Mixture of Experts Approach for Piecewise Modeling and Linearization of RF Power Amplifiers

DC FieldValueLanguage
dc.contributor.authorBrihuega, Alberto-
dc.contributor.authorAbdelaziz, Mahmoud-
dc.contributor.authorAnttila, Lauri-
dc.contributor.authorLi, Yue-
dc.contributor.authorZhu, Anding-
dc.contributor.authorValkama, Mikko-
dc.date.accessioned2021-08-09T11:54:13Z-
dc.date.available2021-08-09T11:54:13Z-
dc.date.copyright2021 IEEEen_US
dc.date.issued2022-01-
dc.identifier.citationIEEE Transactions on Microwave Theory and Techniquesen_US
dc.identifier.issn0018-9480-
dc.identifier.urihttp://hdl.handle.net/10197/12388-
dc.description.abstractPiecewise behavioral models are commonly adopted for modeling and linearization of RF power amplifiers (PAs) that exhibit strong amplitude-dependent nonlinear distortion characteristics, as global polynomial approximations tend to underperform in such scenarios. In this article, we consider a new piecewise model for PAs based on the mixture of experts (ME) approach, which builds on a probabilistic model that allows the different submodels to cooperate--as opposed to operating in an independent fashion that is commonly the case in existing reference methods. We first introduce the ME framework theory while also extend it such that it can be applied to model complex baseband signals and nonlinearities. Then, we show how the ME model allows overcoming some of the intrinsic shortcomings that existing piecewise behavioral models commonly exhibit, which translates into improved modeling accuracy and improved linearization performance. Furthermore, the extension of the ME approach to a tree-structured regression model, referred to as the hierarchical ME model, is also introduced and shown to provide further performance improvements over the basic ME approach. The proposed solutions are validated with extensive RF measurements, covering both PA direct modeling and digital predistortion (DPD)-based linearization, on a gallium nitride (GaN) load-modulated balanced PA, on a GaN Doherty PA, and on a class AB GaN high electron mobility transistor PA, while being compared against several state-of-the-art piecewise methods. The results demonstrate that the ME framework-based models outperform the state of the art.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.rights© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.subjectBehavioral modelingen_US
dc.subjectDigital predistortion (DPD)en_US
dc.subject5G New Radio (NR)en_US
dc.subjectMixture of experts (ME)en_US
dc.subjectNonlinear distortionen_US
dc.subjectPiecewise modelsen_US
dc.subjectPower amplifiers (PAs)en_US
dc.titleMixture of Experts Approach for Piecewise Modeling and Linearization of RF Power Amplifiersen_US
dc.typeJournal Articleen_US
dc.internal.authorcontactotheranding.zhu@ucd.ieen_US
dc.statusPeer revieweden_US
dc.identifier.volume70en_US
dc.identifier.issue1en_US
dc.identifier.startpage380en_US
dc.identifier.endpage391en_US
dc.identifier.doi10.1109/tmtt.2021.3098867-
dc.neeo.contributorBrihuega|Alberto|aut|-
dc.neeo.contributorAbdelaziz|Mahmoud|aut|-
dc.neeo.contributorAnttila|Lauri|aut|-
dc.neeo.contributorLi|Yue|aut|-
dc.neeo.contributorZhu|Anding|aut|-
dc.neeo.contributorValkama|Mikko|aut|-
dc.description.othersponsorshipAcademy of Finlanden_US
dc.description.othersponsorshipNokia Bell Labsen_US
dc.description.othersponsorshipTampere Universityen_US
dc.date.updated2021-08-02T16:33:50Z-
dc.rights.licensehttps://creativecommons.org/licenses/by-nc-nd/3.0/ie/en_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
Appears in Collections:Electrical and Electronic Engineering Research Collection
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