  Unmanned aerial vehicles (UAVs) have gained popularity in the communications
research community because of their versatility in placement and potential to
extend the functions of communication networks. However, there remains still a
gap in existing works regarding detailed and measurement-verified air-to-ground
(A2G) Massive Multi-Input Multi-Output (MaMIMO) channel characteristics which
play an important role in realistic deployment. In this paper, we first design
a UAV MaMIMO communication platform for channel acquisition. We then use the
testbed to measure uplink Channel State Information (CSI) between a rotary-wing
drone and a 64-element MaMIMO base station (BS). For characterization, we focus
on multidimensional channel stationarity which is a fundamental metric in
communication systems. Afterward, we present measurement results and analyze
the channel statistics based on power delay profiles (PDPs) considering space,
time, and frequency domains. We propose the stationary angle (SA) as a
supplementary metric of stationary distance (SD) in the time domain. We analyze
the coherence bandwidth and RMS delay spread for frequency stationarity.
Finally, spatial correlations between elements are analyzed to indicate the
spatial stationarity of the array. The space-time-frequency channel stationary
characterization will benefit the physical layer design of MaMIMO-UAV
communications.

Networking and Internet Architecture;Signal Processing