Adaptive self-linearization with separation filter
View Patent ↗Signal processing includes receiving an unknown signal having a distorted component and an undistorted component, the distorted component and the undistorted component having a nonlinear relationship; and separating from the unknown signal a reference component and a target component.
1. A method of signal processing, comprising:
receiving, at an adaptive self-linearization module, an unknown signal; wherein:
the unknown signal has a distorted component and an undistorted component; and
the distorted component and the undistorted component have a nonlinear relationship; and
separating, at the adaptive self-linearization module, from the unknown signal a reference component and a target component, wherein:
there is no prior knowledge of characteristics of the unknown signal; and
the reference component corresponds to an estimate of one or more signal components that cause the distorted component in the unknown signal, and the target component corresponds to a difference between the unknown signal and the reference component.
2. A method as recited in claim 1 , wherein separating from the unknown signal a reference component and a target component includes:
aggregating the unknown signal over a period of time; and
generating the reference component based on the aggregation.
3. A method as recited in claim 1 , wherein the distorted component is substantially caused by the undistorted component.
4. A method as recited in claim 2 , wherein separating from the unknown signal a reference component and a target component further includes delaying the unknown signal.
5. A method as recited in claim 2 , wherein aggregating the unknown signal over a period of time includes adaptively aggregate the unknown signal.
6. A method as recited in claim 2 , wherein aggregating the unknown signal over a period of time includes:
adapting a plurality of coefficients;
scaling a plurality of samples of the unknown signal using the plurality of coefficients; and
aggregating the scaled samples.
7. A method as recited in claim 6 , further comprising providing feedback to adapt the plurality of coefficients.
8. A method as recited in claim 7 , wherein the feedback includes a difference between a sample of the unknown signal and the aggregated signal.
9. A method as recited in claim 1 , further comprising controlling the adaptation by detecting signal strength of the unknown signal.
10. A method as recited in claim 1 , further comprising controlling the adaptation, including by adjusting a step size μ.
11. A method as recited in claim 1 , further comprising controlling the adaptation, including by adjusting number of filter taps N.
12. A method as recited in claim 1 , further comprising based at least in part on the reference signal, adaptively generating a replica distortion signal that is substantially similar to the distorted component, and subtracting the replica distortion signal from the unknown signal to obtain an output signal.
13. A signal processing system comprising:
an input terminal configured to receive an unknown signal; wherein:
the unknown signal has a distorted component and an undistorted component; and
the distorted component and the undistorted component have a nonlinear relationship; and
a separation block coupled to the input terminal, configured to separate from the unknown signal a reference component and a target component, wherein:
there is no prior knowledge of characteristics of the unknown signal; and
the reference component includes an estimate of one or more signal components that cause the distorted component in the unknown signal, and the target component corresponds to a difference between the unknown signal and the reference component.
14. A system as recited in claim 13 , wherein the separation block includes a persistence filter configured to aggregate the unknown signal over a period of time and generate the reference component.
15. A system as recited in claim 14 , wherein the separation block further includes a combiner configured to combine a sample of the unknown signal and the aggregate signal.
16. A system as recited in claim 14 , wherein the separation block further includes a plurality of coefficient multipliers configured to scale a plurality of samples of the unknown signal with a plurality of coefficients.
17. A system as recited in claim 14 , wherein the persistence filter includes a filter having N filter taps.
18. A system as recited in claim 14 , wherein the persistence filter is adaptive.
19. A system as recited in claim 18 , wherein the persistence filter is adapted by detecting signal strength of the unknown signal.
20. A system as recited in claim 14 , wherein the persistence filter is adaptive and includes a filter having N filter taps, and adaptation of the persistence filter is controlled by adjusting N.
21. A system as recited in claim 14 , wherein the persistence filter is adaptive and is adapted by adjusting a step size μ.
22. A system as recited in claim 13 , further comprising an adaptive filter coupled to the separation block, configured to adaptively generate, based at least in part on the reference signal, a replica distortion signal that is substantially similar to the distorted component, and subtracting the replica distortion signal from the unknown signal to obtain an output signal.