Campuses:

Stochastic geometry

Tuesday, February 23, 2016 - 1:25pm - 2:25pm
Francois Baccelli (The University of Texas at Austin)

Stochastic geometry provides a natural way of averaging out the
quantitative characteristics of any network information theoretic channel
over all potential geometrical patterns or channel gains present in e.g. a
stationary Poisson point process. The talk will survey recent scaling laws
obtained by this approach on several network information theoretic
channels, when the density of the point process tends to infinity. This
approach allows one to predict the asymptotic behavior of spectral

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