In a limited form cellular providers have long shared spectrum in the form of roaming agreements. The primary motivation for this has been to extend the coverage of a wireless carrier's network into regions where it has no infrastructure. As devices and infrastructure become more agile, such sharing could be done on a much faster time-scale and have advantages even when two providers both have coverage in a given area, e.g., by enabling one provider to acquire “overflow” capacity from another provider during periods of high demand. This may provide carriers with an attractive means to better meet their rapidly increasing bandwidth demands. On the other hand, the presence of such a sharing agreement could encourage providers to underinvest in their networks, resulting in poorer performance. We adapt the newsvendor model from the operations management literature to model such a situation and to gain insight into these trade-offs. In particular, we analyze the structure of revenue-sharing contracts that incentivize both capacity sharing and increased access for end-users.

Markets are often viewed as a key ingredient in facilitating more efficient dynamic spectrum access. In this paper we consider how such spectrum markets are influenced by a key property of the wireless medium: interference. Interference can result in "complementarities" among the "spectrum goods" being traded, which complicates the design of an efficient market mechanism. We consider several alternative models for defining such spectrum goods, and explore the impact of these choices on the complexity of the resulting market.

Extensive spectrum markets have the potential to enable more efficient use of this limited resource. Such markets must account for particular properties of the underlying wireless medium. In this paper we focus on one such aspect: the role of interference created among different agents who may purchase the right to use the same spectrum at nearby locations. Such interference can result in “complementarities” among the spectrum goods being traded, which complicates the design of an efficient market. We begin with a simple linear model for these complementarities that was shown to be computationally difficult in earlier work. We give several approximation algorithms for this model. We then consider several alternative models in which the spectrum goods are defined in different ways and explore the impact of these choices on the complexity of the resulting market.