On revenue maximization from secondary spectrum use in wireless cellular networks

Regulatory frameworks for radio spectrum management follow a command and control approach. Namely, a license holder is granted limited spectrum rights so that it can provide specific services but cannot resale its license. Reformers have long called for alternative approaches based on property rights and market dynamics Given the increased demand on wireless communications and the reported inefficiency in using available spectrum bands, the rigidity of the current regulations has recently gained wider recognition and has led to a global effort to create spectrum secondary markets where previously issued licenses can be sold.;In this thesis, we focus on cellular communications and study economics of revenue for license holders from secondary market agreements. First, we address long term spectrum leasing agreements under which a license holder relinquishes its services and leases spectrum rights in subsets of its coverage area. We develop theoretical foundations for capturing network-wide effect of interference to devise revenue-maximizing pricing strategies. We show that the structure of prices lends itself to an efficient iterative computational procedure. The devised strategies are shown to demonstrate superiority over simplistic pricing strategies and emphasize the importance of effective pricing in bringing secondary markets to full realization.;We consider also short term leasing agreements that allow secondary users to access spectrum on opportunistic basis In particular, we optimize spectrum sharing policies which reserve part of cell capacities for the exclusive use of the license holder. We propose an adaptive algorithm that updates reserved capacities in light of fluctuations in traffic rates under the objective of maximizing revenue of the license holder. Furthermore, we exploit the localized nature of shadow prices, or sensitivity of the revenue to a unit change of the reserved capacity of the cell, to devise a distributed version of the algorithm that can be employed at the base stations.;Finally, we argue that the relationship between secondary price and demand, a requirement of critical importance when revenue maximization is sought, might not be necessarily known for the license holder. In this respect, we focus on profitability from secondary markets and establish that it can be achieved if the secondary price is chosen above a certain level regardless of the demand and as long as the price generates demand. We study a number of call admission policies that are practically appealing in their operational properties. In acyclic network topologies, equilibrium network occupancy under each of those policies is shown to admit a Markov Random Field representation that facilitates profit calculations. We observe that certain policies have profitability regions that seem to be almost solely dependent on price, but not on the form of the relationship between price and demand. Thus, these policies appear to posses the same robustness property as an indeterminate optimal policy.