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Compensation of the Nonlinear Power Amplifier by Using SCPWL Predistorter with Genetic Algorithm in OFDM technique
Author(s) -
Mohannad A. M. Al-Ja’afari,
Hussein M. H. Al-Rikabi,
Hassan Falah Fakhruldeen
Publication year - 2018
Publication title -
journal of engineering
Language(s) - English
Resource type - Journals
eISSN - 2520-3339
pISSN - 1726-4073
DOI - 10.31026/j.eng.2018.06.03
Subject(s) - orthogonal frequency division multiplexing , amplifier , nonlinear system , nonlinear distortion , computer science , control theory (sociology) , algorithm , genetic algorithm , bit error rate , power (physics) , signal (programming language) , electronic engineering , telecommunications , channel (broadcasting) , engineering , bandwidth (computing) , artificial intelligence , physics , decoding methods , control (management) , quantum mechanics , machine learning , programming language
The High Power Amplifiers (HPAs), which are used in wireless communication, are distinctly characterized by nonlinear properties. The linearity of the HPA can be accomplished by retreating an HPA to put it in a linear region on account of power performance loss. Meanwhile the Orthogonal Frequency Division Multiplex signal is very rough. Therefore, it will be required a large undo to the linear action area that leads to a vital loss in power efficiency. Thereby, back-off is not a positive solution. A Simplicial Canonical Piecewise-Linear (SCPWL) model based digital predistorters are widely employed to compensating the nonlinear distortion that introduced by a HPA component in OFDM technology. In this paper, the genetic algorithm has been used to optimized the SCPWL coefficients by using Matlab 2015b, and then the Bit Error Rate (BER) performance has been evaluated for OFDM signal with 16-QAM and 64-QAM modulations in three cases, with nonlinear effects, without nonlinear effects (ideal case), with SCPWL and with nonlinear effects (compensated case)). The simulation results showed that the predistorter that adjusted by the genetic algorithm accomplishes huge execution change by successfully compensating the nonlinearity and reducing the input and output back-off (IBO, OBO) of the HPA.

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