Coverage Probability of Double-IRS Assisted Communication Systems

In this paper, we derive the coverage probability
of a double-intelligent reflecting surface (IRS) assisted wireless
network and study the impact of multiplicative beamforming
gain and correlated Rayleigh fading. In particular, we derive
a novel closed-form expression of the coverage probability of a
single-input single-output (SISO) system assisted by two large
IRSs while being dependent on the corresponding arbitrary
reflecting beamforming matrices (RBMs) and large-scale statistics
in terms of correlation matrices. Taking advantage of th large-scale
statistics, we achieve to perform optimization of the RBM of both
IRSs at every several coherence intervals rather at each interval.
This property, based on statistical channel state information (CSI),
is of paramount importance in multi-IRS assisted networks, which
are accompanied with increased computational complexity during
their RBM optimization. Numerical results validate the tightness
of the analytical results even for small IRSs and reveal insightful
properties.