Impact of geographic complementarity in dynamic spectrum access

This research examines the impact of demand bids which account for geographic complementarity in spectrum demand, on the allocation and pricing of wireless spectrum licenses. Using an individual based simulation environment and a model of spectrum demand for the region of Portland, OR, we study a primary market to allocate spectrum licenses to wireless service providers. A truthful and efficient market clearing mechanism is used to sell the available licenses. A demand estimation model creates spatial and temporal demand estimates for each of the service providers. A valuation system determines the marginal value of each license which is further used in the bidding process. Three different scenarios are considered. First, the entire city of Portland is considered as one region and the estimated demand for this region is used to construct bids. The auction determines the clearing price for each license and the winner of the licenses based on the marginal valuations. After the market clearing is done and license allocations are made, we measure the total cost of licenses to the providers, the amount of unused capacity, and the number of unserved calls. In the second scenario, the city is divided into 2 regions in such a way that the number of call pairs are minimized across regions. Each region is auctioned separately. The providers can now decide their valuations sequentially for each region, so that they can use information on the allocations of the first region to optimally bid in the second region. The same set of measurements are taken again to understand the social impact of this scenario in comparison to the fist one. Finally a third scenario is run which is just like the second scenario but the city is now split into 2 regions in such a way that the call density and population is split evenly between regions. Results from the three scenarios are compared and analyzed to determine the impact of geographically complementary demand bids on the social cost and capacity used.