| Summary: | In this paper, we investigate the performance of
a reconfigurable intelligent surface (RIS) assisted large-scale
network by characterizing the coverage probability and the average achievable rate using stochastic geometry. Considering the
spatial correlation between transmitters (TXs) and RISs, their
locations are jointly modelled by a Gauss-Poisson process (GPP).
Two association strategies, i.e., nearest association and fixed
association, are both discussed. For the RIS-aided transmission,
the signal power distribution with a direct link is approximated
by a gamma random variable using a moment matching method,
and the Laplace transform of the aggregate interference power is
derived in closed form. Based on these expressions, we analyze
the channel hardening effect in the RIS-assisted transmission,
the coverage probability, and the average achievable rate of
the typical user. We derive the coverage probability expressions
for the fixed association strategy and the nearest association
strategy in an interference-limited scenario in closed form.
Numerical results are provided to validate the analysis and
illustrate the effectiveness of RIS-assisted transmission with
passive beamforming in improving the system performance.
Furthermore, it is also unveiled that the system performance is
independent of the density of TXs with the nearest association
strategy in the interference-limited scenario.
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