  Linear minimum mean-square error (L-MMSE) equalization is among the most
popular methods for data detection in massive multi-user multiple-input
multiple-output (MU-MIMO) wireless systems. While L-MMSE equalization enables
near-optimal spectral efficiency, accurate knowledge of the signal and noise
powers is necessary. Furthermore, corresponding VLSI designs must solve linear
systems of equations, which requires high arithmetic precision, exhibits
stringent data dependencies, and results in high circuit complexity. This paper
proposes the first VLSI design of the NOnParametric Equalizer (NOPE), which
avoids knowledge of the transmit signal and noise powers, provably delivers the
performance of L-MMSE equalization for massive MU-MIMO systems, and is
resilient to numerous system and hardware impairments due to its parameter-free
nature. Moreover, NOPE avoids computation of a matrix inverse and only requires
hardware-friendly matrix-vector multiplications. To showcase the practical
advantages of NOPE, we propose a parallel VLSI architecture and provide
synthesis results in 28nm CMOS. We demonstrate that NOPE performs on par with
existing data detectors for massive MU-MIMO that require accurate knowledge of
the signal and noise powers.
