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Linear power amplifier modeling based on predistortion technology

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Wuhan University Journal of Natural Sciences

Abstract

Different power amplifier (PA) models have their own effects on PA linearization. In this paper, the nonlinear characteristic of the radio frequency power amplifier (RF PA) is simulated based on the two models combining predistortion technology, and the nonlinear effects of the two models are analyzed, respectively. The simulation results show that Power Series model normalized mean square error (NMSE) is −37.8 dB, which is less than Power Series model −30.4 dB before loading predistortion technology. NMSE of the two systems are −23.4 dB and −26.0 dB respectively, while Saleh model compensates better than the Power Series model combing predistortion technology. The error vector magnitude (EVM) of Power Series model is only 6.75%, whereas the Saleh model EVM is 9.99%, indicating that Power Series model can better describe the nonlinear characteristic of PA. It will have a positive effect on improving the power utilization of wireless communication system.

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Authors and Affiliations

  1. School of Electric Information, Huanggang Normal University, Huanggang, Hubei, 438000, China

    Yulin Xie, Wei Xie, Jie Xiong & Gui Lei

  2. Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China

    Yulin Xie

  3. National Time Service Center, Chinese Academy of Sciences, Xi’an, Shaanxi, 710600, China

    Long Chen

Authors
  1. Yulin Xie
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  2. Wei Xie
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  3. Long Chen
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  4. Jie Xiong
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  5. Gui Lei
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Corresponding author

Correspondence to Gui Lei.

Additional information

Foundation item: Supported by the Research Project of Department of Education Hubei Provincial (B2016206), the Huanggang Normal University Science and Technology Innovation Team Program (201613603)

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Xie, Y., Xie, W., Chen, L. et al. Linear power amplifier modeling based on predistortion technology. Wuhan Univ. J. Nat. Sci. 22, 395–401 (2017). https://doi.org/10.1007/s11859-017-1264-z

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  • DOI: https://doi.org/10.1007/s11859-017-1264-z

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