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Massive MIMO in Real Propagation Environments: Do All Antennas Contribute Equally?
Lund University, Sweden.
Lund University, Sweden.
Lund University, Sweden.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-7599-4367
2015 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 63, no 11, 3917-3928 p.Article in journal (Refereed) PublishedText
Abstract [en]

Massive MIMO can greatly increase both spectral and transmit-energy efficiency. This is achieved by allowing the number of antennas and RF chains to grow very large. However, the challenges include high system complexity and hardware energy consumption. Here we investigate the possibilities to reduce the required number of RF chains, by performing antenna selection. While this approach is not a very effective strategy for theoretical independent Rayleigh fading channels, a substantial reduction in the number of RF chains can be achieved for real massive MIMO channels, without significant performance loss. We evaluate antenna selection performance on measured channels at 2.6 GHz, using a linear and a cylindrical array, both having 128 elements. Sum-rate maximization is used as the criterion for antenna selection. A selection scheme based on convex optimization is nearly optimal and used as a benchmark. The achieved sum-rate is compared with that of a very simple scheme that selects the antennas with the highest received power. The power-based scheme gives performance close to the convex optimization scheme, for the measured channels. This observation indicates a potential for significant reductions of massive MIMO implementation complexity, by reducing the number of RF chains and performing antenna selection using simple algorithms.

Place, publisher, year, edition, pages
Keyword [en]
Massive MIMO; antenna selection; spatial diversity; large-scale fading; channel measurements
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:liu:diva-123814DOI: 10.1109/TCOMM.2015.2462350ISI: 000366506500002OAI: diva2:892899

Funding Agencies|European Union [619086]; ELLIIT-an Excellence Center at Linkoping-Lund in Information Technology; Swedish Research Council (VR); Swedish Foundation for Strategic Research (SSF)

Available from: 2016-01-11 Created: 2016-01-11 Last updated: 2016-08-31

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Larsson, Erik G
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