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A FAIR AND SCALABLE POWER CONTROL SCHEME IN MULTI-CELL MASSIVE MIMO
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-0581-1235
Univ Toronto, Canada.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-5954-434X
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-7599-4367
2019 (English)In: 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE , 2019, p. 4499-4503Conference paper, Published paper (Refereed)
Abstract [en]

This paper studies the transmit power optimization in a multi-cell massive multiple-input multiple-output (MIMO) system. To overcome the scalability issue of network-wide max-min fairness (NW-MMF), we propose a novel power control (PC) scheme. This scheme maximizes the geometric mean (GM) of the per-cell max-min spectral efficiency (SE). To solve this new optimization problem, we prove that it can be rewritten in a convex form and then solved using standard tools. To provide a fair comparison with the available utility functions in the literature, we solve the network-wide proportional fairness (NW-PE) PC as well. The NW-PE focuses on maximizing the sum SE, thereby ignoring fairness, but gives some extra attention to the weakest users. The simulation results highlight the benefits of our model which is balancing between NW-PE and NW-MMF.

Place, publisher, year, edition, pages
IEEE , 2019. p. 4499-4503
Series
International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
Keywords [en]
Massive MIMO; power control; max-min fairness; proportional fairness
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:liu:diva-160636DOI: 10.1109/ICASSP.2019.8682872ISI: 000482554004147ISBN: 978-1-4799-8131-1 (electronic)OAI: oai:DiVA.org:liu-160636DiVA, id: diva2:1360190
Conference
44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Note

Funding Agencies|ELLIIT; European Unions Horizon 2020 research and innovation programme [641985]

Available from: 2019-10-11 Created: 2019-10-11 Last updated: 2019-10-11

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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More styles
Language
  • de-DE
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  • nn-NB
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  • Other locale
More languages
Output format
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