Traffic Matrix Estimation in a Dense Multihop Wireless Network

The traffic matrix estimation based on the measurements at the certain points of a fixed network poses an interesting problem, which has also been studied extensively in the literature. In this paper, we consider a similar problem in the setting of dense multihop wireless network. In particular, we assume a large number of nodes with multihop routes using the shortest path routing, so that the routes can be modelled as straight line segments. Furthermore, we assume that we are able to measure the number of transmissions occurring in the different parts of the network during the measurement periods. In this setting we study the problem of inferring the end-to-end traffic demands (traffic matrix) based on the available information. As this information is not sufficient we make some additional Poissonian assumptions on the nature of the traffic in order to have a well-defined problem with a unique solution. Analysing the problem in the framework of stochastic geometry, we are able to give an exact solution for the formulated traffic matrix estimation problem. The methodology is further illustrated by numerical examples