Data Storage Channel Configuration Using Mutual Information for ISI
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Solution Overview
Problem
Existing data storage device configurations rely on bit error rate (BER) metrics, which require recalibration for changes in conditions like ECC code rate and linear density, and are inaccurate in systems with inter-symbol interference (ISI).
Innovation Solution
Utilize mutual information metrics based on multi-bit symbol sizes to optimize channel circuit configurations, including error correction and modulation codes, track and bit densities, and signal processing filters, to compensate for ISI and improve reliability and capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bit error rate (BER) metrics are used to configure channel circuits, then existing configuration methods can be maintained, but the configuration becomes inaccurate in systems with inter-symbol interference (ISI) and requires recalibration for changes in conditions
Solution Approach 1:
The patent changes the fundamental parameter used for configuration from bit error rate (BER) to mutual information metric. This parameter change enables accurate configuration in the presence of inter-symbol interference without requiring recalibration for different conditions such as ECC code rate and linear density changes.
2Measurement precision
If mutual information metrics based on multi-bit symbol sizes are used, then accuracy and adaptability to ISI improve, but calculation complexity increases
Solution Approach 1:
The patent replaces traditional BER measurement mechanisms with mutual information metric calculations. This substitution provides more accurate measurements that account for inter-symbol interference, with the mutual information metric capturing the relationship between input and output signals more effectively than BER.
Solution Approach 2:
The patent transitions from single-bit BER measurements to multi-bit symbol-based mutual information metrics. This dimensional change from bit-level to symbol-level analysis provides a more comprehensive view of signal quality and enables better configuration decisions that account for inter-symbol interference effects.
3Reliability
If recalibration is performed for changes in ECC code rate and linear density, then configuration accuracy can be maintained, but time and operational complexity increase
Solution Approach 1:
The mutual information metric serves as a universal configuration parameter that works across different ECC code rates and linear densities without requiring separate calibration procedures. This single metric adapts to various operating conditions inherently, eliminating the need for condition-specific recalibration.
Data Source
AI summary
Example systems, data storage devices, testers, and methods for storage device configuration using mutual information are described. A data storage device may include channel circuit configuration settings for the encoding and decoding of data written to a non-volatile storage medium. Mutual information metrics may be calculated based on a multi-bit symbol size to compensate for inter-symbol interference and compared to mutual information thresholds to determine the configuration settings, such as bit and track densities, error correction codes, and modulation codes. Mutual information metrics may be used to characterize heads and media independent of the configuration settings.