Non-Linear Model with Tap Output Normalization
First Claim
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1. A method of compensating an input signal for distortion introduced by an electronic device operating on the input signal to produce an output signal, the method comprising:
- generating, for each of a plurality of sampling time instances, first and second signal samples representing said input and output signals;
generating, for one or more of said sampling time instances, a corresponding set of data samples from said first signal samples and a set of basis functions in a non-linear distortion model of the electronic device or predistorter;
normalizing the data samples so that the normalized data samples from each basis function have a pre-determined variance;
calculating model weighting coefficients to fit the normalized data samples to the second signal samples according to the non-linear distortion model;
determining predistortion weights from the model fitting parameters; and
applying the predistortion weights to the input signal to compensate for the distortion introduced by the electronic device.
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Abstract
A distortion model for a predistortion system uses tap output normalization to normalize the variance of data signals generated from different basis functions in a set of basis functions to a predetermined value. The distortion model is used by a distortion modeling circuit to calculate the weighting coefficients for a digital predistorter.
25 Citations
24 Claims
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1. A method of compensating an input signal for distortion introduced by an electronic device operating on the input signal to produce an output signal, the method comprising:
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generating, for each of a plurality of sampling time instances, first and second signal samples representing said input and output signals; generating, for one or more of said sampling time instances, a corresponding set of data samples from said first signal samples and a set of basis functions in a non-linear distortion model of the electronic device or predistorter; normalizing the data samples so that the normalized data samples from each basis function have a pre-determined variance; calculating model weighting coefficients to fit the normalized data samples to the second signal samples according to the non-linear distortion model; determining predistortion weights from the model fitting parameters; and applying the predistortion weights to the input signal to compensate for the distortion introduced by the electronic device. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A predistortion circuit for predistorting an input signal to compensate for distortion introduced by an electronic device operating on the input signal to produce an output signal, the predistortion circuit comprising:
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an input circuit configured to generate, for each of a plurality of sampling time instances, first and second signal samples representing said input and output signals; a distortion modeling circuit to model distortion of the electronic device or predistorter and to compute predistortion weights, said distortion modeling circuit configured to; generate, for one or more of said sampling time instances, a corresponding set of data samples from said first signal samples and a set of basis functions in a non-linear distortion model of the electronic device or predistorter; normalize the data samples so that the normalized data samples from each basis function have a pre-determined variance; calculate model weighting coefficients to fit the normalized data samples to the second signal samples according to the non-linear distortion model; determine predistortion weights from the model weighting coefficients; a predistorter to apply the predistortion weights to the input signal to compensate for the distortion introduced by the electronic device - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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Specification