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MIMO Subband Volterra Digital Predistortion for Concurrent Aggregated Carrier Communications
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics. Department of Signal Processing, KTH Royal Institute of Technology, Stockholm, Sweden; Electron- ics and Telecommunication Department, Universidad Catolica San Pablo, Arequipa, Peru.ORCID iD: 0000-0001-8460-6509
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.ORCID iD: 0000-0003-2887-049x
2017 (English)In: IEEE transactions on microwave theory and techniques, ISSN 0018-9480, E-ISSN 1557-9670, Vol. 65, no 3, p. 967-979Article in journal (Refereed) Published
Abstract [en]

This paper presents a multiple-input multiple-output (MIMO) nonlinear mitigation technique for closely spaced concurrent aggregated carrier systems. The transmitter architecture considers band-limited sources, where the predistorter and signal bandwidth are the same, thus reducing transmitter hardware cost and power consumption. The technique relies on multirate processing and linear filtering and uses the carrier frequencies to isolate the contribution of linear and nonlinear basis functions to the desired bands. This approach can be used with any MIMO model structure. In particular, models are linear in the parameters of low computational complexity. The technique was evaluated using three concurrent carriers of 50 MHz each fed to a Doherty amplifier. The results show significant reduction in the error vector magnitude and improvements for the transmitter efficiency using the proposed compensation technique.

Place, publisher, year, edition, pages
2017. Vol. 65, no 3, p. 967-979
Keywords [en]
Volterra, Concurrent, digital predistortion (DPD), memory polynomials, MIMO, multiband, multiple-input multiple-output (MIMO) predistortion, power amplifier linearization, power amplifiers
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Intelligent Industry
Identifiers
URN: urn:nbn:se:hig:diva-23800DOI: 10.1109/TMTT.2016.2630066ISI: 000396393000029Scopus ID: 2-s2.0-85009892701OAI: oai:DiVA.org:hig-23800DiVA, id: diva2:1083851
Available from: 2017-03-22 Created: 2017-03-22 Last updated: 2022-09-19Bibliographically approved

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Zenteno, EfrainRönnow, Daniel

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