Sparse Tap Adaptive Equalizer for Low-Distortion Channel Estimation
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Solution Overview
Problem
Conventional equalizers face challenges in reducing filtered signal distortion and chip size due to less precise channel estimation, which leads to unnecessary filtering coefficients being generated, causing distortion in output signals.
Innovation Solution
A sparse tap adaptive equalizer is introduced, which selectively enables coefficient buffers based on filtering coefficient values and determines coefficient values without using a comparator, incorporating a filtering circuit, filter control circuit, and coefficient updating circuit to optimize filtering coefficients and reduce chip size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional equalizers generate filtering coefficients for all taps, then channel estimation is performed, but signal distortion increases due to less precise estimation and unnecessary coefficients
Solution Approach 1:
The patent extracts and processes only the most significant bits (MSBs) of filtering coefficients, separating them from less significant bits. By focusing computational resources on MSBs that have greater impact on signal quality, the system achieves better channel estimation precision while avoiding the distortion caused by processing all coefficients equally.
Solution Approach 2:
The patent applies different processing quality to different parts of the filtering coefficients. MSBs are processed with higher precision and given more weight in channel estimation, while less significant bits receive reduced processing. This local quality differentiation improves overall estimation accuracy without the computational burden of uniform high-precision processing.
2Reliability
If all coefficient buffers are enabled in the filtering circuit, then complete filtering is achieved, but chip size increases
Solution Approach 1:
The patent segments the coefficient processing into two distinct parts: MSB processing and LSB processing. By dividing the coefficient buffer into segments that handle different bit significance levels, the system can selectively enable only necessary buffer segments, reducing chip area while maintaining filtering performance through intelligent segmentation of computational tasks.
Solution Approach 2:
The patent implements partial action by processing only the most significant bits of filtering coefficients rather than all bits. This partial processing approach maintains sufficient filtering performance for reliable operation while significantly reducing the number of active coefficient buffers needed, thereby minimizing chip size.
3Measurement precision
If conventional equalizers use comparators to determine coefficient values, then precise coefficient determination is achieved, but device complexity increases
Solution Approach 1:
The patent replaces the mechanical comparator-based determination system with a simplified logic circuit that directly processes MSBs. This substitution eliminates complex comparator hardware while maintaining coefficient determination precision through bitwise logic operations on the most significant bits, thereby reducing device complexity.
Solution Approach 2:
The patent changes the parameter being processed from full-precision coefficient values to only the most significant bits. By transforming the determination problem to work with reduced-parameter MSBs, the system achieves sufficient precision for coefficient determination without requiring complex comparator circuits, thus reducing overall device complexity.
4Reliability
If filtering coefficients with substantial zero values are still processed, then complete filtering is performed, but productivity decreases due to unnecessary calculations
Solution Approach 1:
The patent extracts and identifies coefficients with substantial zero values by examining MSBs first. By taking out these negligible coefficients from the processing pipeline, the system eliminates unnecessary calculations while maintaining filtering completeness for the significant coefficients, thereby improving processing efficiency without sacrificing reliability.
Solution Approach 2:
The patent applies partial action by performing filtering only on coefficients that have significant impact (non-substantial zero values). By avoiding excessive processing of negligible coefficients, the system maintains adequate filtering completeness for signal quality while significantly improving productivity through elimination of redundant calculations.
Data Source
AI summary
An equalizer may include, filter an input data signal based on a plurality of filtering coefficients, and outputs an output data signal, determine whether filtering coefficients satisfy a condition in response to a bit selection signal, and output the filtering control signals based on the determination result, and generate the filtering coefficients, estimate channels based on the input data signal and update the filtering coefficients based on the estimation results.