DOI码：10.1109/LMWT.2025.3546643

所属单位：中国科学技术大学信息学院

教研室：电子工程与信息科学系

发表刊物：IEEE Microwave and Wireless Technology Letters (Early Access)

项目来源：国家自然科学基金 NNSF 62371436

关键字：End-to-end optimization, digital predistortion (DPD), peak-to-average power ratio (PAPR) reduction, neural network (NN), power amplifiers (PAs), geometric shaping (GS).

摘要：The combination of crest factor reduction (CFR) and digital predistortion (DPD) can mitigate the average efficiency reduction of power amplifiers (PAs) due to high peak-to-average power ratio (PAPR) signals. A common CFR method is time-domain (TD) clipping, which causes irreversible signal impairment. To this end, an end-to-end (E2E) joint optimization method based on neural networks (NNs) is proposed in this letter. The E2E architecture consists of a transmitter network, a DPD model, and a PA model, enabling integrated processing of signal transmitted, transmission, and reception. The proposed method uses multiobjective joint optimization to reduce the PAPR of the TD signal through constellation point geometric shaping (GS) in the frequency domain, while simultaneously training the DPD model. While considering the interaction between PAPR reduction and DPD techniques, this approach can reduce PAPR without signal impairment and can allow them to work together to achieve high-quality signal transmission.

第一作者：Qianqian Zhang (张牵牵)

合写作者：Renlong Han,Chengye Jiang,Junsen Wang,Hao Chang

论文类型：期刊论文

通讯作者：Falin Liu

论文编号：10.1109/LMWT.2025.3546643

学科门类：工学

文献类型：J

卷号：Online

期号：Online

页面范围：1-4

是否译文：否

发表时间：2025-03-12