Wireless Networks

This domain of research is expanding very fast. Members of LINCS played a pioneering role in developing spatial stochastic models of wireless networks. The approach consists in casting information-theoretic principles of communications  into a random geometric context in order to obtain adequate stochastic-geometric or graph-theoretic models of wireless networks. More complete models integrate also a temporal dimension, e.g. representing  user-traffic. Space-time analysis of these models requires also appropriate tools from queueing theory.

The whole  approach allows for a macroscopic analysis of large wireless networks, and is particularly appropriate for network dimensioning. It make evident important theoretic limitations of wireless communication networks.

Regarding international collaborations, we have strong relations with the University of California Berkeley, Stanford University, UT Austin (J. Andrews, G. de Veciana, S. Shakkottai), IIT Madras.  We have also a few strong industrial (telecom) partners (Qualcomm, Sprint, Orange) outside LINCS.