Constructing a Statistical Behavior Management Scheme for Aggregate Interference in Cognitive Radio Sensor Networks

This research work aims to provide design recommendations to manage aggregate interference generated in cognitive radio sensor networks to account for different scenarios. Previous studies have analyzed the statistical behavior of aggregate interference in conventional wireless networks and cognitive radio networks for specific scenarios. However, the behavior of the aggregate interference presents severe challenges in the cognitive radio networks for several scenarios in which it is required to have a design scheme that allows making operational decisions of the network to mitigate or manage such interference. The question arises, how aggregate interference behaves in different scenarios of cognitive radio sensor networks? Moreover, how could a designer of this kind of network handle aggregate interference knowing its behavior? The methodology for answering these questions consists on the development of computational simulations to generate scenarios with distinct parameters that account for variations in the number of users and distinct protection radii for primary receivers of the cognitive networks. Carry out an analysis and statistical modeling of the data obtained and synthesize the results to construct a scheme that helps to handle the aggregate interference. The constructed management scheme shows parameters in which the aggregate interference can be modeled as a heavy-tailed, light-tailed, exponential or Gaussian distribution and, therefore, use that distribution for mitigation methods, or avoid parameters in which extreme values of interference are presented. This work also shows the significance of the most contributing interference nodes in the network to model the aggregate interference with just the most contributing interferers in the network. Furthermore, how the statistical behaviors of interference are affected by the integration of a discrete power control is discussed. The contribution of this study is that it discusses how a cognitive radio sensor network designer could control parameters such as the primary user protection radius to approach for the optimal operation of its network concerning the aggregate interference statistical characteristics.

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