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Throughput Limits in Spectrum Sensing Cognitive Radio Networks Using Point Processes

Spectrum sensing in cognitive wireless networks is important for Secondary nodes to avoid interference with the Primaries. In this paper, considering a spectrum sensing framework, we develop models for bounding interference levels from Secondary network to the Primary nodes. First, we assume that both networks are distributed according to Poisson point processes. Subsequently, we consider a more practical model which takes into account the medium access control regulations and where the Secondary Poisson process is judiciously thinned in two phases to avoid interference with the Secondary as well as the Primary nodes. The resulting process will be a modified version of the Mat\`ern point process. For both of these models, we obtain bounds for CCDF of interference and present simulation results which show the developed analytical bounds are quite tight. Moreover, we use these bounds to find the operation regions of the Secondary network such that the interference constraint is satisfied on receiving Primary nodes for the two cases. We then obtain theoretical results on the Primary and Secondary throughput and find the throughput limits under interference constraint.