Digital predistortion (DPD) technique has already been studied and applied in traditional SISO system. However, when it comes to multiple-input multiple- output (MIMO) systems, new problems such as crosstalk effects must be taken into consideration. In this paper, we propose a neural network based DPD scheme assisted by iterative learning control (ILC) for MIMO system. The proposed method uses direct learning architecture in DPD and can combat nonlinear crosstalk effects. Simulation results show that the proposed method achieves similar or even better performance than the existing polynomial based approach in the presence of nonlinear crosstalk. In addition, the proposed method is computational efficient and is easier for implementation.


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    Title :

    Iterative Learning Control Assisted Neural Network for Digital Predistortion of MIMO Power Amplifier


    Contributors:
    Li, Kenan (author) / Guan, Ning (author) / Wang, Hua (author)


    Publication date :

    2018-06-01


    Size :

    838355 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English