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Experimental modeling of wireless fading channels performed by the WINNER II project has been shown to fit a Rician rather than Rayleigh distribution, the latter being assumed in many analytical studies of multiple-input-multiple-output (MIMO) communication systems. Unfortunately, a Rician MIMO channel matrix has a nonzero mean (i.e., specular component) that yields, for the matrix product that determines the MIMO performance, a noncentral Wishart distribution that is difficult to analyze. Previously, the noncentral Wishart distribution has been approximated, based on a first-order-moment fit, by a central Wishart distribution and used to derive average error probability (AEP) expressions for zero-forcing (ZF) detection. We first reveal that this approximation and the MIMO performance evaluation tools derived from it may be reliable only for rank-one specular matrices. We then exploit this approximation to derive an AEP expression for a lesser known, yet optimal, MIMO ZF approach that, unlike the conventional approach, accounts for channel estimation accuracy through the channel statistics. After validating this AEP expression for the rank-one case, it is shown that the ZF performance averaged over realistic (i.e., WINNER II) distributions of the Rician K-factor and azimuth spread (AS) can be much worse than that for the average K and AS. Finally, through simulations, it is shown that the optimal detection approach can substantially outperform the conventional approach for ZF for full-rank specular matrices, as well as for minimum mean square error detection for both rank-one and full-rank specular matrices.