Adaptive Digital Pre-Distortion for Power Amplifier Linearity
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Solution Overview
Problem
Existing pre-distortion techniques for power amplifiers are less than optimal, leading to significant signal distortion and inefficiency, particularly at high power levels, where there is a need for improved linearization methods to enhance signal quality.
Innovation Solution
The implementation of an adaptive pre-distortion system that uses a pre-distortion unit, power amplifier model, and feedback loop to iteratively update model parameters, minimizing error signals and ensuring linear amplification by computing the inverse of the power amplifier model, which can be applied segment-wise using piecewise polynomial approximations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If Class C power amplifiers are used to achieve high efficiency, then energy efficiency is improved, but signal distortion increases significantly
Solution Approach 1:
The system applies pre-distortion to the input signal before it reaches the power amplifier. A pre-distortion function intentionally distorts the input signal in advance according to a model of the amplifier's non-linear behavior, so that the amplifier's non-linearity cancels out the pre-applied distortion, resulting in linearized output while maintaining Class C efficiency
Solution Approach 2:
The system uses a feedback loop where a portion of the amplifier's output is fed back through a down-converter and comparator. The comparator compares the down-converted output with the original input signal, and the error signal is used to iteratively update the pre-distortion function parameters, enabling adaptive optimization of the linearization
2Object-generated harmful factors
If conventional pre-distortion techniques are applied to reduce distortion, then signal linearity is improved, but the pre-distortion functionality remains suboptimal
Solution Approach 1:
The system transitions from static pre-distortion parameters to dynamic adaptive parameters. The pre-distortion function is continuously updated based on real-time feedback from the amplifier output, allowing the system to adapt to changing operating conditions, temperature variations, and amplifier aging, thereby significantly improving pre-distortion performance
Solution Approach 2:
The system modifies the parameters of the pre-distortion function based on operating conditions. By using a polynomial model with adjustable coefficients that are continuously optimized through feedback, the system can adapt the pre-distortion characteristics to match the actual amplifier behavior under different power levels and conditions
Data Source
AI summary
One embodiment relates to a system which includes a pre-distortion unit, a power amplifier circuit, a power amplifier model, and a parameter estimation unit. The pre-distortion unit is configured to pre-distort an input signal based on a model parameter by directly computing the model inverse in an iterative fashion, thereby providing a pre-distorted signal. The power amplifier circuit is configured to amplify the pre-distorted signal. The power amplifier model is configured to model amplification of the pre-distorted signal by the power amplifier circuit based on the pre-distorted signal and the model parameter. Based on the pre-distorted signal and an error signal, the parameter estimation unit is configured to update the model parameter provided to the pre-distortion unit and the power amplifier model. The error signal represents a difference between an output signal from the power amplifier circuit and a modeled output signal from the power amplifier model.