  Stochastic orders are binary relations defined on probability distributions
which capture intuitive notions like being larger or being more variable. This
paper introduces stochastic ordering of interference distributions in
large-scale networks modeled as point process. Interference is the main
performance-limiting factor in most wireless networks, thus it is important to
understand its statistics. Since closed-form results for the distribution of
interference for such networks are only available in limited cases,
interference of networks are compared using stochastic orders, even when closed
form expressions for interferences are not tractable. We show that the
interference from a large-scale network depends on the fading distributions
with respect to the stochastic Laplace transform order. The condition for
path-loss models is also established to have stochastic ordering between
interferences. The stochastic ordering of interferences between different
networks are also shown. Monte-Carlo simulations are used to supplement our
analytical results.
