Power Amplifier Memory Modeling Across Waveforms and Power Levels
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Solution Overview
Problem
Existing power amplifier models are limited in their ability to compensate for non-linearity and memory effects across varying input waveforms and power levels, leading to inadequate performance in amplifying signals with different characteristics.
Innovation Solution
A universal memory-based model is extracted using a specific extraction waveform with tones of varying frequencies, ensuring the model can be used for a range of waveforms and power levels without the need for additional signal extraction, and digital pre-distortion is applied based on this model to compensate for non-linearity and memory effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a power amplifier model is extracted using a specific input waveform and power level, then the model can accurately compensate for non-linearity and memory effects at that specific condition, but the model cannot adequately compensate for input signals having substantially different waveform and/or power level
Solution Approach 1:
The patent applies universality by designing an extraction waveform that can serve multiple functions: it characterizes the power amplifier's non-linear behavior across different power levels and memory effects simultaneously. The waveform includes multiple frequency components with specific spacing relationships that enable the model to be universally applicable to various input signal types and power levels, not just the specific extraction conditions.
Solution Approach 2:
The patent utilizes parameter changes by varying the frequency spacing relationships in the extraction waveform. Specifically, the waveform is designed with frequency components where the difference between adjacent frequencies follows a non-integer multiple relationship, which changes the excitation patterns across different power levels and enables the model to capture behavior across a broader range of operating conditions.
2Measurement precision
If multiple models are extracted for different waveforms and power levels, then each model can be optimized for its specific condition, but the hardware complexity and power consumption increase
Solution Approach 1:
The patent reduces hardware complexity by implementing a single universal model extraction approach that replaces the need for multiple separate models. The extraction waveform is designed to simultaneously characterize the power amplifier across different operating conditions, allowing one model to serve multiple functions that would otherwise require multiple specialized models and associated hardware.
Solution Approach 2:
The patent merges multiple model extraction requirements into a single unified approach. By combining multiple frequency components with specific spacing relationships in one extraction waveform, the patent consolidates what would otherwise require separate extraction procedures into a single process, reducing hardware complexity and power consumption.
3Measurement precision
If multiple models are extracted for different waveforms and power levels, then each model can be optimized for its specific condition, but the power consumption increases
Solution Approach 1:
The patent reduces power consumption by implementing a universal model that performs multiple characterization functions simultaneously. The extraction waveform is designed to capture power amplifier behavior across different power levels and memory effects in a single extraction process, eliminating the need to run multiple separate extraction procedures that would consume additional power.
Solution Approach 2:
The patent combines multiple model extraction operations into a single unified extraction process. By merging the characterization of different power levels and memory effects into one extraction waveform with specific frequency spacing relationships, the patent reduces the total power consumption that would otherwise be required to execute multiple separate extraction procedures.
Data Source
AI summary
A method for modelling a power amplifier, including memory effect modelling, for general input waveforms and power levels involves generating an extraction waveform having a plurality of tones each having a different frequency, a difference between the frequencies of two adjacent tones of the plurality of tones not being an integer multiple of a difference in frequency between any two other adjacent tones of the plurality of tones. The method further involves providing the extraction waveform to the power amplifier, receiving output from the power amplifier generated in response to the extraction waveform, and generating a model of the power amplifier based on the output.