Model Identification for Digital Predistortion of Power Amplifier with Signed Regressor Algorithm

Ning Guan; Nan Wu; Hua Wang

doi:10.1109/LMWC.2018.2860790

Model Identification for Digital Predistortion of Power Amplifier with Signed Regressor Algorithm

Ning Guan^*, Nan Wu, Hua Wang

^*Corresponding author for this work

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

Abstract

In this letter, a low-complexity approach is proposed to estimate model parameters of digital predistortion (DPD). It takes the advantage of low implementation cost of the signed regressor algorithm and eliminates most multiplications required. A Walsh-Hadamard transform is employed to avoid the correlation between signed DPD basis functions. Performance of the proposed approach is evaluated via experiments, with a two-carrier long term evolution-advanced signal on a 3.5-GHz power amplifier. It is shown that compared with the conventional least-square-based method the proposed approach can achieve similar linearization and convergence performance with much lower computational complexity.

Original language	English
Article number	8458132
Pages (from-to)	921-923
Number of pages	3
Journal	IEEE Microwave and Wireless Components Letters
Volume	28
Issue number	10
DOIs	https://doi.org/10.1109/LMWC.2018.2860790
Publication status	Published - Oct 2018

Keywords

Digital predistortion (DPD)
model identification
signed regressor algorithm (SRA)

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10.1109/LMWC.2018.2860790

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abstract = "In this letter, a low-complexity approach is proposed to estimate model parameters of digital predistortion (DPD). It takes the advantage of low implementation cost of the signed regressor algorithm and eliminates most multiplications required. A Walsh-Hadamard transform is employed to avoid the correlation between signed DPD basis functions. Performance of the proposed approach is evaluated via experiments, with a two-carrier long term evolution-advanced signal on a 3.5-GHz power amplifier. It is shown that compared with the conventional least-square-based method the proposed approach can achieve similar linearization and convergence performance with much lower computational complexity.",

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AB - In this letter, a low-complexity approach is proposed to estimate model parameters of digital predistortion (DPD). It takes the advantage of low implementation cost of the signed regressor algorithm and eliminates most multiplications required. A Walsh-Hadamard transform is employed to avoid the correlation between signed DPD basis functions. Performance of the proposed approach is evaluated via experiments, with a two-carrier long term evolution-advanced signal on a 3.5-GHz power amplifier. It is shown that compared with the conventional least-square-based method the proposed approach can achieve similar linearization and convergence performance with much lower computational complexity.

KW - Digital predistortion (DPD)

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KW - signed regressor algorithm (SRA)

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Model Identification for Digital Predistortion of Power Amplifier with Signed Regressor Algorithm

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Keywords

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