A neural network-based DPD coefficient determination for PA linearization in 5G and beyond-5G mmWave systems-Reference-Cited by-同舟云学术

A neural network-based DPD coefficient determination for PA linearization in 5G and beyond-5G mmWave systems

Published:2024-05-25 Issue:10 Volume:21 Page:20240186-20240186
ISSN:1349-2543
Container-title:IEICE Electronics Express
language:en
Short-container-title:IEICE Electron. Express

Author:

Narayanan Aravind Tharayil¹,Minati Ludovico¹,Hagihara Aran¹,Kobayashi Jun²,Shimura Toshihiro²,Kawano Yoichi²,Chakraborty Parthojit¹,Bartels Jim¹,Tokgöz Korkut Kaan¹³,Dosho Shiro¹,Suzuki Toshihide²,Ito Hiroyuki¹

Affiliation:

1. Institute of Innovative Research, Tokyo Institute of Technology

2. Mobile Systems Business Unit, Wireless Product Development Division, Fujitsu Corporation

3. Faculty of Engineering and Natural Sciences, Sabanci University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Link

https://www.jstage.jst.go.jp/article/elex/21/10/21_21.20240186/_pdf

Reference31 articles.

1. [1] H. Tataria, et al.: “6G wireless systems: vision, requirements, challenges, insights, and opportunities,” Proc. IEEE 109 (2021) 1166 (DOI: 10.1109/jproc.2021.3061701).

2. [2] K.B. Letaief, et al.: “The roadmap to 6G: AI empowered wireless networks,” IEEE Commun. Mag. 57 (2019) 84 (DOI: 10.1109/mcom.2019.1900271).

3. [3] T.S. Rappaport, et al.: “Wireless communications and applications above 100GHz: opportunities and challenges for 6G and beyond,” IEEE Access 7 (2019) 78729 (DOI: 10.1109/access.2019.2921522).

4. [4] L. Chettri and R. Bera: “A comprehensive survey on internet of things (IoT) toward 5G wireless systems,” IEEE Internet Things J. 7 (2020) 16 (DOI: 10.1109/jiot.2019.2948888).

5. [5] I. Ahmed, et al.: “A survey on hybrid beamforming techniques in 5G: architecture and system model perspectives,” IEEE Commun. Surveys Tuts. 20 (2018) 3060 (DOI: 10.1109/comst.2018.2843719).