This paper deals with linear equalization in massive multi-usermultiple-input multiple-output (MU-MIMO) wireless systems. We first providesimple conditions on the antenna configuration for which the well-known linearminimum mean-square error (L-MMSE) equalizer provides near-optimal spectralefficiency, and we analyze its performance in the presence of parametermismatches 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. Weshow that NOPE achieves the same performance as that of the L-MMSE equalizer inthe large-antenna limit, and we demonstrate its efficacy in realistic,finite-dimensional systems. From a practical perspective, NOPE iscomputationally efficient and avoids dedicated training that is typicallyrequired for parameter estimation
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