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Yanmin Zhu 1, 2 and Wei Sun 1 and Jiadi Yu 1 and Tong Liu 1 and Bo Li 1, 3
Academic Editor:Yu Wang
1, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2, Shanghai Key Laboratory of Scalable Computing and Systems, Shanghai 200240, China
3, Hong Kong University of Science and Technology, Sai Kung, Hong Kong
Received 2 July 2014; Revised 24 October 2014; Accepted 2 November 2014; 25 November 2014
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction
With the increasing development of wireless communications, the scarcity of spectrum becomes more and more serious. Some allocated spectrum may not be used all the time. Many prior studies [1-3] show that the radio spectrum is underutilized in the real world. To make better use of the limited radio spectrum resource, cognitive radios [4] are becoming popular. The spectrum utilization can be largely improved by sharing the allocated spectrum of a primary user (PU) with those of secondary users (SUs) when the radio spectrum is not in use.
In this paper, we consider the problem of sharing the allocated spectrum owned by a PU to a set of SUs. Essentially, we consider a cognitive radio network consisting of one PU, the licensed owner of spectrum, and several SUs without licenses. Each secondary user consists of a pair of nodes, a sender, and a receiver, which have the demand of transmitting data over a wireless channel. A cost is incurred from the primary user when allocating some radio spectrum to secondary users. Each secondary user obtains a certain utility for transmitting data. The objective of spectrum sharing in such a cognitive radio network is to maximize the social welfare , which is defined as the sum of the utilities obtained by all secondary users minus the cost paid by the primary user.
A number of existing studies [5, 6] have been conducted for spectrum sharing in cognitive radio networks. Some of these studies [7-9] apply game theory to model interactions between PU and SU in a cognitive radio network. However, they...