UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 10 | October 2026

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Published in:

Volume 12 Issue 8
August-2025
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2508083


Registration ID:
567664

Page Number

a711-a719

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Title

Digital Pre-Distortion Linearization of Power Amplifier using Neural Network

Abstract

Power amplifiers lie at the front end of most radio frequency systems and are critical in ensuring the appropriate range of wireless systems. The persistent search of enhanced efficiency and linearity in power amplifiers has become a pivotal focus in modern wireless communication systems, driven by the escalating demands for higher data rates and improved signal quality. Digital pre-distortion has emerged as a well-known technique to address the inherent nonlinearities exhibited by power amplifiers, Digital pre-distortion has shown to be advantageous in systems employing higher order modulation formats. Digital pre-distortion enables power amplifiers to operate closer to their saturation point, thereby maximizing power efficiency without sacrificing signal integrity. In this paper, neural network technique has been used to model a digital pre-distorter for linearization of power amplifier used in 5G communication system. To compare the performance of proposed digital pre-distorter, cross-term memory polynomial based digital pre-distorter has also been modeled. Results show that proposed digital pre-distorter modeled using neural network has better performance. The paper is organized as follows: section I presents introduction, concept of digital pre-distortion is presented in section II, section III is concept of augmented real-valued time-delay neural network, proposed power amplifier linearization technique is presented in section IV and section V presents conclusion.

Key Words

adjacent channel power ratio, augmented real-valued time-delay neural network, digital pre-distortion, error vector magnitude, normalized mean square error, power amplifier.

Cite This Article

"Digital Pre-Distortion Linearization of Power Amplifier using Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 8, page no.a711-a719, August-2025, Available :http://www.jetir.org/papers/JETIR2508083.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Digital Pre-Distortion Linearization of Power Amplifier using Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 8, page no. ppa711-a719, August-2025, Available at : http://www.jetir.org/papers/JETIR2508083.pdf

Publication Details

Published Paper ID: JETIR2508083
Registration ID: 567664
Published In: Volume 12 | Issue 8 | Year August-2025
DOI (Digital Object Identifier): https://doi.org/10.56975/jetir.v12i8.567664
Page No: a711-a719
Country: Patiala, Punjab, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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