ADC Non-Linearity Correction via Coefficient Transformation
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Solution Overview
Problem
Analog-to-digital converters (ADCs) face challenges in supporting multiple sampling rates due to increased memory requirements for non-linearity correction coefficients, limiting their ability to meet stringent harmonic distortion and intermodulation distortion specifications across a wide range of sampling rates.
Innovation Solution
A non-linearity correction system that stores coefficients for one sampling rate and transforms them using a matrix multiplication method to support any sampling rate, reducing memory needs and power consumption by applying fewer coefficients based on bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sets of non-linearity correction coefficients are stored for different sampling rates, then non-linearity correction accuracy is improved across various sampling rates, but memory requirements increase
Solution Approach 1:
A single set of non-linearity correction coefficients is designed to serve multiple sampling rates through mathematical transformation. The system uses a transformation matrix to adapt coefficients for different sampling rates, making the coefficient storage universal rather than rate-specific. This eliminates the need for separate coefficient sets for each sampling rate while maintaining correction accuracy.
Solution Approach 2:
The system changes the parameters of the correction coefficients through mathematical transformation when the sampling rate changes. Instead of storing different coefficients for different rates, the system transforms the existing coefficients using a transformation matrix that accounts for the sampling rate difference, thereby adapting the same coefficient set to multiple operating conditions.
2Reliability
If multiple sets of non-linearity correction coefficients are stored for different sampling rates, then correction performance across sampling rates is improved, but power consumption increases
Solution Approach 1:
The coefficient storage is designed to be universal, storing only one set of coefficients that can be transformed to serve multiple sampling rates. This reduces the total number of coefficients that need to be loaded and processed, thereby reducing power consumption while maintaining correction performance across different sampling rates.
Solution Approach 2:
The system extracts only the essential coefficient set and uses mathematical transformation to derive coefficients for different sampling rates. By extracting and reusing the core coefficient information rather than storing redundant copies, the system reduces memory access operations and associated power consumption while maintaining correction reliability.
3Quantity of substance
If a single set of non-linearity correction coefficients is stored, then memory requirements and power consumption are reduced, but the ability to meet distortion specifications across wide range of sampling rates is limited
Solution Approach 1:
The system compensates for the limitation of a single coefficient set by dynamically changing the coefficient parameters through mathematical transformation. When the sampling rate changes, the transformation matrix adjusts the coefficients accordingly, enabling the single stored set to adapt to a wide range of sampling rates while meeting distortion specifications.
Solution Approach 2:
A transformation matrix is introduced as an intermediary between the stored coefficient set and the actual correction process. This intermediary transforms the stored coefficients to match the current sampling rate requirements, enabling the system to achieve wide sampling rate adaptability without storing multiple coefficient sets.
4Adaptability or versatility
If transformation matrix multiplication is applied to generate coefficients for different sampling rates, then coefficient adaptability is improved, but computational complexity increases
Solution Approach 1:
The transformation matrix is pre-calculated and stored based on the relationship between different sampling rates. By performing the transformation matrix multiplication in advance and storing the results, the system reduces real-time computational complexity while maintaining coefficient adaptability for different sampling rates.
Data Source
AI summary
Circuitry for correcting non-linearity of an analog-to-digital converter. A non-linearity correction system for an analog-to-digital converter (ADC) includes coefficient storage, coefficient transformation circuitry, and correction circuitry. The coefficient storage is encoded with a first set of coefficients for correcting non-linearity of the ADC at a first sampling rate. The coefficient transformation circuitry is coupled to the coefficient storage. The coefficient transformation circuitry is configured to generate a second set of coefficients for correcting non-linearity of the ADC at a different sampling rate. The correction circuitry is configured to apply the second set of coefficients to correct non-linearity in output of the ADC while the ADC is operating at the different sampling rate.