RF Power Amplifier Pre-Distortion with Selective Sample Updating
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Solution Overview
Problem
Existing pre-distortion systems for radio frequency amplifiers in multi-channel wireless transmitters face instability in coefficient training due to varying signal conditions, particularly when handling signals from different wireless standards with frequency hopping and amplitude variations, leading to suboptimal correction of distortion.
Innovation Solution
A method for determining pre-distorter coefficients by selectively updating input samples based on a figure of merit calculated from the frequency and amplitude spectrum, ensuring comprehensive frequency coverage and optimal amplifier characteristic consideration, even in unstable signal conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If pre-distorter coefficients are trained using all input samples in multi-channel wireless transmitter, then more data is available for coefficient determination, but coefficient training becomes unstable due to varying signal conditions and frequency hopping
Solution Approach 1:
The patent changes the parameter of sample selection by introducing a figure of merit based on frequency spectrum occupancy. Instead of using all samples uniformly, the system selectively weights or includes samples based on whether they represent occupied frequency bins, thereby adapting the training process to actual signal conditions and stabilizing coefficient determination despite frequency hopping and amplitude variations
Solution Approach 2:
The patent implements feedback by calculating the figure of merit from the frequency spectrum of input samples and using this information to adjust which samples contribute to coefficient training. The system continuously monitors spectrum occupancy and adapts the sample selection process based on this feedback, ensuring that only representative samples are used for training under varying multi-channel conditions
2Productivity
If pre-distorter coefficients are determined without selective sample updating, then the process is simpler and faster, but the correction of distortion becomes suboptimal across the entire frequency spectrum
Solution Approach 1:
The patent introduces a figure of merit parameter that evaluates the quality of input samples based on frequency spectrum occupancy. This parameter enables selective updating of coefficients only when appropriate samples are available, balancing the trade-off between processing speed and correction accuracy by avoiding unnecessary computations while ensuring comprehensive frequency coverage
3Quantity of substance
If all input samples are used for pre-distorter training, then comprehensive data coverage is achieved, but frequency spectrum gaps cause suboptimal correction in unoccupied frequency regions
Solution Approach 1:
The patent changes the approach from uniform sample inclusion to selective sample inclusion based on frequency spectrum occupancy analysis. By calculating the figure of merit for each sample set and comparing frequency spectra, the system identifies and utilizes only those samples that provide meaningful coverage of occupied frequency bins, thereby improving distortion correction quality without sacrificing comprehensive data coverage in relevant regions
Data Source
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AI summary
Coefficients of a pre-distorter are determined for correction of distortion of a signal amplified by a radio frequency amplifier by sampling the signal at the input to the pre-distorter to generate a plurality of input samples and sampling the signal at the output of the amplifier to generate a plurality of output samples, each of the plurality of output samples corresponding to one of the plurality of input samples, calculating a figure of merit for one or more of said plurality of input samples on the basis of the one or more of said plurality of input samples, selectively updating a previously selected set of input samples with said one or more of said plurality of input samples on the basis of the calculated figure of merit, whereby to generate an updated selected set and determining the coefficients of the pre-distorter on the basis of the input samples in the updated selected set and the corresponding output samples.