  We propose a new methodology to estimate the spatial reuse of CSMA-like
scheduling. Instead of focusing on spatial configurations of users, we model
the interferences between users as a random graph. Using configuration models
for random graphs, we show how the properties of the medium access mechanism
are captured by some deterministic differential equations, when the size of the
graph gets large. Performance indicators such as the probability of connection
of a given node can then be efficiently computed from these equations. We also
perform simulations to illustrate the results on different types of random
graphs. Even on spatial structures, these estimates get very accurate as soon
as the variance of the interference is not negligible.
