Digital Pre-Distortion Sample Screening for Accurate Coefficient Estimation
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Solution Overview
Problem
Existing digital pre-distortion systems face challenges in accurately estimating pre-distortion coefficients for power amplifiers due to the need for large memory capacity and the inclusion of inappropriate samples, which degrades linearization performance and increases hardware and cost burdens.
Innovation Solution
A method and apparatus that determine the validity of samples using a low-capacity memory by classifying input samples into valid and invalid groups based on magnitude distribution, ensuring only valid samples are used to estimate pre-distortion coefficients, thereby preventing errors and optimizing linearization performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a sufficiently large number of samples are collected using a large-capacity memory, then the accuracy of pre-distortion parameter estimation is improved, but the hardware load and cost increase
Solution Approach 1:
The patent applies preliminary action by classifying samples into valid and invalid groups before estimation using magnitude distribution criteria. This pre-screening ensures that only valid samples enter the estimation process, eliminating the need to store and process excessive invalid samples, thus reducing memory capacity requirements while maintaining estimation accuracy.
Solution Approach 2:
The patent changes the parameter of sample selection from quantity-based to quality-based by introducing magnitude distribution criteria. Instead of collecting a large number of samples regardless of quality, the system evaluates sample validity based on magnitude distribution characteristics, allowing accurate estimation with fewer, higher-quality samples.
2Quantity of substance
If inappropriate samples are included in the collected samples, then the memory capacity requirement is reduced, but the accuracy of pre-distortion characteristics deteriorates
Solution Approach 1:
The patent transforms the sample selection criterion from quantity to quality by introducing magnitude distribution as a validity parameter. Samples are evaluated based on whether their magnitudes fall within expected distributions, ensuring that even with a limited number of samples, only those meeting quality standards are used for estimation.
Solution Approach 2:
The patent extracts valid samples from the collected sample set by applying magnitude distribution criteria. This extraction process separates valid samples (those with appropriate magnitude distributions) from invalid samples (such as zero-signal samples in TDD systems), ensuring that only the extracted valid samples are used for accurate pre-distortion characteristics estimation.
3Reliability
If the power amplifier is driven in a low-power level to operate with linear characteristics, then signal quality is improved, but the efficiency of the power amplifier is lowered by about 10% to 20%
Solution Approach 1:
The patent applies preliminary action through digital pre-distortion, which pre-compensates the input signal before it reaches the power amplifier. By calculating pre-distortion parameters based on valid samples and applying the inverse of the amplifier's nonlinear characteristics to the input signal, the system ensures that the amplifier operates efficiently at high power levels while the output remains linearized, thus improving efficiency without sacrificing signal quality.
Data Source
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AI summary
A method and an apparatus for determining validity of samples for a digital pre-distortion apparatus is disclosed. It is an object of at least one embodiment to provide a method and an apparatus for determining validity of samples for a digital pre-distortion apparatus that is configured to compensate for nonlinearity of a power amplifier in an efficient manner by accurately estimating a pre-distortion coefficient with a low-capacity memory.