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Massive MIMO Systems With Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits
KTH, School of Electrical Engineering (EES), Signal Processing. Linköping University, Sweden.
2014 (English)In: IEEE Transactions on Information Theory, ISSN 0018-9448, Vol. 60, no 11, 7112-7139 p.Article in journal (Refereed) Published
Abstract [en]

The use of large-scale antenna arrays can bring substantial improvements in energy and/or spectral efficiency to wireless systems due to the greatly improved spatial resolution and array gain. Recent works in the field of massive multiple-input multiple-output (MIMO) show that the user channels decorrelate when the number of antennas at the base stations (BSs) increases, thus strong signal gains are achievable with little interuser interference. Since these results rely on asymptotics, it is important to investigate whether the conventional system models are reasonable in this asymptotic regime. This paper considers a new system model that incorporates general transceiver hardware impairments at both the BSs (equipped with large antenna arrays) and the single-antenna user equipments (UEs). As opposed to the conventional case of ideal hardware, we show that hardware impairments create finite ceilings on the channel estimation accuracy and on the downlink/uplink capacity of each UE. Surprisingly, the capacity is mainly limited by the hardware at the UE, while the impact of impairments in the large-scale arrays vanishes asymptotically and interuser interference (in particular, pilot contamination) becomes negligible. Furthermore, we prove that the huge degrees of freedom offered by massive MIMO can be used to reduce the transmit power and/or to tolerate larger hardware impairments, which allows for the use of inexpensive and energy-efficient antenna elements.

Place, publisher, year, edition, pages
2014. Vol. 60, no 11, 7112-7139 p.
Keyword [en]
Capacity bounds, channel estimation, energy efficiency, massive MIMO, pilot contamination, time-division duplex, transceiver hardware impairments
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Signal Processing
URN: urn:nbn:se:kth:diva-157604DOI: 10.1109/TIT.2014.2354403ISI: 000344524100028ScopusID: 2-s2.0-84908222752OAI: diva2:771189
EU, European Research CouncilEU, FP7, Seventh Framework Programme, 265578Swedish Research Council, 2012-228

QC 20141212

Available from: 2014-12-12 Created: 2014-12-11 Last updated: 2014-12-12Bibliographically approved

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