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MIMO and Massive MIMO Transmitter Crosstalk
KTH.
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Electronics.ORCID iD: 0000-0003-2887-049x
2020 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 19, no 3, p. 1882-1893Article in journal (Refereed) Published
Abstract [en]

The effects of hardware-induced crosstalk in MIMO transmitters, subject to nonlinear power amplifier distortion, are considered in this paper. A methodology that provides tractable results and a clear understanding of the effects of crosstalk on transmitter performance is introduced and applied to different transmitter models. In particular, a physically motivated 2×2 MIMO transmitter model, which is subjected to input and output crosstalk, is studied in detail, as well as a behavior motivated transmitter model, which is subjected to linear crosstalk. For the latter structure, asymptotic results, when the number of transmitters tends to infinity, are derived. These results provide insight into different 1D and 2D transmitter structures in the massive MIMO scenario. The methodology provides tractable analytical results of the performance of the transmitter. It is shown that the transmitter crosstalk degrades the performance in terms of normalized mean squared error with 3 dB going from a 2×2 set-up to a 1D array of a massive amount of transmitters, and an additional 3 dB loss going from a 1D to 2D transmitter structure. Transmitter input power back-off optimization is further studied, with back-off determination that takes the effects of MIMO crosstalk into account in order to increase the energy efficiency of the transmitter.

Place, publisher, year, edition, pages
IEEE, 2020. Vol. 19, no 3, p. 1882-1893
Keywords [en]
Orthogonal frequency division multiplexing (OFDM), input back-off, massive MIMO, power amplifier, transmitter hardware imperfections
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Intelligent Industry
Identifiers
URN: urn:nbn:se:hig:diva-31379DOI: 10.1109/TWC.2019.2959534ISI: 000521186100030Scopus ID: 2-s2.0-85081726843OAI: oai:DiVA.org:hig-31379DiVA, id: diva2:1383059
Available from: 2020-01-07 Created: 2020-01-07 Last updated: 2020-11-23Bibliographically approved

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Rönnow, Daniel

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CiteExportLink to record
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  • apa
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