Broadband ADC Calibration for Nonlinearity and Self-Aliasing
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Solution Overview
Problem
Conventional broadband signal acquisition and analog-to-digital conversion technologies introduce errors and distortion due to nonlinearity in receiving systems, which affect the quality of digital signals.
Innovation Solution
A method and system for broadband analog-to-digital conversion that employs nonlinearity correction models and secondary subsampling to mitigate distortion, using training signals and isolation filtering to estimate and correct nonlinearity-related errors, and performs secondary subsampling to recover bands affected by self-aliasing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional analog-to-digital conversion is performed, then signal conversion is achieved, but distortion and errors are introduced due to system nonlinearity
Solution Approach 1:
The patent applies preliminary action by injecting training signals into unoccupied spectral regions before actual signal conversion. This allows the system to pre-characterize and store correction parameters for nonlinear distortion in those regions, which are then applied during actual operation to eliminate distortion in previously unoccupied bands.
Solution Approach 2:
The system implements feedback by measuring the actual output signal in unoccupied spectral regions, comparing it with expected values, and using this information to generate correction parameters. These correction parameters are fed back into the conversion process to compensate for nonlinear distortion, creating a closed-loop system that continuously improves accuracy.
2Adaptability or versatility
If broadband signal acquisition is performed, then spectral coverage is increased, but nonlinearity distortion in unoccupied regions deteriorates signal quality
Solution Approach 1:
The patent segments the broadband spectrum into occupied and unoccupied spectral regions. By treating these regions separately and applying specific correction techniques to unoccupied regions using training signals, the system maintains high reliability in both segments while achieving broad spectral coverage.
Solution Approach 2:
The system changes parameters by injecting training signals at specific power levels and frequencies into unoccupied spectral regions. This allows the system to characterize nonlinear distortion parameters specific to each unoccupied region and apply targeted correction, thereby maintaining signal quality across the entire broadband spectrum.
3Measurement precision
If nonlinearity correction calibration is performed using training signals, then distortion is reduced, but system complexity increases
Solution Approach 1:
The patent introduces training signals as an intermediary element that mediates between the nonlinear system and the measurement process. These training signals serve as a bridge to characterize system nonlinearity without requiring complex direct measurement methods, thereby reducing overall system complexity while maintaining high correction accuracy.
Solution Approach 2:
The system creates a digital copy or model of the nonlinear distortion characteristics by measuring responses to training signals. This copied distortion model is then used for correction without requiring physical modification of the system, simplifying the calibration process while achieving accurate nonlinearity compensation.
Data Source
AI summary
Nonlinearity correction in a device that performs analog-to-digital conversion on received analog signals, may be calibrated by generating correction-parameters estimation which when applied to the total spectral content reduces distortion resulting from said nonlinearity in originally-unoccupied spectral regions. Digital signals generated based on sampling of the received analog signals may then be corrected, to remove nonlinearity related distortion, based on the estimated correction-parameters. The nonlinearity calibration may be performed during reception and handling of said analog signals. The correction-parameters may be generated based on signals located in particular spectral regions, such as the originally-unoccupied spectral regions. These signals may be injected within the device, into the particular spectral regions, and the signal may have known characteristics to enable estimating the required correction.