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Efficient cooperative spectrum sensing in Cognitive Radio using coalitional game model

机译:联盟游戏模型的认知无线电有效的合作频谱感应

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The performance of spectrum sensing is limited by noise uncertainty, multipath fading, and shadowing, which are the fundamental characteristics of wireless channels. If the Primary User (PU) signal experiences deep fading or blocked by obstacles, the power of the received PU signal at the Secondary User (SU) may be too weak to be detected. If the SU transmitter cannot detect the presence of the PU transmitter while the PU receiver is within the transmission range of the SU, the transmission of the PU will be interfered. To address this problem, CSS has been shown to be an effective method to improve the detection performance by exploiting spatial diversity. In this paper, we investigate the optimality of cooperation scheme using coalitional game theory. The cognitive behavior i.e. observe, learn and act can be modelled effectively in game theory to study, model and analyze the strategic interactions among Cognitive Radio (CR) users. This paper describes the analytical insights of coalitional game theory for CSS in cognitive radio, highlighting techniques for identifying steady states, convergence and steady state optimality. We critically assess the techniques available in the literature, and then describe our ongoing work applying our insights to algorithm design for cognitive radios using Game theory.
机译:频谱传感的性能受到噪声不确定性,多径衰落和阴影的限制,这是无线信道的基本特征。如果主用户(PU)信号经历深衰落或被障碍阻挡,则辅助用户(SU)处的接收PU信号的功率可能太弱而无法检测到。如果SU发射器不能检测到PU发射器的存在,而PU接收器在SU的传输范围内,则PU的传输将受到干扰。为了解决这个问题,已经证明了CSS是通过利用空间分集来改善检测性能的有效方法。在本文中,我们研究了采用联盟博弈论的合作方案的最优性。在博弈论中可以有效地建模的认知行为,即观察,学习和行动,以便研究,模型和分析认知无线电(CR)用户中的战略互动。本文介绍了CSS在认知无线电中CSS的分析识别,突出了识别稳态状态,收敛性和稳态最优的技术。我们批判性地评估文献中可用的技术,然后描述我们使用博弈理论的认知收音机算法设计的持续工作。

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