Genetic Algorithms for Capacity Estimation in Pluralistic Spectrum Licensing Simulations

摘要

The regional licensing of 5G spectrum represents an exemplary use case for the huge potential of a geographically fine-grained spectrum assignment. It raises the question, whether new types of spectrum licenses could augment the current arsenal of static allocation schemes with central control. In our contribution, we introduce the use of genetic-algorithms (GA) as integral part of ex-ante evaluations of new licensing schemes. We apply the method to calculate the near-optimal exploitation of available spectrum resources in the course of an academic simulation. It assesses the effects of interference-based sub-licensing contracts, also known as Pluralistic Licensing Contracts (PLCs), on mobile networks. Our findings suggest that PLCs might provide a low-effort exploitation of underutilized spectrum reserves, e.g. in sparse user populations, and constitute a highly scalable means for the pricing of externalities.