The performance of wireless systems depends strongly on the locations of the users or nodes. In modern networks, these locations are subject to considerable uncertainty and thus need to be modeled as a stochastic process of points in the two- or three-dimensional space.

The area of mathematics providing such models and methods to analyze their properties is stochastic geometry, in particular point process theory. Hence wireless network modeling and analysis is a very natural application of stochastic geometry, and, indeed, the last decade has witnessed a significant growth in this area. The goal of this book is to make the mathematical theory accessible to graduate students, researchers, and practitioners who are working in the field of wireless networks. This not only includes a coherent presentation of the theory as it applies to wireless networks, but also enables the reader to understand the related research articles and to define and solve new problems. The field is young enough to leave many opportunities for exciting and relevant new results. Indeed, not all the theoretical concepts covered in this book have found applications to wireless networks yet.

It is assumed that the reader has a solid background in basic probability and perhaps has had some exposure to point processes in one dimension most likely in the form of traffic models for queueing theory.

While being rigorous the book is not pedantic and does not dwell on measure theoretic details.