  Massive multiple-input-multiple-output (MIMO) transmission is a promising
technology to improve the capacity and reliability of wireless systems.
However, the number of antennas that can be equipped at a base station (BS) is
limited by the BS form factor, posing a challenge to the deployment of massive
linear arrays. To cope with this limitation, this work discusses Full Dimension
MIMO (FD-MIMO), which is currently an active area of research and
standardization in the 3rd Generation Partnership Project (3GPP) for evolution
towards fifth generation (5G) cellular systems. FD-MIMO utilizes an active
antenna system (AAS) with a 2D planar array structure, which provides the
ability of adaptive electronic beamforming in the 3D space. This paper presents
the design of the AAS and the ongoing efforts in the 3GPP to develop the
corresponding 3D channel model. Compact structure of large-scale antenna arrays
drastically increases the spatial correlation in FD-MIMO systems. In order to
account for its effects, the generalized spatial correlation functions for
channels constituted by individual antenna elements and overall antenna ports
in the AAS are derived. Exploiting the quasi-static channel covariance matrices
of the users, the problem of determining the optimal downtilt weight vector for
antenna ports, which maximizes the minimum signal-to-interference ratio of a
multi-user multiple-input-single-output system, is formulated as a fractional
optimization problem. A quasi-optimal solution is obtained through the
application of semi-definite relaxation and Dinkelbach's method. Finally, the
user-group specific elevation beamforming scenario is devised, which offers
significant performance gains as confirmed through simulations. These results
have direct application in the analysis of 5G FD-MIMO systems.
