This paper proposes a predistortion scheme based on an orthogonal hidden layer feedforward neural network for reducing nonlinear distortion introduced by a traveling wave tube amplifier (TWTA) over orthogonal frequency division multiplexing (OFDM) signals. In predistorter, the inputs weight are fixed and based on this the output weights are analytically determined. Computer simulation results confirm that once the 16QAM-OFDM signals are predistorted and amplified at an input back-off level of 0 dB there is a bit error rate performance very close to the ideal case of linear amplification.


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    Titel :

    Orthogonal Neural Network Based Predistortion for OFDM Systems


    Beteiligte:


    Erscheinungsdatum :

    01.09.2007


    Format / Umfang :

    259158 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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