  A fundamental challenge for millimeter wave (mmWave) communications lies in
its sensitivity to the presence of blockages, which impact the connectivity of
the communication links and ultimately the reliability of the entire network.
In this paper, we analyze a reconfigurable intelligent surface (RIS)-aided
mmWave communication system for enhancing the network reliability and
connectivity in the presence of random blockages. To enhance the robustness of
hybrid analog-digital beamforming in the presence of random blockages, we
formulate a stochastic optimization problem based on the minimization of the
sum outage probability. To tackle the proposed optimization problem, we
introduce a low-complexity algorithm based on the stochastic block gradient
descent method, which learns sensible blockage patterns without searching for
all combinations of potentially blocked links. Numerical results confirm the
performance benefits of the proposed algorithm in terms of outage probability
and effective data rate.
