Optimal Pricing for Spectrum Allocation in Cognitive Radio Networks

Abstract

In this paper, we investigate the problem of spectrum allocation in Cognitive Radio Networks (CRNs) where a primary user (PU) leases its idle spectrums to a number of secondary users (SUs) who may have different willing to pay for these spectrums. For the PU, its main objective is to gain profit from selling the idle spectrums, and from the perspective of the Sus, they aim to maximize their utility from using spectrums. We model the interaction between the PU and SUs as a two-stage Stackelberg game, where the PU sets the prices for its spectrum in the first stage, and SUs make their spectrum demands decisions in the second stage. We use the backward induction method to solve this game. The numerical results show that the proposed solution method can increase revenue of the PU compared with the uniform pricing scheme.