Investment and Pricing with Spectrum Uncertainty: A Cognitive Operator's Perspective

TL;DR

This paper analyzes how a cognitive mobile virtual network operator optimally invests in spectrum sensing and leasing, and sets prices under spectrum uncertainty, to maximize profit and ensure fair quality of service.

Contribution

It models the joint investment and pricing problem as a Stackelberg game, revealing threshold-based strategies and the benefits of spectrum sensing over leasing.

Findings

Spectrum sensing enhances expected profit and user payoffs.

Optimal pricing is independent of user wireless characteristics.

Threshold structures determine investment and pricing decisions.

Abstract

This paper studies the optimal investment and pricing decisions of a cognitive mobile virtual network operator (C-MVNO) under spectrum supply uncertainty. Compared with a traditional MVNO who often leases spectrum via long-term contracts, a C-MVNO can acquire spectrum dynamically in short-term by both sensing the empty "spectrum holes" of licensed bands and dynamically leasing from the spectrum owner. As a result, a C-MVNO can make flexible investment and pricing decisions to match the current demands of the secondary unlicensed users. Compared to dynamic spectrum leasing, spectrum sensing is typically cheaper, but the obtained useful spectrum amount is random due to primary licensed users' stochastic traffic. The C-MVNO needs to determine the optimal amounts of spectrum sensing and leasing by evaluating the trade off between cost and uncertainty. The C-MVNO also needs to determine the optimal price to sell the spectrum to the secondary unlicensed users, taking into account wireless heterogeneity of users such as different maximum transmission power levels and channel gains. We model and analyze the interactions between the C-MVNO and secondary unlicensed users as a Stackelberg game. We show several interesting properties of the network equilibrium, including threshold structures of the optimal investment and pricing decisions, the independence of the optimal price on users' wireless characteristics, and guaranteed fair and predictable QoS among users. We prove that these properties hold for general SNR regime and general continuous distributions of sensing uncertainty. We show that spectrum sensing can significantly improve the C-MVNO's expected profit and users' payoffs.