Adaptive Error Slicer for Residual ISI in Sign/Sign Equalizers
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Solution Overview
Problem
Conventional zero-forcing decision-feedback equalizers (ZF-DFE) with sign/sign adaptation algorithms fail in the presence of strong residual intersymbol interference (ISI) due to a masking effect that destroys correlation between single-bit data and error signals, leading to ineffective tap weight adaptation and increased error performance.
Innovation Solution
Incorporating an adaptive error slicer and residual ISI correlators to estimate and subtract residual ISI terms, allowing the sign/sign algorithm to operate by modifying the error signal to retain sufficient correlation, thereby overcoming the 'dead zone' caused by residual ISI.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If sign/sign adaptation algorithm is used in conventional ZF-DFE, then device complexity is reduced, but reliability deteriorates in the presence of strong residual ISI due to masking effect
Solution Approach 1:
The patent introduces an intermediary error slicer between the data slicer and the adaptation algorithm. This error slicer generates a modified error signal that removes the masking effect of residual ISI, allowing the sign/sign algorithm to function reliably. The intermediary component transforms the corrupted error signal into a usable form without increasing overall system complexity significantly.
Solution Approach 2:
The patent changes the parameter being used for adaptation by modifying how the error signal is generated. Instead of using the raw error signal that contains residual ISI, the system uses an error signal conditioned by the error slicer that has removed or reduced the residual ISI component, thereby changing the effective parameter for adaptation from a corrupted signal to a cleaned signal.
2Device complexity
If conventional error slicer is used, then device complexity is low, but measurement precision deteriorates due to inability to estimate residual ISI
Solution Approach 1:
The error slicer acts as an intermediary component that processes the error signal to remove residual ISI. It takes the raw error signal containing residual ISI and produces a cleaned error signal that more accurately represents the true adaptation error, thereby improving measurement precision without adding significant complexity.
Solution Approach 2:
The error slicer uses feedback from the data decisions to adjust the error signal generation. By incorporating feedback about the detected data values, the error slicer can compensate for residual ISI effects and generate a more accurate error signal for adaptation purposes.
Data Source
AI summary
Conventional adaptive equalizers often use the “sign/sign” algorithm as a low complexity means to adjust their tap weight coefficients by driving the correlation between its single-bit “error” and “data” signals to zero. This algorithm fails in the presence of strong residual intersymbol interference (ISI), since this ISI renders the “error” signal sufficiently inaccurate to mask the correlation between “data” and “error”. Failure manifests itself two-fold as an inability to achieve tap weight acquisition at startup, and an inability to track dynamic channel conditions. The invention described herein employs an adaptive estimator to compute the residual masking ISI terms that in turn control an adaptive error slicer to synthesize a modified single-bit “error” signal that remains correlated with the “data” signal. By restoring this correlation between “error” and “data” using these two modifications, the “sign/sign” algorithm retains its acquisition and tracking capabilities in the presence of strong residual ISI.