Reduced-Complexity Polynomials with Memory Applied to the Linearization of Power Amplifiers with Real-Time Discrete Gain Control.
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| Title: | Reduced-Complexity Polynomials with Memory Applied to the Linearization of Power Amplifiers with Real-Time Discrete Gain Control. |
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| Authors: | Schuartz, Luis1 (AUTHOR) luisschuartz@ufpr.br, Santos, Edson L.1 (AUTHOR) edson_l@hotmail.com, Leite, Bernardo1 (AUTHOR) leite@ufpr.br, Mariano, André A.1 (AUTHOR) mariano@ufpr.br, Lima, Eduardo G.1 (AUTHOR) elima@eletrica.ufpr.br |
| Source: | Circuits, Systems & Signal Processing. Sep2019, Vol. 38 Issue 9, p3901-3930. 30p. |
| Subjects: | Power amplifiers, Electronic linearization, Reduced-order models, Polynomials, Memory, Radio frequency |
| Abstract: | In reconfigurable power amplifiers (PAs), the efficiency can be improved by dynamically switching the discrete gain mode according to the input envelope amplitude. Nevertheless, discontinuities that occur between gain mode changes critically compromise the linearization capability of traditional digital baseband predistorters (DPDs) based on continuous polynomials with memory. To circumvent such drawback, this work introduces a model based on polynomials bounded at both sides and able to take into account commutation delays. Besides, two novel approaches are presented to the model order reduction without basis change. The effectiveness of the proposed approaches to linearize a 130 nm CMOS class AB PA commutating in real time among three gain modes is certified based on Cadence Virtuoso and Matlab simulations. The proposed memory polynomial-based model was able to accurately model both direct and inverse transfer characteristics of a three gain mode PA, showing normalized mean square error results of about − 41 dB. Besides, a 25.5 dB reduction in adjacent channel power ratio is provided by the inclusion of a 10 parameters DPD that adopts the proposed approaches, in comparison with unlinearized PA of same output mean power. [ABSTRACT FROM AUTHOR] |
| Copyright of Circuits, Systems & Signal Processing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 137848194 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Reduced-Complexity Polynomials with Memory Applied to the Linearization of Power Amplifiers with Real-Time Discrete Gain Control. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Schuartz%2C+Luis%22">Schuartz, Luis</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> luisschuartz@ufpr.br</i><br /><searchLink fieldCode="AR" term="%22Santos%2C+Edson+L%2E%22">Santos, Edson L.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> edson_l@hotmail.com</i><br /><searchLink fieldCode="AR" term="%22Leite%2C+Bernardo%22">Leite, Bernardo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> leite@ufpr.br</i><br /><searchLink fieldCode="AR" term="%22Mariano%2C+André+A%2E%22">Mariano, André A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mariano@ufpr.br</i><br /><searchLink fieldCode="AR" term="%22Lima%2C+Eduardo+G%2E%22">Lima, Eduardo G.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> elima@eletrica.ufpr.br</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Circuits%2C+Systems+%26+Signal+Processing%22">Circuits, Systems & Signal Processing</searchLink>. Sep2019, Vol. 38 Issue 9, p3901-3930. 30p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Power+amplifiers%22">Power amplifiers</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+linearization%22">Electronic linearization</searchLink><br /><searchLink fieldCode="DE" term="%22Reduced-order+models%22">Reduced-order models</searchLink><br /><searchLink fieldCode="DE" term="%22Polynomials%22">Polynomials</searchLink><br /><searchLink fieldCode="DE" term="%22Memory%22">Memory</searchLink><br /><searchLink fieldCode="DE" term="%22Radio+frequency%22">Radio frequency</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In reconfigurable power amplifiers (PAs), the efficiency can be improved by dynamically switching the discrete gain mode according to the input envelope amplitude. Nevertheless, discontinuities that occur between gain mode changes critically compromise the linearization capability of traditional digital baseband predistorters (DPDs) based on continuous polynomials with memory. To circumvent such drawback, this work introduces a model based on polynomials bounded at both sides and able to take into account commutation delays. Besides, two novel approaches are presented to the model order reduction without basis change. The effectiveness of the proposed approaches to linearize a 130 nm CMOS class AB PA commutating in real time among three gain modes is certified based on Cadence Virtuoso and Matlab simulations. The proposed memory polynomial-based model was able to accurately model both direct and inverse transfer characteristics of a three gain mode PA, showing normalized mean square error results of about − 41 dB. Besides, a 25.5 dB reduction in adjacent channel power ratio is provided by the inclusion of a 10 parameters DPD that adopts the proposed approaches, in comparison with unlinearized PA of same output mean power. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Circuits, Systems & Signal Processing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00034-019-01049-6 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 30 StartPage: 3901 Subjects: – SubjectFull: Power amplifiers Type: general – SubjectFull: Electronic linearization Type: general – SubjectFull: Reduced-order models Type: general – SubjectFull: Polynomials Type: general – SubjectFull: Memory Type: general – SubjectFull: Radio frequency Type: general Titles: – TitleFull: Reduced-Complexity Polynomials with Memory Applied to the Linearization of Power Amplifiers with Real-Time Discrete Gain Control. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Schuartz, Luis – PersonEntity: Name: NameFull: Santos, Edson L. – PersonEntity: Name: NameFull: Leite, Bernardo – PersonEntity: Name: NameFull: Mariano, André A. – PersonEntity: Name: NameFull: Lima, Eduardo G. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2019 Type: published Y: 2019 Identifiers: – Type: issn-print Value: 0278081X Numbering: – Type: volume Value: 38 – Type: issue Value: 9 Titles: – TitleFull: Circuits, Systems & Signal Processing Type: main |
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