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Massive Multiple-Input Multiple-Output (MIMO)communications uses a largenumber of antennas at the base station to increase the data rate and userdensity in future wireless systems. For simulation, it has become commonpractice to use i.i.d. complex Gaussian matrix entries to obtain an averageMIMO channel behavior. More refined models have been devised and proposed tostandardization bodies; yet, channel modeling remains an active area ofresearch, as current models tend to be, still, quite limited, e.g., when itcomes to evaluating clustering algorithms, with regions of spatialorthogonality for concurrent scheduling of users, which is an essential conceptin massive MIMO precoding. For this, spatial correlations need to be included.To further refine channel modeling, we have built a "spider antenna" prototypethat allows spatially continuous measurements in three dimensions, enabling ahigh-resolution sampling over, initially, a volume of 2m x 2m x 2m for indoormeasurements. Several experiments have been conducted to illustrate the newinsights to be gained when studying user orthogonality, clustering andprecoding in a massive MIMO context. Furthermore, the influence of antennaarray geometry and user spacing on the achievable rate over actually measuredchannels is studied.

Evaluating Massive MIMO Precoding based on 3D-Channel Measurements with a Spider Antenna