Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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A New Polynomial Digital Predistortion Method Based on Direct Learning for Linearizing Nonlinear Power Amplifier

비선형 앰프의 선형화를 위한 다항식 기반 직접 학습 방식의 디지털 사전왜곡 기법

  • Published : 2007.12.31
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Abstract

A new polynomial-based predistortion method for linearizing nonlinear power amplifier is proposed. The proposed method finds the predistortion parameter directly without the help of postdistorter whereas most existing polynomial-based predistortion methods calculate the predistortion parameter indirectly from the prostdistorter. First, a new predistortion algorithm is derived based on the assumption that the characteristic of the amplifier is modeled by piecewise linear function. Then it is modified into a proposed method which does not require any assumption or prior knowledge of the amplifier. The proposed method is derived based on the RLS (recursive least squares) algorithm. The proposed technique is simpler to implement than the existing methods and the computer simulation demonstrates that the proposed method is more robust to the initial condition and the saturation region of the amplifier.

본 논문에서는 비선형 앰프를 선형화 하는 다항식에 기반한 사전왜곡 알고리즘을 제안한다. 제안된 방식은 기존의 다항식 기반 방식과는 다르게 사후왜곡기의 도움 없이 직접 학습 방식으로 사전왜곡 계수를 추정한다. 먼저 앰프의 특성이 부분 선형으로 가정하여 알고리즘이 유도되고, 다음에 이 알고리즘을 앰프에 대한 어떠한 가정이 필요없는 구조로 변경한다. 제안된 사전왜곡기는 복소 계수를 가지는 다항식으로 구성되며 다항식의 계수는 RLS(recursive least squares)에 기반하여 찾게 된다. 컴퓨터 모의실험에 의하면 제안된 직접방식의 알고리즘이 기존의 간접 학습 방식에 비해 앰프의 초기 계수나 포화 영역에서 강인한 특성을 보인다.

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References

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