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Full-Duplex Cooperative Sensing for Spectrum-Heterogeneous Cognitive Radio Networks

机译:频谱异构认知无线电网络的全双工协作感知

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摘要

In cognitive radio networks (CRNs), spectrum sensing is critical for guaranteeing that the opportunistic spectrum access by secondary users (SUs) will not interrupt legitimate primary users (PUs). The application of full-duplex radio to spectrum sensing enables SU to carry out sensing and transmission simultaneously, improving both spectrum awareness and CRN throughput. However, the issue of spectrum sensing with full-duplex radios deployed in heterogeneous environments, where SUs may observe different spectrum activities, has not been addressed. In this paper, we give a first look into this problem and develop a light-weight cooperative sensing framework called PaCoSIF, which involves only a pairwise SU transmitter (SU-Tx) and its receiver (SU-Rx) in cooperation. A dedicated control channel is not required for pairwise cooperative sensing with instantaneous feedback (PaCoSIF) because sensing results are collected and fused via the reverse channel provided by full-duplex radios. We present a detailed protocol description to illustrate how PaCoSIF works. However, it is a challenge to optimize the sensing performance of PaCoSIF since the two sensors suffer from spectrum heterogeneity and different kinds of interference. Our goal is to minimize the false alarm rate of PaCoSIF given the bound on the missed detection rate by adaptively adjusting the detection threshold of each sensor. We derive an expression for the optimal threshold using the Lagrange method and propose a fast binary-searching algorithm to solve it numerically. Simulations show that, with perfect signal-to-interference-and-noise-ratio (SINR) information, PaCoSIF could decrease the false alarm rate and boost CRN throughput significantly against conventional cooperative sensing when SUs are deployed in spectrum-heterogeneous environments. Finally, the impact of SINR error upon the performance of PaCoSIF is evaluated via extensive simulations.
机译:在认知无线电网络(CRN)中,频谱感测对于确保次要用户(SU)的机会性频谱访问不会中断合法的主要用户(PU)至关重要。全双工无线电在频谱感测中的应用使SU能够同时执行感测和传输,从而提高了频谱感知能力和CRN吞吐量。但是,尚未解决在异类环境中部署的全双工无线电的频谱感测问题,SU可能会观察到这些频谱活动。在本文中,我们首先对此问题进行了研究,并开发了一个轻量级的协作传感框架PaCoSIF,该框架仅涉及成对的SU发送器(SU-Tx)和其接收器(SU-Rx)合作。具有即时反馈的成对协同感应(PaCoSIF)不需要专用的控制信道,因为感应结果是通过全双工无线电提供的反向信道收集和融合的。我们提供详细的协议描述,以说明PaCoSIF的工作方式。但是,优化PaCoSIF的感测性能是一个挑战,因为两个传感器都存在频谱异质性和不同种类的干扰。我们的目标是通过自适应地调整每个传感器的检测阈值,使PaCoSIF的误报警率达到给定的漏检率上限。我们使用拉格朗日方法推导了最佳阈值的表达式,并提出了一种快速的二进制搜索算法对其进行数值求解。仿真表明,在频谱异质环境中部署SU时,PaCoSIF具有完美的信噪比(SINR)信息,与传统的协作感测相比,​​PaCoSIF可以降低误报率并显着提高CRN吞吐量。最后,通过广泛的仿真评估了SINR误差对PaCoSIF性能的影响。

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