Adaptive Basis Direct Learning Method for Predistortion of RF Power Amplifier

被引:12
|
作者
Yu, Cuiping [1 ]
Tang, Ke [1 ]
Liu, Yuanan [1 ]
机构
[1] Beijing Univ Posts & Telecommun, Beijing Key Lab Work Safety Intelligent Monitorin, Sch Elect Engn, Beijing 100876, Peoples R China
基金
中国国家自然科学基金;
关键词
Noise measurement; Predistortion; Convergence; Learning systems; Wireless communication; Complexity theory; Mean square error methods; Adaptive basis; digital predistortion (DPD); direct learning (DL) structure; power amplifier (PA);
D O I
10.1109/LMWC.2019.2951193
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:98 / 101
页数:4
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