A Generalized Digital Predistortion Model Based on Artificial Neural Networks

被引：0
|
作者：
Yu, Zhijian [1 ]
机构：
[1] Shanghai Huawei Technol Co Ltd, Shanghai 201206, Peoples R China
来源：
2018 ASIA-PACIFIC MICROWAVE CONFERENCE PROCEEDINGS (APMC) | 2018年
关键词：
Linearization; power amplifiers; digital predistortion; artificial neural networks;
D O I：
暂无
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 paper, the CPWL-based DPD model in is extended to a DPD model based on artificial neural networks, where the mapping from R-n to C-m in CPWL functions is implemented by ANNs. The linearization performance of ANNs model with different activation functions is also validated with platform tests. The test results show the ANNs-based DPD model with ABS activation function can achieve similar performance as the CPWL-based DPD model. The performance of ANNs model with other activation functions (PWL, ReLU and tanh functions), is 1 similar to 2 dB worse than that of the ABS activation function.
引用
收藏
页码：935 / 937
页数：3
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