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Optimal Fusion Techniques for Cooperative Spectrum Sensing in Cognitive Radio Networks

机译:认知无线电网络中协同谱检测的最佳融合技术

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Cooperative Spectrum Sensing (CSS) is a critical component in cognitive radio networks (CRN). It is a scheme used to opportunistically scan the spectrum by multiple CR devices to make collaborative decisions on the presence or absence of the Primary User (PU). It improves the performance on spectrum utilization by exploring the spatial diversity of the cognitive radio networks. Both the selection criterion of cooperating secondary users (SUs) and the fusion schemes used for CSS affect the detection probabilities of the PU. This paper investigates the performance of AND, majority and OR rule fusion techniques. The performance based on an optimal number of collaborating SUs in majority fusion rule is considered and comparison made against OR and AND rules. The optimal number of SUs collaborating in sensing is investigated using Newton Raphson Method. The performance results indicate that majority fusion rule has better detection capability, low total error probability as compared to the OR and AND rules at low SNR.
机译:协同频谱感测(CSS)是认知无线电网络(CRN)中的关键组成部分。它是一种用于机会通过多个CR器件扫描光谱的方案,以在主要用户(PU)的存在或不存在上进行协作决策。它通过探索认知无线电网络的空间多样性来提高频谱利用的性能。合作辅助用户(SUS)的选择标准和用于CSS的融合方案都影响了PU的检测概率。本文调查了融合技术的性能和,大多数和或规则。考虑基于大多数融合规则的最佳协作次数的最佳数量的性能以及反对或和和规则进行比较。使用Newton Raphson方法研究了感测中的最佳数量的感测。性能结果表明,与低SNR的低于或和规则相比,多数融合规则具有更好的检测能力,较低的总误差概率。

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