Adaptive Noise Predictive Filter Calibration for Low-Area Circuits
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data processing systems face challenges in achieving effective noise predictive filtering, which is often insufficient in converging to a corrected data stream and is costly in terms of area and power.
Innovation Solution
The implementation of data processing circuits that include a noise predictive filter circuit, a mean calculation circuit, a summation circuit, and a filter tap adaptation circuit, which perform noise predictive filtering by adapting filter taps based on input and sum outputs, and optionally include bias calculation and programmable tap gain values, to enhance noise predictive filtering efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noise predictive filtering is implemented using prior art circuits, then noise reduction capability is provided, but the circuit area and power consumption are excessive
Solution Approach 1:
The patent combines multiple functions (noise predictive filtering, mean calculation, summation, and filter tap adaptation) into an integrated circuit architecture. The filter tap adaptation circuit adaptively calculates filter taps based on input data and sum outputs, merging what would traditionally be separate calibration and filtering circuits into a unified structure that reduces overall area while maintaining noise reduction capability.
Solution Approach 2:
The patent implements adaptive filter tap calculation where the filter coefficients are dynamically adjusted based on the input data characteristics and sum outputs. This dynamic adaptation allows the circuit to optimize its performance for different noise conditions without requiring extensive fixed hardware for all possible scenarios, thereby reducing circuit area while maintaining effective noise reduction.
2Object-affected harmful factors
If noise predictive filtering is implemented using prior art circuits, then noise reduction capability is provided, but power consumption is excessive
Solution Approach 1:
The adaptive filter tap calculation dynamically adjusts filtering parameters based on actual noise conditions rather than using fixed, over-engineered hardware. This dynamic approach allows the circuit to consume only the necessary power for the current noise level, avoiding the continuous high power consumption of prior art circuits that maintain fixed calibration parameters.
Solution Approach 2:
The filter tap adaptation circuit automatically adjusts filter coefficients based on input data and sum outputs without requiring external calibration or control circuits. This self-adapting mechanism eliminates the need for additional power-consuming calibration circuits and manual adjustment mechanisms present in prior art systems.
3Productivity
If simple data detection and decoding is performed, then processing speed is maintained, but convergence to corrected data stream is insufficient
Solution Approach 1:
The patent implements a feedback mechanism where the filter tap adaptation circuit uses sum outputs (which represent error signals) to continuously adjust filter taps. This feedback loop enables the system to converge on the correct data stream by iteratively reducing errors, while the adaptive nature maintains processing speed by avoiding exhaustive error correction procedures.
Data Source
AI summary
Various embodiments of the present invention provide systems and methods for data processing. As an example, a data processing circuit is discussed that includes: a noise predictive filter circuit, a mean calculation circuit, a summation circuit, and a filter tap adaptation circuit. The noise predictive filter circuit is operable to perform a noise predictive filtering process on a data input based upon a selector input to yield a noise predictive output. The selector input is derived from a data detector output. The mean calculation circuit is operable to average two or more instances of the noise predictive output to yield a mean output. The summation circuit is operable to subtract the mean output from the noise predictive output to yield a sum output. The filter tap adaptation circuit is operable to adaptively calculate a filter tap based at least in part on a value derived from the data input and a value derived from the sum output.