Adaptive Signal Equalization Without Training Patterns for Severe ISI
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Solution Overview
Problem
Conventional equalization techniques require a predetermined training pattern to determine optimal equalization coefficients, which increases complexity, especially in electronic test equipment, and are ineffective in severe intersymbol interference (ISI) scenarios.
Innovation Solution
A system and method to dynamically determine equalization coefficients without using a predetermined training pattern by measuring maximum voltage differences at different sampling intervals, approximating the step response of ISI, and calculating coefficients to remove distortion from data signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a predetermined training pattern is used to determine equalization coefficients, then the equalization process can be implemented, but the complexity of the training process increases
Solution Approach 1:
The patent extracts and removes the requirement for predetermined training patterns from the equalization process. Instead of using external training sequences, the system determines equalization coefficients directly from the received data signal itself, eliminating the complex training phase while maintaining coefficient determination accuracy
Solution Approach 2:
The system enables the received signal to determine its own equalization coefficients without external assistance. The equalization coefficients are derived from the signal's own characteristics (eye diagram parameters, voltage levels, timing information) rather than from separate training sequences, making the signal self-sufficient for its own equalization
2Reliability
If conventional training algorithms are used, then equalization coefficients can be determined, but the method is ineffective in severe intersymbol interference scenarios
Solution Approach 1:
The patent implements a dynamic approach where equalization coefficients are continuously adapted based on real-time signal characteristics. The system uses ongoing measurements of eye diagram parameters and signal voltage levels to update coefficients, allowing it to adapt to severe and varying ISI conditions rather than relying on static training patterns
Solution Approach 2:
The system incorporates feedback mechanisms where the received signal quality is continuously monitored and used to adjust equalization coefficients. By measuring eye opening, voltage levels, and timing parameters from the actual received signal and feeding this information back into the coefficient determination process, the system effectively handles severe ISI that would defeat conventional open-loop training methods
Data Source
AI summary
A system for filtering a data signal includes an input configured to receive the data signal through a transmission medium and a filter configured to remove distortion from the received data signal using equalization coefficients. The system further includes a processing unit configured to determine dynamically the equalization coefficients of the filter without using a predetermined training pattern in the received data signal.