  The reconfigurable intelligent surface (RIS) is a promising technology that
is anticipated to enable high spectrum and energy efficiencies in future
wireless communication networks. This paper investigates optimum location-based
RIS selection policies in RIS-aided wireless networks to maximize the signal-to
noise ratio (SNR) for a power path-loss model in outdoor communications and an
exponential path-loss model in indoor communications. The random locations of
all available RISs are modeled as a Poisson point process (PPP). To quantify
the network performance, the outage probabilities and average rates attained by
the proposed RIS selection policies are evaluated by deriving the distance
distribution of the chosen RIS node as per the selection policies for both
power and exponential path-loss models. Feedback could incur heavy signaling
overhead. To reduce the overhead, we also propose limited-feedback RIS
selection policies by limiting the average number of RISs that feed back their
location information to the source. The outage probabilities and average rates
obtained by the limited-feedback RIS selection policies are derived for both
path-loss models. The numerical results show notable performance gains obtained
by the proposed RIS selection policies and demonstrate that the conventional
relay selection policies are not suitable for RIS-aided wireless networks.
