  Intelligent reflecting surface (IRS) is envisioned to have abundant
applications in future wireless networks by smartly reconfiguring the signal
propagation for performance enhancement. Specifically, an IRS consists of a
large number of low-cost passive elements each reflecting the incident signal
with a certain phase shift to collaboratively achieve beamforming and suppress
interference at one or more designated receivers. In this paper, we study an
IRS-enhanced point-to-point multiple-input single-output (MISO) wireless system
where one IRS is deployed to assist in the communication from a multi-antenna
access point (AP) to a single-antenna user. As a result, the user
simultaneously receives the signal sent directly from the AP as well as that
reflected by the IRS. We aim to maximize the total received signal power at the
user by jointly optimizing the (active) transmit beamforming at the AP and
(passive) reflect beamforming by the phase shifters at the IRS. We first
propose a centralized algorithm based on the technique of semidefinite
relaxation (SDR) by assuming the global channel state information (CSI)
available at the IRS. Since the centralized implementation requires excessive
channel estimation and signal exchange overheads, we further propose a
low-complexity distributed algorithm where the AP and IRS independently adjust
the transmit beamforming and the phase shifts in an alternating manner until
the convergence is reached. Simulation results show that significant
performance gains can be achieved by the proposed algorithms as compared to
benchmark schemes. Moreover, it is verified that the IRS is able to drastically
enhance the link quality and/or coverage over the conventional setup without
the IRS.
