Deep learning based asymmetrical autoencoder for PAPR reduction of CP-OFDM systems

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Deep learning based asymmetrical autoencoder for PAPR reduction of CP-OFDM systems

Adoption of Orthogonal Frequency Division Multiplexing (OFDM) in 5th Generation New Radio (5G NR) as a multicarrier modulation technique allows high data rate transmission with lower complexity. However, problem such as peak to average power ratio (PAPR) has decreased the transmitter efficiency. Rec...

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Bibliographic Details
Published in:	ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH
Main Authors:	Abdullah, Ezmin; Dimyati, Kaharudin; Muhamad, Wan Norsyafizan W.; Shuhaimi, Nurain Izzati; Mohamad, Roslina; Hidayat, Nabil M.
Format:	Article; Early Access
Language:	English
Published:	ELSEVIER - DIVISION REED ELSEVIER INDIA PVT LTD 2024
Subjects:	Engineering
Online Access:	https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001162239300001

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