  In this paper, we investigate resource allocation algorithm design for
intelligent reflecting surface (IRS)-assisted multiuser cognitive radio (CR)
systems. In particular, an IRS is deployed to mitigate the interference caused
by the secondary network to the primary users. The beamforming vectors at the
base station (BS) and the phase shift matrix at the IRS are jointly optimized
for maximization of the sum rate of the secondary system. The algorithm design
is formulated as a non-convex optimization problem taking into account the
maximum interference tolerance of the primary users. To tackle the resulting
non-convex optimization problem, we propose an alternating optimization-based
suboptimal algorithm exploiting semidefinite relaxation, the penalty method,
and successive convex approximation. Our simulation results show that the
system sum rate is dramatically improved by our proposed scheme compared to two
baseline schemes. Moreover, our results also illustrate the benefits of
deploying IRSs in CR networks.
