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    A digital predistortion technique based on a NARX network to linearize GaN class F power amplifiers

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    Aguilar_14Aug_DPD_by_NARX.PDF (986.9Kb)
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    Date
    2014-08
    Author
    Aguilar-Lobo, Lina M.
    Rayas-Sánchez, José E.
    Loo-Yau, José R.
    Garcia-Osorio, Alberto
    Ortega-Cisneros, Susana
    Moreno, Pablo
    Reynoso-Hernández, Apolinar
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    Description
    This work presents a novel Digital Predistortion (DPD) scheme based on a NARX network, suitable for linearizing power amplifiers (PAs). The NARX network is a Recurrent Neural Network (RNN) with embedded memory that allows efficient modeling of nonlinear systems. Its neural architecture is very effective to model long term dependencies, such as the typical memory effects of PAs. To demonstrate the feasibility of the NARX network as a DPD system, a GaN class F PA with two LTE signals with 5 MHz of bandwidth is used. Experimental results show a distortion correction better than 10 dB.
    ITESO, A.C.
    CINVESTAV Guadalajara
    CICESE
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    © ITESO, Universidad Jesuita de Guadalajara 2022

    Sistemas de Información de la Dirección de Información Académica, DIA
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    © ITESO, Universidad Jesuita de Guadalajara 2022

    Sistemas de Información de la Dirección de Información Académica, DIA
    Biblioteca "Dr. Jorge Villalobos Padilla, S.J."

    Contact Us | Send Feedback