach 2:
The patent introduces equalized combined samples as an intermediary between the raw multiple read samples and the final data recovery result. These equalized combined samples serve as a mediator that consolidates information from multiple sources (first samples, second samples from adjacent tracks) into a unified, optimized form that facilitates the iterative outer code recovery process, thereby improving success rate while managing algorithmic complexity.
Data Source
AI summary
An apparatus may include a circuit that initializes a read operation to read one or more requested data segments of a respective data unit. The circuit may generate equalized combined samples for a failed data segment of the one or more requested data segments based on first samples and second samples. In addition, the circuit may perform iterative outer code recovery for the data unit utilizing the equalized combined samples as samples for the failed data segment.