  Line-of-sight (LoS) multi-input multi-output (MIMO) systems exhibit
attractive scaling properties with increase in carrier frequency: for a fixed
form factor and range, the spatial degrees of freedom increase quadratically
for 2D arrays, in addition to the typically linear increase in available
bandwidth. In this paper, we investigate whether modern all-digital baseband
signal processing architectures can be devised for such regimes, given the
difficulty of analog-to-digital conversion for large bandwidths. We propose
low-precision quantizer designs and accompanying spatial demultiplexing
algorithms, considering 2x2 LoS MIMO with QPSK for analytical insight, and 4x4
MIMO with QPSK and 16QAM for performance evaluation. Unlike prior work, channel
state information is utilized only at the receiver (i.e., transmit precoding is
not employed). We investigate quantizers with regular structure whose high-SNR
mutual information approaches that of an unquantized system. We prove that
amplitude-phase quantization is necessary to attain this benchmark; phase-only
quantization falls short. We show that quantizers based on maximizing
per-antenna output entropy perform better than standard Minimum Mean Squared
Quantization Error (MMSQE) quantization. For spatial demultiplexing with
severely quantized observations, we introduce the novel concept of virtual
quantization which, combined with linear detection, provides reliable
demodulation at significantly reduced complexity compared to maximum likelihood
detection.
