期刊
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
卷 6, 期 2, 页码 195-209出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSTSP.2011.2175699
关键词
Cognitive radio; cooperative games; game theory; sensing and access
资金
- National Science Foundation (NSF) [CNS-0910461, CNS-0953377, CNS-0905556, ECCS-1028782, CNS-1117560, CNS-0832084]
- Research Council of Norway [183311/S10, 176773/S10, 18778/V11]
- Air Force Office of Scientific Research (AFOSR) [FA9550-09-10249]
- Defense Threat Reduction Agency (DTRA) [HDTRA1-07-1-0037]
- Direct For Computer & Info Scie & Enginr
- Division Of Computer and Network Systems [1117560] Funding Source: National Science Foundation
- Division Of Computer and Network Systems
- Direct For Computer & Info Scie & Enginr [0953377] Funding Source: National Science Foundation
Unlicensed secondary users (SUs) in cognitive radio networks are subject to an inherent tradeoff between spectrum sensing and spectrum access. Although each SU has an incentive to sense the primary user (PU) channels for locating spectrum holes, this exploration of the spectrum can come at the expense of a shorter transmission time, and, hence, a possibly smaller capacity for data transmission. This paper investigates the impact of this tradeoff on the cooperative strategies of a network of SUs that seek to cooperate in order to improve their view of the spectrum (sensing), reduce the possibility of interference among each other, and improve their transmission capacity (access). The problem is modeled as a coalitional game in partition form and an algorithm for coalition formation is proposed. Using the proposed algorithm, the SUs can make individual distributed decisions to join or leave a coalition while maximizing their utilities which capture the average time spent for sensing as well as the capacity achieved while accessing the spectrum. It is shown that, by using the proposed algorithm, the SUs can self-organize into a network partition composed of disjoint coalitions, with the members of each coalition cooperating to jointly optimize their sensing and access performance. Simulation results show the performance improvement that the proposed algorithm yields with respect to the noncooperative case. The results also show how the algorithm allows the SUs to self-adapt to changes in the environment such as changes in the traffic of the PUs, or slow mobility.
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