Mixture of Experts Neural Network for Modeling of Power Amplifiers

Arne Fischer-Bühner, Alberto Brihuega, Lauri Anttila, Manil Dev Gomony, Mikko Valkama

Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

1 Lataukset (Pure)

Abstrakti

A new Mixture of Experts Neural Network (ME-NN) approach is described and proposed for modeling of nonlinear RF power amplifiers (PAs). The proposed ME-NN is compared with various piece-wise polynomial models and the time-delay neural network (TDNN) regarding their ability to scale in terms of modeling accuracy and parameter count. To this end, measurements with GaN Doherty PA at 1.8 GHz and a load modulated balanced (LMBA) PA operating at 2.1 GHz with strong nonlinear behavior and dynamics are employed, assessing the potential benefits of ME-NN over the existing models. Implementation-related advantages of the proposed ME-NN over TDNNs at increasing network sizes are furthermore discussed. The measurement results show that the ME-NN approach offers increased modeling accuracy, particularly in the LMBA PA case, compared to the existing reference methods.

AlkuperäiskieliEnglanti
Otsikko2022 IEEE/MTT-S International Microwave Symposium, IMS 2022
KustantajaIEEE
Sivut510-513
Sivumäärä4
ISBN (elektroninen)9781665496131
ISBN (painettu)9781665496148
DOI - pysyväislinkit
TilaJulkaistu - 2022
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE/MTT-S International Microwave Symposium - Denver, Yhdysvallat
Kesto: 19 kesäk. 202224 kesäk. 2022

Julkaisusarja

NimiIEEE MTT-S International Microwave Symposium Digest
ISSN (painettu)0149-645X
ISSN (elektroninen)2576-7216

Conference

ConferenceIEEE/MTT-S International Microwave Symposium
Maa/AlueYhdysvallat
KaupunkiDenver
Ajanjakso19/06/2224/06/22

Julkaisufoorumi-taso

  • Jufo-taso 1

!!ASJC Scopus subject areas

  • Radiation
  • Condensed Matter Physics
  • Electrical and Electronic Engineering

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