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Adaptive Basis Direct Learning Method for Predistortion of RF Power Amplifier
IEEE Microwave and Wireless Components Letters ( IF 2.9 ) Pub Date : 2020-01-01 , DOI: 10.1109/lmwc.2019.2951193
Cuiping Yu , Ke Tang , Yuanan Liu

In this letter, an adaptive basis direct learning (DL) method was proposed for the linearization of power amplifiers (PAs). The proposed method can reduce the complexity and improve the stability performance of DL digital predistortion (DPD) structure. The experimental results show that the proposed method is more stable and can achieve improvement in normalized mean square error (NMSE) and adjacent channel power ratios (ACPRs) compared with the DL. In addition, the proposed method reduces the number of coefficients by 87%.

中文翻译:

射频功率放大器预失真的自适应基直接学习方法

在这封信中,提出了一种用于功率放大器 (PA) 线性化的自适应基础直接学习 (DL) 方法。所提出的方法可以降低DL数字预失真(DPD)结构的复杂度并提高其稳定性。实验结果表明,与DL相比,所提出的方法更稳定,并且可以实现归一化均方误差(NMSE)和邻道功率比(ACPR)的改善。此外,所提出的方法将系数的数量减少了 87%。
更新日期:2020-01-01
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