A New Algorithm of Spectrum Allocation for Cognitive Radio Based on Cooperative Game

Abstract

Secondary users, which base on the spectrum pricing function given by primary users, can compete the spectrum resource with each other through game theory in cognitive radio system. It can be divided into cooperative game and noncooperative game according to whether the secondary users cooperate or not in the spectrum sharing. In this paper, based on the Nash bargaining in cooperative game, an improved utility function is proposed to maximize the profit product of all the secondary users. The cooperative game algorithm of spectrum allocation in cognitive radio is found and the priority of secondary users is introduced. We prove the existence and uniqueness of NBS (Nash Bargaining Solution) for the new utility in cooperative game. The simulation results show that the new algorithm can reflect the secondary users' priorities of spectrum allocation by setting the parameters properly and make sure the spectrum allocation becomes more efficient and fair.

Repeated Game-Inspired Spectrum Sharing for Clustering Cognitive Ad Hoc Networks

“…This is because the revenue is tending towards stable condition. Compared with the spectrum allocation algorithm in [13], it is shown clearly that our spectrum-sharing strategy outperforms the algorithm in [13], and the algorithm in [13] only performs well at high SNR.…”

“…(a) Total rate revenue compared with [13]. (b) Total rate revenue versus number of stages for different discount factors.…”

“…It is shown that the SUs can get the highest rate utility only by announcing their true private information under the assumption that all the SUs have the same maximal transmission power. Based on the Nash bargaining in cooperative game, an improved utility function is proposed in [13] to maximize the profit product of all the SUs.…”