一种基于进化博弈的认知无线电传感器网络高效节能协同频谱感知方案

Xiaolong Ma, Fanzi Zeng, Jisheng Xu
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引用次数: 9

摘要

本文主要研究认知无线电传感器网络中,如何使cr有效协作并最大限度地节约能源。我们建立了一个认知传感器之间的进化博弈模型。为了让认知传感器有效地感知频谱,我们设计了一种贡献-惩罚机制,刺激高信噪比传感器参与频谱感知。此外,为了减少传感器在空闲时的能量浪费,我们引入了周期性睡眠-聆听机制。最后,我们模拟了一个6人多态群体博弈的行为动力学,并将我们提出的机制与非周期性睡眠-聆听机制进行了比较。结果表明,该方案能够有效地激发高信噪比传感器参与频谱感知,提高了系统的能效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel energy efficient cooperative spectrum sensing scheme for cognitive radio sensor network based on evolutionary game
In this paper, we focused on how to get CRs collaborate effectively as well as maximize energy savings in cognitive radio sensor network. We have established a model of evolutionary game between a cognitive sensors. In order to let cognitive sensors sense spectrum effectively, we designed a contribution-punishment mechanism, which can stimulate high SNR sensors to participate in spectrum sensing. Additionally, in order to reduce the wasted energy of sensors in idle, we introduced periodic sleep-listen mechanism. Finally, we simulated behavior dynamics for a 6-player polymorphic population game and compared our proposed scheme with non-periodic sleep-listen mechanism scheme. Result shows that our proposed scheme can stimulate high SNR sensors to participate in spectrum sensing effectively and can make the system more energy efficient.
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