  Massive multiple-input multiple-output (MIMO) is a promising technology for
enabling cellular-connected unmanned aerial vehicle (UAV) communications in the
future. Equipped with full-dimensional large arrays, ground base stations
(GBSs) can apply adaptive fine-grained three-dimensional (3D) beamforming to
mitigate the strong interference between high-altitude UAVs and low-altitude
terrestrial users, thus significantly enhancing the network spectral
efficiency. However, the performance gain of massive MIMO critically depends on
the accurate channel state information (CSI) of both UAVs and terrestrial users
at the GBSs, which is practically difficult to achieve due to UAV-induced pilot
contamination and UAV's high mobility in 3D. Moreover, the increasingly popular
applications relying on a large group of coordinated UAVs or UAV swarm as well
as the practical hybrid GBS beamforming architecture for massive MIMO further
complicate the pilot contamination and channel/beam tracking problems. In this
article, we provide an overview of the above challenging issues, propose new
solutions to cope with them, and discuss about promising directions for future
research. Preliminary simulation results are also provided to validate the
effectiveness of proposed solutions.
