  We propose blind estimators for the average noise power, receive signal
power, signal-to-noise ratio (SNR), and mean-square error (MSE), suitable for
multi-antenna millimeter wave (mmWave) wireless systems. The proposed
estimators can be computed at low complexity and solely rely on beamspace
sparsity, i.e., the fact that only a small number of dominant propagation paths
exist in typical mmWave channels. Our estimators can be used (i) to quickly
track some of the key quantities in multi-antenna mmWave systems while avoiding
additional pilot overhead and (ii) to design efficient nonparametric algorithms
that require such quantities. We provide a theoretical analysis of the proposed
estimators, and we demonstrate their efficacy via synthetic experiments and
using a nonparametric channel-vector denoising task with realistic
multi-antenna mmWave channels.
