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Massive MIMO for Communications With Drone Swarms
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-7599-4367
2018 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 3, p. 1604-1629Article in journal (Refereed) Published
Abstract [en]

We illustrate the potential of Massive MIMO for communication with unmanned aerial vehicles (UAVs). We consider a scenario, where multiple single-antenna UAVs simultaneously communicate with a ground station (GS) equipped with a large number of antennas. Specifically, we discuss the achievable uplink (UAV to GS) capacity performance in the case of line-of-sight conditions. We develop a realistic geometric model, which incorporates an arbitrary orientation, of the GS and UAV antenna elements to characterize the polarization mismatch loss, which occurs due to the movement and orientation of the UAVs. A closed-form expression for a lower bound on the ergodic rate for a maximum-ratio combining receiver with estimated channel state information is derived. The optimal antenna spacing that maximizes the ergodic rate achieved by an UAV is also determined for uniform linear and rectangular arrays. It is shown that when the UAVs are spherically uniformly distributed around the GS, the ergodic rate per UAV is maximized for an antenna spacing equal to an integer multiple of one-half wavelength.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2018. Vol. 17, no 3, p. 1604-1629
Keywords [en]
Unmanned aerial vehicles; Massive MIMO; ergodic capacity
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:liu:diva-147124DOI: 10.1109/TWC.2017.2782690ISI: 000427226500015OAI: oai:DiVA.org:liu-147124DiVA, id: diva2:1199523
Note

Funding Agencies|Swedish Research Council (VR); ELLIIT

Available from: 2018-04-20 Created: 2018-04-20 Last updated: 2018-06-13

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Chandhar, PrabhuDanev, DanyoLarsson, Erik G.

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