SerDes Equalizer Initialization Using Centroid-Based Parameter Search
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Solution Overview
Problem
Existing digital communication systems face challenges in reducing convergence time for equalizer parameter initialization due to channel non-idealities, noise, and variations from process, voltage, and temperature changes, which affect the accuracy and efficiency of symbol detection.
Innovation Solution
Implementing a discrete-time, finite impulse response (FIR) filter and a decision element with a controller that estimates equalizer performance for multiple parameter values, finds a centroid value, and derives an initial parameter from this centroid to reduce convergence time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If adaptive equalization is used to cope with PVT variations and channel changes, then the equalizer can adapt to different conditions, but the convergence time increases
Solution Approach 1:
The patent applies preliminary action by initializing equalizer parameters using centroid values calculated from performance measurements taken at multiple predetermined parameter values. This pre-initialization step positions the equalizer closer to optimal parameters before adaptive equalization begins, thereby reducing the convergence time required for the equalizer to adapt to channel conditions and PVT variations.
2Loss of time
If the equalizer parameters are initialized near ideal values, then the convergence time is reduced, but the complexity of the initialization process increases
Solution Approach 1:
The patent performs preliminary measurements of equalizer performance at multiple predetermined parameter values and calculates centroid values to establish initial parameter estimates. This pre-computed initialization approach reduces convergence time while keeping the added complexity manageable through systematic measurement and calculation procedures.
Solution Approach 2:
The equalizer performs self-initialization by automatically measuring its own performance at different parameter values and calculating appropriate initial parameter values without requiring external calibration equipment or complex manual setup. This self-service approach reduces initialization complexity while achieving fast convergence.
3Adaptability or versatility
If the search range for parameter optimization is widened to account for PVT variations, then the equalizer becomes more robust to variations, but the time required to find optimal parameters increases
Solution Approach 1:
The patent performs preliminary performance measurements at multiple predetermined parameter values that span a wide range to account for PVT variations. By calculating centroid values from these broad-range measurements, the system establishes initial parameters that are robust to variations while avoiding the need to search the entire wide range during adaptive equalization, thus reducing the actual optimization time.
Data Source
AI summary
Serializer/deserializer (SerDes) modules, equalizers, and equalization techniques having robust parameter initialization may substantially reduce convergence time. One illustrative equalizer includes: a discrete-time, finite impulse response (“FIR”) filter to convert a receive signal to a filtered signal; a decision element to determine channel symbols represented by the filtered signal; and a controller. The controller is configured to, for each of multiple values in a search range, estimate a performance of the equalizer based on the channel symbols and at least one of the filtered signal or an input signal to the decision element; configured to find a centroid value based on the performance for each of the multiple parameter values in the search range; and configured to derive an initial value for the parameter from the centroid value.