Nokia Solutions and Networks Gmbh & Co. Kg

Rene Roeschke

Shavantha Kularatna

Bjoern Jelonnek

Christian Reichl

The present invention addresses method, apparatus and computer program product for stabilization of the direct learning algorithm for wideband signals. Thereby, a signal to be amplified is input to a pre-distorter provided for compensating for non-linearity of the power amplifier, and the pre-distorted output signal from the pre-distorter is forwarded to the power amplifier. Parameters of the pre-distorter are adapted based on an error between the linearized signal output from the power amplifier and the signal to be amplified using an adaptive direct learning algorithm, and the linear system of equations formed by the direct learning algorithm are solved using a conjugate gradient algorithm, wherein, once per direct learning algorithm adaptation, at least one of the initial residual and the initial direction of the conjugate gradient algorithm are set based on the result of the previous adaptation.

Stabilization of direct learning algorithm for wideband signals

The present invention addresses method, apparatus and computer program product for controlling a Direct Learning Algorithm. Thereby, a power amplifier operating in a non-linear state is controlled. A signal to be amplified is input to a pre-distorter provided for compensating for non-linearity of the power amplifier. The pre-distorted output signal is forwarded from the pre-distorter to the power amplifier. Parameters of the pre-distorter are adapted in plural steps based on an error between a linearized signal output from the power amplifier and the signal to be amplified using an adaptive direct learning algorithm. It is detected whether the error diverges; and adapting of the parameters of the pre-distorter is stopped when it is determined that the error is diverging.

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Mammendorf, Germany

Rene Roeschke