Risk-based pricing for secondary spectrum access

Probabilistic reasoning applied to dynamic spectrum sharing systems enables them to characterize situational uncertainties and determine acceptable spectrum access behaviors. Spectrum sharing systems may use sensing data to reduce situational uncertainty and improve spectrum sharing potential. Probabilistic reasoning approaches enable risk-constrained spectrum access, a concept in which spectrum sharing is governed by maintaining acceptable levels of interference and spectrum access risks. Simulations show the potential for greater user density as a function of reduced situational uncertainty. This paper extends the risk-based spectrum access approach to secondary spectrum providers, who need to determine how to best allocate spectrum resources to users. A secondary spectrum provider revenue and cost model is developed that incorporates secondary user density, pricing models, and spectrum provider costs that are functions of interference risk and situational uncertainty. Simulations and analyses demonstrate the relationship among revenue, cost, risk, and situational uncertainty. Analysis shows significant variation in secondary spectrum provider revenue as a function of path loss uncertainty and interference risk.