Low-complexity Sub-band DPD with Sequential Learning: Novel Algorithms and WARPLab Implementation

Chance Tarver, Mahmoud Abdelaziz, Lauri Anttila, Mikko Valkama, Joseph Cavallaro

    Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

    3 Sitaatiot (Scopus)

    Abstrakti

    Digital predistortion (DPD) is an effective way of mitigating spurious emission violations without the need of a significant backoff in the transmitter, thus providing better power efficiency and network coverage. In this paper an iterative version of the IM3 sub-band DPD, proposed earlier by the authors, is presented. The DPD learning is iterated between the higher and lower IM3 sub-bands until a satisfactory performance is achieved for both of them. A sequential DPD learning procedure is also presented in order to reduce the hardware complexity when higher order nonlinearities are incorporated in the DPD learning. Improvements on the convergence speed of the adaptive DPD learning are also achieved via incorporating a variable learning rate and training from previous values. A WARPLab implementation of the proposed DPD is also shown with excellent suppression of the targeted spurious emissions.
    AlkuperäiskieliEnglanti
    OtsikkoIEEE International Workshop on Signal Processing Systems (SiPS), 2016
    KustantajaIEEE
    Sivut303-308
    Sivumäärä6
    ISBN (elektroninen)978-1-5090-3361-4
    DOI - pysyväislinkit
    TilaJulkaistu - 1 jouluk. 2016
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
    TapahtumaIEEE WORKSHOP ON SIGNAL PROCESSING SYSTEMS -
    Kesto: 1 tammik. 1900 → …

    Julkaisusarja

    Nimi
    ISSN (elektroninen)2374-7390

    Conference

    ConferenceIEEE WORKSHOP ON SIGNAL PROCESSING SYSTEMS
    Ajanjakso1/01/00 → …

    Julkaisufoorumi-taso

    • Jufo-taso 1

    !!ASJC Scopus subject areas

    • Engineering(all)
    • Computer Science(all)

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