Deep neural network based digital predistorter of power amplifiers
dc.contributor.author | Olcay Güneş, Ece | |
dc.contributor.author | Ozoğuz, Serdar | |
dc.date.accessioned | 2022-03-22T06:19:17Z | |
dc.date.available | 2022-03-22T06:19:17Z | |
dc.date.issued | 2021 | en_US |
dc.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü | en_US |
dc.description.abstract | We show how to address nonlinearities in power amplifiers (PAs), which limit the power efficiency of mobile devices, increase the error vector magnitude, using an deep neural-network (DNN) method. DPD is frequently performed using polynomial-based algorithms that employ an indirect-learning architecture (ILA), which can be computationally complex, particularly on mobile devices, and highly sensitive to noise. By first training a DNN to model the PA and then training a predistorter using PA data through the PA DNN model. The DNN DPD successfully learns the unique PA distortions that a polynomial-based model may struggle to fit, and therefore may provide a nice balance between computation cost and DPD efficiency. We use two different DNN models to show the performance of our DNN approach and examine the complexity tradeoffs. | en_US |
dc.identifier.citation | Daylak, F., Gunes, E. O., Bayat, O., & Ozoguz, S. (2021, November). Deep Neural Network Based Digital Predistorter of Power Amplifiers. In 2021 13th International Conference on Electrical and Electronics Engineering (ELECO) (408-410). IEEE. | en_US |
dc.identifier.endpage | 410 | en_US |
dc.identifier.isbn | 978-605011437-9 | |
dc.identifier.scopus | 2-s2.0-85125264304 | |
dc.identifier.scopusquality | N/A | |
dc.identifier.startpage | 408 | en_US |
dc.identifier.uri | https://hdl.handle.net/20.500.12939/2299 | |
dc.indekslendigikaynak | Scopus | |
dc.institutionauthor | Daylak, Funda | |
dc.institutionauthor | Bayat, Oğuz | |
dc.language.iso | en | |
dc.relation.ispartof | 2021 13th International Conference on Electrical and Electronics Engineering, ELECO 2021 | |
dc.relation.isversionof | 10.23919/ELECO54474.2021.9677871 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Ulusal - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | DNN | en_US |
dc.subject | DPD | en_US |
dc.subject | PA | en_US |
dc.title | Deep neural network based digital predistorter of power amplifiers | |
dc.type | Conference Object |
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