  Both the power-dissipation and cost of massive multiple-input multiple-output
(mMIMO) systems may be substantially reduced by using low-resolution
analog-to-digital converters (LADCs) at the receivers. However, both the coarse
quantization of LADCs and the inaccurate instantaneous channel state
information (ICSI) degrade the performance of quantized mMIMO systems. To
overcome these challenges, we propose a novel stochastic hybrid analog-digital
combiner (SHC) scheme for adapting the hybrid combiner to the long-term
statistics of the channel state information (SCSI). We seek to minimize the
transmit power by jointly optimizing the SHC subject to average rate
constraints. For the sake of solving the resultant nonconvex stochastic
optimization problem, we develop a relaxed stochastic successive convex
approximation (RSSCA) algorithm. Simulations are carried out to confirm the
benefits of our proposed scheme over the benchmarkers.
