User Scheduling and Antenna Topology in Dense Massive MIMO Networks

An Experimental Study

Journal Article (2020)
Author(s)

Cheng Ming Wang (Katholieke Universiteit Leuven)

Qing Wang (TU Delft - Embedded Systems)

Abdo Gaber (National Instruments)

Andrea P. Guevara (Katholieke Universiteit Leuven)

Sofie Pollin (Katholieke Universiteit Leuven)

DOI related publication
https://doi.org/10.1109/TWC.2020.3001224 Final published version
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Publication Year
2020
Language
English
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Journal title
IEEE Transactions on Wireless Communications
Issue number
9
Volume number
19
Article number
9119873
Pages (from-to)
6210-6223
Downloads counter
138
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Institutional Repository
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Abstract

A massive MIMO network can serve ten's of users simultaneously. However, in dense scenarios the users are potentially closely-spaced, potentially resulting in substantial inter-user interference. Scheduling can overcome this by selecting the users that lead to the highest combined spectral efficiency. As scheduling comes with a significant pilot overhead, an alternative strategy could minimize user correlation by distributing the antenna elements in space. In this paper, we propose a comprehensive system study including antenna topology and distribution, user scheduling and pilot overhead reduction. Our user scheduling and pilot reduction algorithms are evaluated using system level simulations relying on indoor line-of-sight channel measurements from a 64 antenna base station at 2.61GHz. To have a thorough evaluation of the proposed algorithm, we consider four different antenna topologies, including co-located and distributed placement of the base station arrays. Our evaluation shows that in a conference room with 64 densely deployed users, our proposed low complexity algorithm can improve the spectral efficiency by at least 14% compared to random user selection with the best antenna distribution strategy. Finally, our results show that by relying on channel hardening, we reduce the pilot overhead by 3.2 \times.

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