  Intelligent reflecting surfaces (IRSs) are regarded as key enablers of
next-generation wireless communications, due to their capability of customizing
the wireless propagation environment. In this paper, we investigate
power-efficient resource allocation for IRS-assisted multiuser multiple-input
single-output (MISO) systems. To minimize the transmit power, both the
beamforming vectors at the access point (AP) and phase shifts at the IRS are
jointly optimized while taking into account the minimum required
quality-of-service (QoS) of the users. To tackle the non-convexity of the
formulated optimization problem, an inner approximation (IA) algorithm is
developed. Unlike existing designs, which cannot guarantee local optimality,
the proposed algorithm is guaranteed to converge to a Karush-Kuhn-Tucker (KKT)
solution. Our simulation results show the effectiveness of the proposed
algorithm compared to baseline schemes and reveal that deploying IRSs is more
promising than leveraging multiple antennas at the AP in terms of energy
efficiency.
