Chebyshev Functional Link Neural Network integrating FIR Filter Architecture for Power Amplifier Linearization

Chebyshev polynomial functional link neural networks (FLNN) integrating FIR filter architecture for power amplifier linearization is proposed. Furthermore, considering the system implementation and resources, we simplify the Chebyshev polynomials in the actual realization on the premise of guarantee...

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Bibliographic Details
Published in2022 IEEE International Conference on Consumer Electronics (ICCE) pp. 1 - 5
Main Authors Ren, Jijun, Song, Qiushuang, Wang, Xing, Yang, Xinrong
Format Conference Proceeding
LanguageEnglish
Published IEEE 07.01.2022
Subjects
adaptive digital predistorter
Chebyshev approximation
Chebyshev orthogonal polynomial
Computer architecture
Finite impulse response filters
Functional link neural network
Neural networks
power amplifier linearization
Power amplifiers
Software
Software algorithms
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Summary:Chebyshev polynomial functional link neural networks (FLNN) integrating FIR filter architecture for power amplifier linearization is proposed. Furthermore, considering the system implementation and resources, we simplify the Chebyshev polynomials in the actual realization on the premise of guaranteeing the fitting accuracy. Experimental results on High-Frequency (HF) Power Amplifier (PA) of actual short-wave communication and the software simulation of dual carrier LTE signal show that more accurate linearization results can be obtained by using the proposed method.
ISSN:2158-4001
DOI:10.1109/ICCE53296.2022.9730573