  In multiuser multiple-input multiple-output (MU-MIMO) systems, channel
correlation is detrimental to system performance. We demonstrate that widely
used, yet overly simplified, correlation models that generate identical
correlation profiles for each terminal tend to severely underestimate the
system performance. In sharp contrast, more physically motivated models that
capture variations in the power angular spectra across multiple terminals,
generate diverse correlation patterns. This has a significant impact on the
system performance. Assuming correlated Rayleigh fading and downlink
zero-forcing precoding, tight closed-form approximations for the average
signal-to-noise-ratio, and ergodic sum spectral efficiency are derived. Our
expressions provide clear insights into the impact of diverse correlation
patterns on the above performance metrics. Unlike previous works, the
correlation models are parameterized with measured data from a recent 2.53 GHz
urban macrocellular campaign in Cologne, Germany. Overall, results from this
paper can be treated as a timely re-calibration of performance expectations
from practical MU-MIMO systems.
