# Stochastic Geometry and Wireless Networks

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

efficiency in large wireless networks under densification assumptions.

François Baccelli is Simons Math+X Chair in Mathematics and ECE at UT

Austin. His research directions are at the interface between Applied

Mathematics (probability theory, stochastic geometry, dynamical systems)

and Communications (network science, information theory, wireless

networks). He is co-author of research monographs on point processes and

queues (with P. Brémaud); max plus algebras and network dynamics (with G.

Cohen, G. Olsder and J.P. Quadrat); stationary queuing networks (with P.

Brémaud); stochastic geometry and wireless networks (with B.

Blaszczyszyn). Before joining UT Austin, he held positions at INRIA, Ecole

Normale Supérieure and Ecole Polytechnique. He received the France Télécom

Prize of the French Academy of Sciences in 2002 and the ACM Sigmetrics

Achievement Award in 2014. He is a co-recipient of the 2014 Stephen O.

Rice Prize and of the Leonard G. Abraham Prize Awards of the IEEE

Communications Theory Society. He is a member of the French Academy of

Sciences and part time researcher at INRIA.