On distribution of aggregate interference in cognitive radio networks

This paper analyzes the distribution of aggregate interference in cognitive radio networks. Poisson point spatial distribution model and average propagation path loss model are considered. All possible scenarios are classified into three typical cases, based on typical outage events. When the average number of nodes in the forbidden region is much smaller than one, the aggregate interference can be well approximated by the nearest one (nearest node dominates outage events). When the average number of nodes in the forbidden range is greater than one, the aggregate interference can be approximated by a Gaussian random variable (many nodes contribute to outage). When the average number of nodes in the forbidden range is slightly smaller than one, neither the nearest node approximation nor Gaussian one is accurate (a few near-by nodes are dominant), and higher order cumulants approximations or others are required. We derive the nearest interference distribution and give a simpler way to calculate the cumulants of the aggregate interference.