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The authors study the performance characteristics of cognitive wireless networks under different dynamic spectrum access scenarios. Their focus is especially on the influence of spatial structures of the primary and secondary user networks on the achievable performance of the secondary network. They adopt techniques from spatial statistics to develop stochastic models for the structure and interaction of these networks. The chosen models are based on Gaussian random fields and Gibbs point processes, and are firmly grounded on empirical data. They, then apply extensive Monte Carlo simulations to study the behavior of these models and their related performance properties.
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