  In recent years, a brand-new technology, reconfigurable intelligent surface
(RIS) has been widely studied for reconfiguring the wireless propagation
environment. RIS is an artificial surface of electromagnetic material that is
capable of customizing the propagation of the wave impinging upon it. Utilizing
RIS for communication service like signal enhancement usually lead to
non-convex optimization problems. Existing optimization methods either suffers
from scalability issues for $N$ number of RIS elements large, or may lead to
suboptimal solutions in some scenario. In this paper, we propose a
divide-and-sort (DaS) discrete optimization approach, that is guaranteed to
find the global optimal phase shifts for $1$-bit RIS, and has time complexity
$\mathcal{O}(N \log(N))$. Numerical experiments show that the proposed approach
achieves a better ``performance--complexity tradeoff'' over other methods for
$1$-bit RIS.
