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    Estimation of Sparse Memory Taps for RF Power Amplifier Behavioral Models


    Dooley, John and O'Brien, Bill and Finnerty, Keith and Farrell, Ronan (2015) Estimation of Sparse Memory Taps for RF Power Amplifier Behavioral Models. IEEE Microwave and Wireless Components Letters, 25 (1). pp. 64-66. ISSN 1531-1309

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    Abstract

    When a larger than required dimension such as memory depth or order of nonlinearity, is specified during behavioral model extraction, redundant terms can be calculated when determining the weights of the model. Extraction of a behavioral model can therefore benefit from a priori knowledge of the system to be modeled. Conversely if there is a limitation in the hardware required to calculate model outputs a limit can be set for the maximum number of weights to be used. In this letter, an approach is proposed which allows the input delay vector to be reduced to a sparse vector including the delayed samples which are most important in the construction of the power amplifier model. Simulations of behavioral models for experimentally measured data of two different PAs demonstrates the sparse models extracted in this way are as accurate as a full model but have a more compact and as a result more computationally efficient structure.

    Item Type: Article
    Additional Information: This work was supported in part by the Science Foundation Ireland under Grant 10/CE/ I1853 and by HEA under PRTLI5 and is being co-funded by the Irish Government and the EU under Ireland’s Structural Funds Programmes 2007-2013: Investing in your future.
    Keywords: Active antenna arrays; behavioral modeling; memory effect, power amplifier (PA); Volterra series;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Item ID: 9575
    Identification Number: https://doi.org/10.1109/LMWC.2014.2361678
    Depositing User: Dr. Ronan Farrell
    Date Deposited: 20 Jun 2018 14:43
    Journal or Publication Title: IEEE Microwave and Wireless Components Letters
    Publisher: IEEE
    Refereed: Yes
    Funders: Science Foundation Ireland (SFI), Higher Education Authority (HEA), Ireland Structural Funds Programmes 2007-2013
    URI:

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