Interference Analysis in Non-Poisson Networks Under Spatially Correlated Shadowing

Abstract

Spatial correlations that appear in mobile wireless networks, such as the correlations of node locations and shadowing effects, significantly affect the characteristics of interference, which may degrade the performance of various wireless network systems. In this paper, we theoretically analyze the statistical and temporal characteristics of interference in a network where the node locations and shadowing are spatially correlated. We model the correlation of the node locations by two types of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">non-Poisson</i> point processes: determinantal point processes (DPPs) for modeling <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">repulsiveness</i> and doubly Poisson cluster processes (DPCPs) for modeling <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">attractiveness</i> . Furthermore, we consider Gudmundson's model for the spatial correlation of shadowing. Using this model and assuming an i.i.d. mobility of nodes, we analyze the variance along with the spatial and temporal correlations of interference. Since the exact expressions are in non-analytical forms, we derive their simple closed-form asymptotic formulas when the variance of the shadowing is large. The results show a readable relationship between the characteristics of interference and various system parameters. This relationship can be used for realistic modeling and better understanding of various wireless network systems under spatially correlated shadowing. Moreover, we discuss various numerical examples and demonstrate that the obtained asymptotic expressions achieve tight approximation.