A Novel Price-Based Power Control Algorithm in Cognitive Radio Networks

Abstract

This letter investigates price-based power control problem in the spectrum sharing cognitive radio networks (CRNs). The base station (BS) of primary users (PUs) can admit secondary users (SUs) to access if their interference power is under the interference power constraint (IPC). In order to access the spectrum, the SUs need to pay for their interference power. The BS first decides the price for each SUs to maximize its revenue. Then, each SU controls its transmit power to maximize its revenue based on non-cooperative game. We model the interaction between the BS and the SUs as a Stackelberg game. Using backward induction, the revenue function of the BS is expressed as a function of the transmit power of the SUs. After we depict the property of optimal transmit power of the SUs, we propose a novel price-based power control algorithm to maximize the revenue of the BS. Simulation results show the proposed algorithm improves the revenue of both the BS and SUs compared with the proportionate pricing algorithm.