Adaptive Converter Error Modeling for Nonlinearity Calibration
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Solution Overview
Problem
Existing data conversion systems, particularly in telecommunications, face errors due to non-linearities and process variations, which are costly to correct using traditional methods like randomization and self-calibration.
Innovation Solution
A model is developed to adaptively mitigate errors by generating an emulated error signal based on the output signal's frequency content, which is used to calibrate parameters and reduce errors in analog-to-digital and digital-to-analog converters through noise shaping and compensation systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional randomization techniques or trimming of analog components are used to correct component mismatches, then manufacturing precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent creates a digital copy of the analog component errors through an error model that captures mismatch characteristics. Instead of physically trimming components or adding complex analog correction circuits, the system digitally replicates the error behavior and uses this copy to generate compensation signals, thereby correcting mismatches without increasing analog device complexity
Solution Approach 2:
The patent replaces physical mechanical/analog correction methods (such as component trimming or analog compensation circuits) with a digital signal processing approach. The error model and compensation mechanism operate in the digital domain, substituting complex analog correction hardware with software-based error emulation and digital signal injection
2Measurement precision
If self-calibration techniques are employed to compensate for non-linearities, then measurement precision is improved, but device complexity and implementation difficulty increase
Solution Approach 1:
The patent creates a digital replica of the converter's non-linear error characteristics through an error model. This model copy captures the non-linear behavior and is used to generate compensation signals that counteract the actual non-linearities, achieving high measurement precision without requiring complex self-calibration hardware or algorithms
3Productivity
If adaptive model calibration is implemented to emulate error characteristics, then productivity is improved through reduced errors, but device complexity increases due to additional processing
Solution Approach 1:
The patent performs preliminary calibration to establish the error model parameters before actual conversion operations. During this initial phase, the system characterizes the converter's error characteristics and stores them in the error model. This preliminary action enables subsequent conversions to benefit from pre-computed compensation without requiring complex real-time adaptation during normal operation
Data Source
AI summary
An error model can be utilized to mitigate errors associated with a conversion system, such as an analog-to-digital or digital-to analog converter. The error model is adaptively calibrated to approximate error characteristics associated with at least a portion of the conversion system, such as a digital-to analog converter. The error model can be generated on-line during system operation or off-line to improve performance of various types of signal converters and systems using such signal converters.