Amplifier measurement and modeling processes for use in generating predistortion parameters
First Claim
1. A method for modeling a wideband amplifier, comprising:
- (a) applying stimulation signals to the amplifier to measure characteristics of the amplifier;
(b) using the characteristics measured in (a) to generate a non-linear model of the amplifier;
(c) applying an input signal to the model and to the amplifier while monitoring a difference between respective outputs thereof, and adaptively adjusting parameters of the model until an error floor in the difference is substantially reached; and
(d) increasing a level of complexity of the model and then repeating (c), wherein increasing the level of complexity of the model comprises increasing an order of the model.
4 Assignments
0 Petitions
Accused Products
Abstract
A wideband predistortion system compensates for a nonlinear amplifier'"'"'s frequency and time dependent AM-AM and AM-PM distortion characteristics. The system comprises a data structure in which each element stores a set of compensation parameters (preferably including FIR filter coefficients) for predistorting the wideband input transmission signal. The parameter sets arc preferably indexed within the data structure according to multiple signal characteristics, such as instantaneous amplitude and integrated signal envelope, each of which corresponds to a respective dimension of the data structure. To predistort the input transmission signal, an addressing circuit digitally generates a set of data structure indices from the input transmission signal, and the indexed set of compensation parameters is loaded into a compensation circuit which digitally predistorts the input transmission signal. This process of loading new compensation parameters into the compensation circuit is preferably repeated every sample instant, so that the predistortion function varies from sample-to-sample. The sets of compensation parameters are generated periodically and written to the data structure by an adaptive processing component that performs a non-real-time analysis of amplifier input and output signals. The adaptive processing component also implements various system identification processes for measuring the characteristics of the power amplifier and generating initial sets of filter coefficients. In an antenna array embodiment, a single adaptive processing component generates the compensation parameters sets for each of multiple amplification chains on a time-shared basis. In an embodiment in which the amplification chain includes multiple nonlinear amplifiers that can be individually controlled (e.g., turned ON and OFF) to conserve power, the data structure separately stores compensation parameter sets for each operating state of the amplification chain.
-
Citations
19 Claims
-
1. A method for modeling a wideband amplifier, comprising:
-
(a) applying stimulation signals to the amplifier to measure characteristics of the amplifier;
(b) using the characteristics measured in (a) to generate a non-linear model of the amplifier;
(c) applying an input signal to the model and to the amplifier while monitoring a difference between respective outputs thereof, and adaptively adjusting parameters of the model until an error floor in the difference is substantially reached; and
(d) increasing a level of complexity of the model and then repeating (c), wherein increasing the level of complexity of the model comprises increasing an order of the model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
coupling the amplifier model to an output of a pre-amplification compensation module;
applying a signal to the pre-amplification compensation module, and monitoring a resulting difference between said signal and an output of the amplifier model; and
adaptively adjusting compensation parameters of the pre-amplification compensation module to reduce said difference, to thereby generate estimates of compensation parameters to be used during transmissions.
-
-
13. The method as in claim 12, wherein the pre-amplification compensation module is a model of a pre-amplification compensation circuit used during transmissions.
-
14. The method as in claim 12, wherein adaptively adjusting the compensation parameters comprises applying at least one of the following types of algorithms:
- LMS, RLS, Kalman.
-
15. The method as in claim 14, wherein adaptively adjusting the compensation parameters further comprises using convolutional updating of FIR filter coefficients.
-
16. The method as in claim 1, further comprising, after (d):
-
reducing the model of the amplifier to a first order, single kernel model in which sets of filter coefficients are stored in a one-dimensional data structure; and
computing an initial set of the compensation parameters directly from the first order, single kernel model.
-
-
17. A method of generating an initial set of compensation parameters, including filter coefficients, for use within a digital compensation circuit that predistorts an input signal to a wideband amplifier, the method comprising:
-
generating an initial model of the wideband amplifier, wherein the initial model comprises a filter structure for which sets of coefficients are supplied by a multi-dimensional data structure, wherein each dimension of the data structure corresponds to a different respective input signal characteristic and each storage element of the data structure stores a set of filter coefficients;
reducing the initial model of the amplifier to a first order, single kernel model in which sets of filter coefficients are stored in a one-dimensional data structure; and
computing an initial set of the compensation parameters directly from the first order, single kernel model. - View Dependent Claims (18, 19)
(a) applying stimulation signals to the amplifier to measure characteristics of the amplifier;
(b) using the characteristics measured in (a) to generate a non-linear model of the amplifier;
(c) applying an input signal to the non-linear model and to the amplifier while monitoring a difference between respective outputs thereof, and adaptively adjusting parameters of the model until an error floor in the difference is substantially reached; and
(d) increasing a level of complexity of the non-linear model and then repeating (c) until a desired level of accuracy is reached.
-
-
19. The method as in claim 17, wherein the one-dimensional data structure stores FIR filter coefficient sets that are indexed based solely on an amplitude of the input signal.
Specification