This monograph provides an overview of interference analysis in large wireless networks, focusing on the statistical characterization of interference and its impact on network performance. It covers various network models, including deterministic lattices, Poisson networks, and Poisson cluster networks, and discusses the effects of path loss, fading, and power control on interference. The book introduces analytical techniques such as Palm theory and conditional probability generating functionals, which are essential for deriving interference statistics in complex network scenarios. It also addresses the distribution of interference, the signal-to-interference-plus-noise ratio (SINR), and outage probabilities, which are critical metrics for evaluating network performance. The text emphasizes the importance of understanding interference in wireless networks, especially in the context of emerging systems where centralized control is not feasible. It provides detailed derivations for interference in different network models, including one-dimensional and two-dimensional lattices, and discusses the implications of these results for network design and optimization. The monograph concludes with a discussion of the statistical properties of interference in Poisson networks, highlighting the role of shot noise and the use of stable distributions to model interference behavior. Overall, the book serves as a comprehensive resource for understanding and analyzing interference in large wireless networks.This monograph provides an overview of interference analysis in large wireless networks, focusing on the statistical characterization of interference and its impact on network performance. It covers various network models, including deterministic lattices, Poisson networks, and Poisson cluster networks, and discusses the effects of path loss, fading, and power control on interference. The book introduces analytical techniques such as Palm theory and conditional probability generating functionals, which are essential for deriving interference statistics in complex network scenarios. It also addresses the distribution of interference, the signal-to-interference-plus-noise ratio (SINR), and outage probabilities, which are critical metrics for evaluating network performance. The text emphasizes the importance of understanding interference in wireless networks, especially in the context of emerging systems where centralized control is not feasible. It provides detailed derivations for interference in different network models, including one-dimensional and two-dimensional lattices, and discusses the implications of these results for network design and optimization. The monograph concludes with a discussion of the statistical properties of interference in Poisson networks, highlighting the role of shot noise and the use of stable distributions to model interference behavior. Overall, the book serves as a comprehensive resource for understanding and analyzing interference in large wireless networks.