2011
DOI: 10.1142/s0218126611007724
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Linearization of Rf Power Amplifiers Using Adaptive Kalman Filtering Algorithm

Abstract: In this paper, a new linearization algorithm of Power Amplifier, based on Kalman filtering theory is proposed for obtaining fast convergence of the adaptive digital predistortion. The proposed method uses the real-time digital processing of baseband signals to compensate the nonlinearities and memory effects in radio-frequency Power Amplifier. To reduce the complexity of computing in classical Kalman Filtering, a sliding timewindow has been inserted which combines off-line measurement and on-line parameter est… Show more

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Cited by 6 publications
(2 citation statements)
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“…In order to reduce this Back-Off while maintaining good transmission quality, linearization techniques [10][11][12][13][14][15], such as digital predistortion, have proven to be effective and are widely used in numerous wireless communication systems [16][17][18][19][20]. Their principle is to digitally predistort the complex signal envelope in order to compensate the PA distortions [21,22]. Therefore, complex mathematical functions are implemented to describe its gain/phase inverse characteristics and memory effects.…”
Section: Introductionmentioning
confidence: 99%
“…In order to reduce this Back-Off while maintaining good transmission quality, linearization techniques [10][11][12][13][14][15], such as digital predistortion, have proven to be effective and are widely used in numerous wireless communication systems [16][17][18][19][20]. Their principle is to digitally predistort the complex signal envelope in order to compensate the PA distortions [21,22]. Therefore, complex mathematical functions are implemented to describe its gain/phase inverse characteristics and memory effects.…”
Section: Introductionmentioning
confidence: 99%
“…One solution to minimize these effects without compromising the efficiency is to linearize the PA behavior. Predistortion techniques have been proposed as a potential solution to overcome the non-linear effects [2] [3]. Their common principle is the introduction of inverse nonlinearities to compensate for the PA distortions.…”
Section: Introductionmentioning
confidence: 99%