  Receivers with one-bit analog-to-digital converters (ADCs) are promising for
high bandwidth millimeter wave (mmWave) systems as they consume less power than
their full resolution counterparts. The extreme quantization in one-bit
receivers and the use of large antenna arrays at mmWave make channel estimation
challenging. In this paper, we develop channel estimation algorithms that
exploit the low-rank property of mmWave channels. We also propose a novel
training solution that results in a low complexity implementation of our
algorithms. Simulation results indicate that the proposed methods achieve
better channel reconstruction than compressed sensing-based techniques that
exploit sparsity of mmWave channels.
