Optimal Pricing and Admission Control for Heterogeneous Secondary Users

TL;DR

This paper develops optimal static and dynamic pricing and admission control strategies for spectrum sharing with heterogeneous secondary users, demonstrating significant revenue improvements with dynamic pricing.

Contribution

It introduces a stochastic dynamic programming model for joint pricing and admission control considering demand heterogeneity, and derives optimal policies for both static and dynamic schemes.

Findings

Dynamic pricing can increase revenue by over 30% compared to static pricing.

Stationary admission policies are optimal under static pricing.

The model accounts for demand heterogeneity and stochastic user behavior.

Abstract

This paper studies how to maximize a spectrum database operator's expected revenue in sharing spectrum to secondary users, through joint pricing and admission control of spectrum resources. A unique feature of our model is the consideration of the stochastic and heterogeneous nature of secondary users' demands. We formulate the problem as a stochastic dynamic programming problem, and present the optimal solutions under both static and dynamic pricing schemes. In the case of static pricing, the prices do not change with time, although the admission control policy can still be time-dependent. In this case, we show that a stationary (time-independent) admission policy is in fact optimal under a wide range of system parameters. In the case of dynamic pricing, we allow both prices and admission control policies to be time-dependent. We show that the optimal dynamic pricing can improve the operator's revenue by more than 30% over the optimal static pricing, when secondary users' demands for spectrum opportunities are highly elastic.