  This paper deals with linear equalization in massive multi-user
multiple-input multiple-output (MU-MIMO) wireless systems. We first provide
simple conditions on the antenna configuration for which the well-known linear
minimum mean-square error (L-MMSE) equalizer provides near-optimal spectral
efficiency, and we analyze its performance in the presence of parameter
mismatches in the signal and/or noise powers. We then propose a novel,
optimally-tuned NOnParametric Equalizer (NOPE) for massive MU-MIMO systems,
which avoids knowledge of the transmit signal and noise powers altogether. We
show that NOPE achieves the same performance as that of the L-MMSE equalizer in
the large-antenna limit, and we demonstrate its efficacy in realistic,
finite-dimensional systems. From a practical perspective, NOPE is
computationally efficient and avoids dedicated training that is typically
required for parameter estimation
