Novel Adaptive Digital Predistortion Based on the Hybrid Indirect Learning Algorithm

被引:0
作者
Zhang, F. [1 ]
Wang, Y. [1 ]
Ai, B. [1 ]
机构
[1] Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China
来源
2014 IEEE INTERNATIONAL SYMPOSIUM ON BROADBAND MULTIMEDIA SYSTEMS AND BROADCASTING (BMSB) | 2014年
关键词
HPA; DPD; HIL; measurement noise;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Adaptive digital predistortion (DPD) is one of the most promising linearization technique, which leads to more efficient and cost-effective high power amplifier (HPA). In this paper, we propose a novel adaptive DPD based on the hybrid indirect learning (HIL) algorithm, which can not only remedy the effect caused by measurement noise in the feedback loop effectively, but also improve the convergence stability and reduce the overall cost of DPD implementation simultaneously. The effectiveness of this scheme in the presence of the measurement noise was confirmed through computer simulations.
引用
收藏
页数:4
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