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Downlink Power Control in Massive MIMO Networks with Distributed Antenna Arrays
Australian Natl Univ, Australia.
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
Australian Natl Univ, Australia.
2018 (English)In: 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), IEEE, 2018Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we investigate downlink power control in massive multiple-input multiple-output (MIMO) networks with distributed antenna arrays. The base station (BS) in each cell consists of multiple antenna arrays, which are deployed in arbitrary locations within the cell. Due to the spatial separation between antenna arrays, the large-scale propagation effect is different from a user to different antenna arrays in a cell, which makes power control a challenging problem as compared to conventional massive MIMO. We assume that the BS in each cell obtains the channel estimates via uplink pilots. Based on the channel estimates, the BSs perform maximum ratio transmission for the downlink. We then derive a closed-form spectral efficiency (SE) expression, where the channels are subject to correlated fading. Utilizing the derived expression, we propose a max-min power control algorithm to ensure that each user in the network receives a uniform quality of service. Numerical results demonstrate that, for the network considered in this work, optimizing for max-min SE through the max-min power control improves the sum SE of the network as compared to the equal power allocation.

Place, publisher, year, edition, pages
IEEE, 2018.
Series
IEEE International Conference on Communications, E-ISSN 1938-1883
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:liu:diva-169791DOI: 10.1109/ICC.2018.8422458ISI: 000519271302069ISBN: 978-1-5386-3180-5 (electronic)ISBN: 978-1-5386-3181-2 (print)OAI: oai:DiVA.org:liu-169791DiVA, id: diva2:1468911
Conference
IEEE International Conference on Communications (ICC) / Workshop on Integrating UAVs into 5G, Kansas City, MO, may 20-24, 2018
Note

Funding Agencies|Australian Government Research Training Program (RTP) ScholarshipAustralian GovernmentDepartment of Industry, Innovation and Science; ARC Discovery ProjectAustralian Research Council [DP180104062]; Swedish Research Council (VR)Swedish Research Council; ELLIIT

Available from: 2020-09-18 Created: 2020-09-18 Last updated: 2020-09-18

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
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  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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