Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario

Abstract The performance of centralized and distributed massive MIMO deployments are studied for simulated indoor office scenarios. The distributed deployments use one of the following precoding methods: (1) local precoding with local channel state information (CSI) to the user equipments (UEs) that...

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Main Authors: Stefan Dierks, Gerhard Kramer, Berthold Panzner, Wolfgang Zirwas
Format: Article
Language:English
Published: SpringerOpen 2020-01-01
Series:EURASIP Journal on Wireless Communications and Networking
Subjects:
5G
Online Access:https://doi.org/10.1186/s13638-019-1636-5
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spelling doaj-359cd934879541f38b0dbfff15be098c2021-01-24T12:26:02ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14992020-01-012020111210.1186/s13638-019-1636-5Information rates of precoding for massive MIMO and base station cooperation in an indoor scenarioStefan Dierks0Gerhard Kramer1Berthold Panzner2Wolfgang Zirwas3ROHDE & SCHWARZ GmbH & Co. KGChair for Communications Engineering, Technical University of MunichNokia NetworksNokia NetworksAbstract The performance of centralized and distributed massive MIMO deployments are studied for simulated indoor office scenarios. The distributed deployments use one of the following precoding methods: (1) local precoding with local channel state information (CSI) to the user equipments (UEs) that it serves, (2) large-scale MIMO with local CSI to all UEs in the network, (3) network MIMO with global CSI. For the distributed deployment (3), it is found that using twice as many base station antennas as data streams provides many of the massive MIMO benefits in terms of spectral efficiency and fairness. This is in contrast to the centralized and distributed deployments using (1) or (2) where more antennas are needed. Two main conclusions are that distributing base stations helps to overcome wall penetration loss; however, a backhaul is required to mitigate inter-cell interference. The effect of estimation errors on the performance is also quantified.https://doi.org/10.1186/s13638-019-1636-5Mobile radio communication5GIndoor communicationMassive MIMONetwork MIMOBase station cooperation
collection DOAJ
language English
format Article
sources DOAJ
author Stefan Dierks
Gerhard Kramer
Berthold Panzner
Wolfgang Zirwas
spellingShingle Stefan Dierks
Gerhard Kramer
Berthold Panzner
Wolfgang Zirwas
Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario
EURASIP Journal on Wireless Communications and Networking
Mobile radio communication
5G
Indoor communication
Massive MIMO
Network MIMO
Base station cooperation
author_facet Stefan Dierks
Gerhard Kramer
Berthold Panzner
Wolfgang Zirwas
author_sort Stefan Dierks
title Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario
title_short Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario
title_full Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario
title_fullStr Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario
title_full_unstemmed Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario
title_sort information rates of precoding for massive mimo and base station cooperation in an indoor scenario
publisher SpringerOpen
series EURASIP Journal on Wireless Communications and Networking
issn 1687-1499
publishDate 2020-01-01
description Abstract The performance of centralized and distributed massive MIMO deployments are studied for simulated indoor office scenarios. The distributed deployments use one of the following precoding methods: (1) local precoding with local channel state information (CSI) to the user equipments (UEs) that it serves, (2) large-scale MIMO with local CSI to all UEs in the network, (3) network MIMO with global CSI. For the distributed deployment (3), it is found that using twice as many base station antennas as data streams provides many of the massive MIMO benefits in terms of spectral efficiency and fairness. This is in contrast to the centralized and distributed deployments using (1) or (2) where more antennas are needed. Two main conclusions are that distributing base stations helps to overcome wall penetration loss; however, a backhaul is required to mitigate inter-cell interference. The effect of estimation errors on the performance is also quantified.
topic Mobile radio communication
5G
Indoor communication
Massive MIMO
Network MIMO
Base station cooperation
url https://doi.org/10.1186/s13638-019-1636-5
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