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Distributed Power Control in Downlink Cellular Massive MIMO Systems
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
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
Department of Design Engineering & Maths, Middlesex University London, United Kingdom.
2018 (English)In: WSA 2018: 22nd International ITG Workshop on Smart Antennas, VDE Verlag GmbH, 2018, p. 1-7Conference paper, Published paper (Refereed)
Abstract [en]

This paper compares centralized and distributed methods to solve the power minimization problem with quality-of-service (QoS) constraints in the downlink (DL) of multi-cell Massive multiple-input multiple-output (MIMO) systems. In particular, we study the computational complexity, number of parameters that need to be exchanged between base stations (BSs), and the convergence of iterative implementations. Although a distributed implementation based on dual decomposition (which only requires statistical channel knowledge at each BS) typically converges to the global optimum after a few iterations, many parameters need to be exchanged to reach convergence.

Place, publisher, year, edition, pages
VDE Verlag GmbH, 2018. p. 1-7
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:liu:diva-148936ISBN: 978-3-8007-4541-8 (print)OAI: oai:DiVA.org:liu-148936DiVA, id: diva2:1222787
Conference
IEEE 22nd International ITG Workshop on Smart Antennas (WSA2018)
Projects
5GwirelessELLIITCENIITAvailable from: 2018-06-22 Created: 2018-06-22 Last updated: 2019-06-28

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Van Chien, TrinhBjörnson, EmilLarsson, Erik G.

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