中国邮电高校学报(英文) ›› 2014, Vol. 21 ›› Issue (3): 18-22.doi: 10.1016/S1005-8885(14)60296-X

• Wireless • 上一篇    下一篇

Cancellation of nonlinear distortion based on integration of FCM clustering algorithm and adaptive-two-stage linear approximation

王桂叶 邹卫霞 王振宇 杜光龙 GAO Ying   

  1. 1. Key laboratory of wireless universal communications, Beijing University of Posts and Telecommunications, Beijing 100876, China 2. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • 收稿日期:2013-06-21 修回日期:2014-05-11 出版日期:2014-06-30 发布日期:2014-06-30
  • 通讯作者: 王桂叶 E-mail:guiyexieyun@163.com
  • 基金资助:

    This work was supported by the National Natural Science Foundation of China (61171104).

Cancellation of nonlinear distortion based on integration of FCM clustering algorithm and adaptive-two-stage linear approximation

王桂叶 邹卫霞 王振宇 杜光龙 GAO Ying   

  1. 1. Key laboratory of wireless universal communications, Beijing University of Posts and Telecommunications, Beijing 100876, China 2. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2013-06-21 Revised:2014-05-11 Online:2014-06-30 Published:2014-06-30
  • Contact: Rebecca Wang E-mail:guiyexieyun@163.com
  • Supported by:

    This work was supported by the National Natural Science Foundation of China (61171104).

摘要:

A hybrid system of the fuzzy c-means (FCM) clustering algorithm and adaptive-two-stage linear approximation was presented for nonlinear distortion cancellation of radio frequency (RF) power amplifier (PA). This mechanism can effectively eliminate noise, adaptively model PA’s instantaneous change, and efficiently correct nonlinear distortion. This article puts forward the FCM clustering algorithm for clustering received signals to eliminate white noise, and then uses the adaptive-two-stage linear approximation to fit the inverse function of the amplitude’s and phase’s nonlinear mapping during the training phase. Parameters of the linear function and similarity function are trained using the gradient-descent and minimum mean-square error criteria. The proposed approach’s training results is directly employed to eliminate sampling signal’s nonlinear distortion. This hybrid method is realized easier than the multi-segment linear approximation and could reduce the received signal’s bit error rate (BER) more efficiently.

关键词:

PA, nonlinear distortion cancellation, FCM clustering algorithm, similarity function, adaptive-two-stage linear approximation

Abstract:

This paper presents a new hybrid system of the fuzzy c-means clustering algorithm and adaptive-two-stage linear approximation for the nonlinear distortion cancellation of the RF power amplifier (PA). This mechanism can eliminate the noise, adaptively model the PA’s instantaneous change, and then correct the nonlinear distortion efficiently. The paper puts forward using the FCM clustering algorithm for clustering the received signal to eliminate white noise, and then uses adaptive-two-stage linear approximation to fit the inverse function of the amplitude’s and phase’s nonlinear mapping in the training phase. Firstly, the parameters involved in the linear function and the similarity function are trained using gradient-descent and minimum mean-square error criterion. Secondly, the sample signals directly employ the proposed approach’s training result to eliminate nonlinear distortion. This hybrid method is easier to realize than the multi-segment linear approximation and could more efficiently reduce the received signal’s BER.

Key words:

PA, nonlinear distortion cancellation, FCM clustering algorithm, similarity function, adaptive-two-stage linear approximation

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