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A Cooperative Bayesian Nonparametric Framework for Primary User Activity Monitoring in Cognitive Radio Networks

机译:认知无线电网络中用于主要用户活动监控的合作贝叶斯非参数框架

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摘要

This paper introduces a novel approach that enables a number of cognitive radio devices that are observing the availability pattern of a number of primary users (PUs), to cooperate and use Bayesian nonparametric techniques to estimate the distributions of the PUs' activity pattern. To address this problem, a coalitional game is formulated between the cognitive devices and an algorithm for cooperative coalition formation is proposed. It is shown that the proposed coalition formation algorithm allows the cognitive nodes that are experiencing a similar behavior from some PUs to self-organize into disjoint, independent coalitions. Inside each coalition, the cooperative cognitive nodes use Bayesian nonparametric techniques so as to improve the accuracy of the estimated PUs' activity distributions. Simulation results show that the proposed algorithm significantly improves the estimates of the PUs' activity patterns.
机译:本文介绍了一种新颖的方法,该方法使许多正在观察大量主要用户(PU)可用性模式的认知无线电设备能够合作并使用贝叶斯非参数技术来估计PU活动模式的分布。为了解决这个问题,在认知设备之间建立了联盟博弈,并提出了一种合作联盟形成算法。结果表明,所提出的联盟形成算法允许正在从某些PU中经历类似行为的认知节点自组织成不相交的独立联盟。在每个联盟内部,合作认知节点使用贝叶斯非参数技术,以提高估计的PU活动分布的准确性。仿真结果表明,该算法大大提高了PU的活动模式估计。

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