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Outage-Constrained Robust Beamforming for Intelligent Reflecting Surface Aided Wireless Communication
In intelligent reflecting surface (IRS) aided wireless communication systems,
channel state information (CSI) is crucial to achieve its promising passive
beamforming gains. However, CSI errors are inevitable in practice and generally
correlated over the IRS reflecting elements due to the limited training with
discrete phase shifts, which degrade the data transmission rate and
reliability. In this paper, we focus on investigating the effect of CSI errors
to the outage performance in an IRS-aided multiuser downlink communication
system. Specifically, we aim to jointly optimize the active transmit precoding
vectors at the access point (AP) and passive discrete phase shifts at the IRS
to minimize the AP's transmit power, subject to the constraints on the maximum
CSI-error induced outage probability for the users. First, we consider the
single-user case and derive the user's outage probability in terms of the mean
signal power (MSP) and variance of the received signal at the user. Since there
is a trade-off in tuning these two parameters to minimize the outage
probability, we propose to maximize their weighted sum with the optimal weight
found by one-dimensional search. Then, for the general multiuser case, since
the users' outage probabilities are difficult to obtain in closed-form due to
the inter-user interference, we propose a novel constrained stochastic
successive convex approximation (CSSCA) algorithm, which replaces the
non-convex outage probability constraints with properly designed convex
surrogate approximations. Simulation results verify the effectiveness of the
proposed robust beamfoming algorithms and show their significant performance
improvement over various benchmark schemes.Comment: 15 pages, 14 figures, accepted for publication in IEEE Transactions
on Signal Processin
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