Multi-Dimensional Distortion Compensator With Fast Adaptive Calibration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing techniques for modeling and reducing distortion in electronic components like analog-to-digital converters and RF power amplifiers require significant processing resources and are slow to adapt to changing environments, such as frequency-hopping systems, due to complex calibration methods and high power consumption.
Innovation Solution
A multi-dimensional compensator that uses various functions of the input signal, including delay, derivative, integral, and statistical functions, to accurately model distortion mechanisms with minimal processing resources, allowing for fast adaptive updates and reduced power consumption by indexing correction values in memory and using simple arithmetic for error averaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If polynomial nonlinear models or Volterra filters are used to model distortion, then distortion compensation accuracy is improved, but processing requirements and power consumption increase significantly
Solution Approach 1:
The distortion compensation function is segmented into multiple lookup tables, each storing correction values for specific combinations of input signal characteristics (amplitude, frequency, phase). This segmentation allows the system to retrieve pre-computed correction values instead of performing complex real-time calculations, significantly reducing power consumption while maintaining compensation accuracy.
Solution Approach 2:
Correction values are pre-calculated and stored in lookup tables during a calibration phase before actual operation. The system performs the computationally intensive distortion modeling work in advance, then simply retrieves pre-computed correction values during normal operation, eliminating the need for real-time complex calculations and reducing power consumption.
2Measurement precision
If adaptive background calibration is used to update distortion models, then compensation accuracy is improved, but convergence speed is slow and processing requirements remain high
Solution Approach 1:
The system performs adaptive calibration in the background during normal operation, continuously updating lookup tables with newly calculated correction values. This preliminary background processing allows the system to adapt to changing conditions without interrupting normal operation and without requiring high-speed real-time processing, thus improving convergence speed while maintaining accuracy.
Solution Approach 2:
The adaptive calibration process operates continuously in the background during normal system operation, constantly updating correction values as new data becomes available. This continuous background processing eliminates the need for separate calibration phases and allows the system to adapt rapidly to changing environmental conditions while maintaining uninterrupted service.
3Measurement precision
If complex adaptive algorithms like gradient descent or recursive least squares are used for calibration, then compensation accuracy is improved, but processing complexity and power consumption increase
Solution Approach 1:
The complex calibration process is segmented into discrete steps that update lookup tables incrementally. Instead of performing complex matrix operations on the entire dataset at once, the system processes data in smaller chunks and updates correction values for specific lookup table entries, reducing processing complexity while maintaining accuracy.
Solution Approach 2:
The system uses simple arithmetic operations (addition, subtraction, multiplication) for updating correction values instead of complex adaptive algorithms. These computationally inexpensive operations are performed repeatedly on individual lookup table entries, achieving the same calibration effect as complex algorithms but with much lower processing complexity and power consumption.
4Use of energy by moving object
If static memory tables are used for distortion correction, then processing resources and power consumption are reduced, but performance degrades over frequency, time, temperature, and power level
Solution Approach 1:
The lookup tables are extended from simple amplitude-based correction to multi-dimensional tables that account for additional parameters such as frequency, temperature, and power level. By adding these dimensions, the system can retrieve correction values that are specific to the current operating conditions, maintaining high performance across varying parameters while still using efficient table lookup instead of complex real-time calculations.
Solution Approach 2:
The lookup tables are made dynamic through background updates that continuously refresh correction values as new operating conditions are encountered. This allows the static table structure to adapt to changing environmental conditions over time, maintaining performance across frequency, temperature, and power level variations while preserving the low-power benefits of table lookup.
Data Source
AI summary
The present invention is a computationally-efficient compensator for removing nonlinear distortion. The compensator operates in a digital post-compensation configuration for linearization of devices or systems such as analog-to-digital converters and RF receiver electronics. The compensator also operates in a digital pre-compensation configuration for linearization of devices or systems such as digital-to-analog converters, RF power amplifiers, and RF transmitter electronics. The multi-dimensional compensator effectively removes linear and nonlinear distortion in these systems by accurately modeling the state of the device by tracking multiple functions of the input, including but not limited to present signal value, delay function, derivative function (including higher order derivatives), integral function (including higher order integrals), signal statistics (mean, median, standard deviation, variance), covariance function, power calculation function (RMS or peak), or polynomial functions. The multi-dimensional compensator can be adaptively calibrated using simple arithmetic operations that can be completed with low processing requirements and quickly to track parameters that rapidly change over time, temperature, power level such as in frequency-hopping systems.