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Massive MIMO systems with hardware-constrained base stations
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. SUPELEC, France .
2014 (English)Conference paper (Refereed)
Abstract [en]

Massive multiple-input multiple-output (MIMO) systems are cellular networks where the base stations (BSs) are equipped with unconventionally many antennas. Such large antenna arrays offer huge spatial degrees-of-freedom for transmission optimization; in particular, great signal gains, resilience to imperfect channel knowledge, and small inter-user interference are all achievable without extensive inter-cell coordination. The key to cost-efficient deployment of large arrays is the use of hardware-constrained base stations with low-cost antenna elements, as compared to today's expensive and power-hungry BSs. Low-cost transceivers are prone to hardware imperfections, but it has been conjectured that the excessive degrees-of-freedom of massive MIMO would bring robustness to such imperfections. We herein prove this claim for an uplink channel with multiplicative phase-drift, additive distortion noise, and noise amplification. Specifically, we derive a closed-form scaling law that shows how fast the imperfections increase with the number of antennas.

Place, publisher, year, edition, pages
2014. 3142-3146 p.
, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, ISSN 1520-6149 ; 6854179
Keyword [en]
Achievable uplink rates, channel estimation, massive MIMO, scaling laws, transceiver hardware imperfections, Acoustic noise, Amplification, Antenna arrays, Base stations, Degrees of freedom (mechanics), MIMO systems, Transceivers, Additive distortion, Cellular network, Imperfect channel knowledge, Inter-cell coordinations, Inter-user interference, Multiple-input-multiple-output systems, Noise amplification, Transceiver hardware, Hardware
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-167605DOI: 10.1109/ICASSP.2014.6854179ISI: 000343655303035ScopusID: 2-s2.0-84905216547ISBN: 9781479928927OAI: diva2:814842
2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, 4 May 2014 through 9 May 2014, Florence

QC 20150528

Available from: 2015-05-28 Created: 2015-05-22 Last updated: 2015-05-28Bibliographically approved

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Björnson, Emil
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