SYSTEM LINEARIZATION

• US 20130166259A1
• Filed: 11/16/2012
• Published: 06/27/2013
• Est. Priority Date: 11/17/2011
• Status: Abandoned Application

• Current Assignee: Analog Devices, Inc.
• Original Assignee: Analog Devices, Inc.
• Inventors: Vigoda, Benjamin, McCormick, Martin, Weber, Theophane, Pratt, Patrick, Park, Joshua
• Application Number:
  US13/678,904
• Publication Number:
  US 20130166259A1
• Time in Patent Office: Days
• US Class Current: 703/2
• CPC Class Codes: H03F 1/3247 using feedback acting on predistortion circuits H03F1/3264 takes precedence
• CPC Class Codes: H03F 1/3258 based on polynomial terms
• CPC Class Codes: H03F 1/3282 Acting on the phase and the amplitude of the input signal
• CPC Class Codes: H03F 2201/3209 the amplifier comprising means for compensating memory effects
• CPC Class Codes: H03F 2201/3224 Predistortion being done for compensating memory effects

Abstract

A method for linearizing a non-linear system element includes acquiring data representing inputs and corresponding outputs of the non-linear system element. A model parameter estimation procedure is applied to the acquired data to determine model parameters of a model characterizing input-output characteristics of the non-linear element. An input signal representing a desired output signal of the non-linear element is accepted and processed to form a modified input signal according to the determined model parameters. The processing includes, for each of a series of successive samples of the input signal, applying an iterative procedure to determining a sample of the modified input signal according to a predicted output of the model of the non-linear element. The modified input signal is provided for application to the input of the non-linear element.

Claims

1. A method for linearizing a non-linear system element comprising:

acquiring data representing inputs and corresponding outputs of the non-linear system element;

applying a model parameter estimation procedure using the acquired data to determine model parameters of a model characterizing input-output characteristics of the non-linear element;

accepting an input signal representing a desired output signal of the non-linear element;

processing the input signal to form a modified input signal according to the determined model parameters, the processing including, for each of a series of successive samples of the input signal applying an iterative procedure to determining a sample of the modified input signal according to a predicted output of the model of the non-linear element; and

providing the modified input signal for application to the input of the non-linear element.

2. The method of claim 1 wherein the non-linear system element comprises a power amplifier.

3. The method of claim 1 wherein applying the model parameter estimation procedure comprises applying a sparse regression approach, including selecting a subset of available model parameters for characterizing input-output characteristics of the model.

4. The method of claim 1 wherein applying the iterative procedure comprises applying a numerical procedure to solve a polynomial equation.

5. The method of claim 1 wherein applying the iterative procedure comprises applying a belief propagation procedure.

6. The method of claim 1 wherein applying the iterative procedure to determining a sample of the modified input signal according to a predicted output of the model of the non-linear element comprises first determining a magnitude of the sample and then a phase of said sample.

7. The method of claim 1 wherein the model characterizing input-output characteristics of the non-linear element comprises a memory polynomial.

8. The method of claim 1 wherein the model characterizing input-output characteristics of the non-linear element comprises a Volterra series model.

9. The method of claim 1 wherein the model characterizing input-output characteristics of the non-linear element comprises a model that predicts an output of the non-linear element based data representing a set of past inputs and a set of past outputs of the element.

10. The method of claim 9 wherein the model characterizing input-output characteristics of the non-linear element comprises an Infinite Impulse Response (IIR) model.

11. The method of claim 1 wherein acquiring data representing inputs and corresponding outputs of the non-linear system element comprises acquiring non-consecutive outputs of the non-linear element, and wherein the model parameter estimation procedure does not require consecutive samples of the output.

12. A system for linearizing a non-linear element, the system comprising:

an estimator configure to accept data representing inputs and corresponding outputs of the non-linear system element and apply a model parameter estimation procedure to determine model parameters of a model characterizing input-output characteristics of the non-linear element; and

a predistorter including a input for accepting an input signal representing a desired output signal of the non-linear element, an input for accepting the model parameters from the estimator, and a processing element for forming a modified input signal from the input signal, the processing element being configured to perform functions including, for each of a series of successive samples of the input signal applying an iterative procedure to determining a sample of the modified input signal according to a predicted output of the model of the non-linear element, and an output for providing the modified input signal for application to the input of the non-linear element.

13. The system of claim 12 wherein the estimator is configured to apply a sparse regression approach that includes selecting a subset of available model parameters for characterizing input-output characteristics of the model.

14. The system of claim 12 wherein the processing element is configured to apply a numerical procedure to solve a polynomial equation.

15. The system of claim 12 wherein the processing element is configured to apply a belief propagation procedure.

16. The system of claim 12 wherein the processing element is configured to determining a sample of the modified input signal according to a predicted output of the model of the non-linear element by first determining a magnitude of the sample and then a phase of said sample.

17. The system of claim 12 wherein the model characterizing input-output characteristics of the non-linear element comprises a model that predicts an output of the non-linear element based data representing a set of past inputs and a set of past outputs of the element.

18. Software stored on a non-transitory comprising instructions for causing a data processor to perform functions including:

acquiring data representing inputs and corresponding outputs of the non-linear system element;

applying a model parameter estimation procedure using the acquired data to determine model parameters of a model characterizing input-output characteristics of the non-linear element;

accepting an input signal representing a desired output signal of the non-linear element;

processing the input signal to form a modified input signal according to the determined model parameters, the processing including, for each of a series of successive samples of the input signal applying an iterative procedure to determining a sample of the modified input signal according to a predicted output of the model of the non-linear element; and

providing the modified input signal for application to the input of the non-linear element.