Blind Iterative Equalizer Setting for Test Instruments
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Solution Overview
Problem
Existing equalizer technologies in test and measurement instruments struggle with small or absent eyes in eye diagrams, particularly in bad channels, necessitating improved signal equalization methods.
Innovation Solution
A blind and iterative method and system for setting an equalizer, involving presetting with default settings, filtering, symbol detection, and iterative adjustment based on detected symbols, without requiring a training sequence or de-embedding, to achieve optimized equalization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional equalizer methods (including training sequence-based methods) are used, then equalization can be performed, but the eyes in eye diagrams remain small or absent in bad channels
Solution Approach 1:
The patent implements a feedback mechanism where the equalizer settings are iteratively adjusted based on the detected symbols and the resulting eye diagram quality. The system continuously monitors the eye diagram and uses this information to refine the equalizer parameters, creating a closed-loop optimization process that progressively improves eye opening in bad channels
Solution Approach 2:
The equalizer settings are made dynamic through iterative adjustment rather than being fixed. The system adapts the equalizer parameters in real-time based on the actual signal conditions and detected symbols, allowing the equalization performance to evolve and improve throughout the communication process
2Ease of manufacture
If training sequences are used for equalizer setting, then equalization can be initialized, but the method requires de-embedding and prior knowledge of input symbols
Solution Approach 1:
The patent extracts and removes the training sequence requirement from the equalization process. Instead of relying on predefined training sequences that need de-embedding, the system directly processes the actual signal symbols, eliminating the need for separate training phase and reducing overall processing complexity
Solution Approach 2:
The equalizer system performs self-optimization by automatically adjusting its own parameters based on the detected symbols and eye diagram quality. The system serves itself by using the actual signal data to refine its equalization settings without requiring external training sequences or manual configuration
Data Source
AI summary
Embodiments of the present disclosure relate to a method of setting an equalizer for a test and/or measurement instrument. The equalizer is preset with pre-defined settings. The input signal is filtered by the equalizer, thereby obtaining an equalized signal. Symbols are detected by processing the equalized signal. The equalizer is set based on the detected symbols. The step of filtering the input signal, the step of detecting symbols, and the step of setting the equalizer are repeated at least once. Further, embodiments of the present disclosure relate to a system for determining a setting of an equalizer to be set.