MISO Equalizer Parameter Adaptation With Regularization
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Solution Overview
Problem
In multi-input single-output (MISO) equalizers, existing adaptation algorithms often result in parameter wandering due to ill-conditioning when input signals are similar, leading to performance loss during off-track reads, as standard algorithms fail to effectively penalize deviations from predetermined on-track parameters.
Innovation Solution
A regularized adaptation algorithm is employed, which penalizes deviations from predetermined channel parameters using a cost function that includes a regularization term, preventing parameter wandering by maintaining alignment with on-track adapted values, thereby stabilizing coefficients and improving read channel performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standard adaptation algorithms are used, then the system can adapt parameters dynamically, but parameter wandering occurs due to ill-conditioning when input signals are similar
Solution Approach 1:
The patent modifies the adaptation algorithm by changing the parameter update rule to include a regularization term. This term penalizes deviations from predetermined on-track parameters, effectively constraining the adaptation process to remain within a stable region while still allowing necessary adjustments for performance optimization.
Solution Approach 2:
The patent introduces a feedback mechanism where the adaptation algorithm continuously monitors parameter deviations and applies corrective penalties based on the regularization term. This feedback loop prevents parameter wandering by constantly steering parameters back toward their on-track values when deviations occur.
2Adaptability or versatility
If standard adaptation algorithms are used, then the system can track changing conditions, but performance loss occurs during off-track reads
Solution Approach 1:
The patent changes the parameter adaptation strategy by incorporating a regularization term that modifies the update rule. This ensures parameters remain close to optimal on-track values even when off-track conditions occur, preventing performance degradation while still allowing necessary adaptations.
Solution Approach 2:
The patent prepares for potential off-track conditions by pre-establishing on-track parameter values as reference points. The regularization term acts as a cushioning mechanism that prevents parameters from drifting too far from these reference values, thereby cushioning against performance loss during off-track reads.
3Productivity
If parameter adaptation is allowed freely, then the system can optimize for current conditions, but transient times to optimal conditions increase
Solution Approach 1:
The patent modifies the parameter update dynamics by adding a regularization term that constrains the rate and direction of parameter changes. This prevents excessive wandering during transients, allowing the system to reach optimal conditions faster while maintaining processing efficiency.
Solution Approach 2:
The patent applies preliminary anti-action by anticipating potential parameter wandering during transient periods. The regularization term preemptively counteracts deviations from on-track parameters, preventing unnecessary transient excursions and reducing the time to reach optimal conditions.
Data Source
AI summary
An apparatus may include a circuit configured to process at least one input signal using a set of channel parameters. The circuit may adapt, using a regularized adaptation algorithm, a first set of channel parameters for use by the circuit as the set of channel parameters in processing the at least one input signal, the regularized adaptation algorithm penalizing deviations by the first set of channel parameters from a corresponding predetermined second set of channel parameters. The circuit may then perform the processing of the at least one input signal using the first set of channel parameters as the set of channel parameters.