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Fusion rule and cluster head selection scheme in cooperative spectrum sensing

机译:合作频谱传感中的融合规则与簇头选择方案

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摘要

Cluster based cooperative spectrum sensing (CSS) in cognitive radio networks provides for reduced sensing error, reporting delays and improved energy efficiency, in a practical network. However, achieving these advantages depend on suitably selecting a cluster head and adopting an appropriate fusion rule. This work investigates a new hard decision fusion rule, which makes the cluster heads non-cooperative sensing result a necessary condition for cooperative decision making. The study also presents a comparative numerical study of three existing cluster head selection schemes with respect to their performance in CSS, under varying detection thresholds and cluster's heterogeneity. A robust and generalised cluster head selection scheme that overcomes the limitations of the existing schemes is thereafter proposed. The performance of the existing cluster head selection schemes depends on the distribution of secondary users relative to the primary user's position, and the detection threshold. Simulation results show that the proposed cluster head selection scheme can overcome the limitations of existing schemes. Furthermore, the hard decision fusion rule being proposed indicates improved performance compared with the OR rule in minimising the total error rate over Rayleigh fading channels.
机译:认知无线电网络中基于集群的协作频谱感测(CSS)提供了减少的感测误差,报告延迟和实际网络中的能效。 However, achieving these advantages depend on suitably selecting a cluster head and adopting an appropriate fusion rule.这项工作调查了一个新的硬决策融合规则,使得群集头部不合作传感结果是合作决策的必要条件。该研究还提出了三个现有的簇头选择方案的比较数值研究,相对于CSS的性能,在不同的检测阈值和集群的异质性下。此后提出了一种克服现有方案的局限性的鲁棒和广义的簇头选择方案。现有群集头选择方案的性能取决于辅助用户相对于主用户位置的分布以及检测阈值。仿真结果表明,拟议的集群头选择方案可以克服现有方案的局限性。此外,所提出的硬判决融合规则表明与最小化瑞利衰落通道的总误差率最小化或规则相比,性能提高。

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