  Massive Multiple-Input Multiple-Output (MIMO)communications uses a large
number of antennas at the base station to increase the data rate and user
density in future wireless systems. For simulation, it has become common
practice to use i.i.d. complex Gaussian matrix entries to obtain an average
MIMO channel behavior. More refined models have been devised and proposed to
standardization bodies; yet, channel modeling remains an active area of
research, as current models tend to be, still, quite limited, e.g., when it
comes to evaluating clustering algorithms, with regions of spatial
orthogonality for concurrent scheduling of users, which is an essential concept
in massive MIMO precoding. For this, spatial correlations need to be included.
To further refine channel modeling, we have built a "spider antenna" prototype
that allows spatially continuous measurements in three dimensions, enabling a
high-resolution sampling over, initially, a volume of 2m x 2m x 2m for indoor
measurements. Several experiments have been conducted to illustrate the new
insights to be gained when studying user orthogonality, clustering and
precoding in a massive MIMO context. Furthermore, the influence of antenna
array geometry and user spacing on the achievable rate over actually measured
channels is studied.
