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频谱异构认知无线电网络的全双工协作感知

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

作者信息

Liu Peng, Qi Wangdong, Yuan En, Wei Li, Zhao Yuexin

机构信息

Department of Network Engineering, P. L. A. Army Engineering University, Nangjing 210007, China.

出版信息

Sensors (Basel). 2017 Aug 2;17(8):1773. doi: 10.3390/s17081773.

Abstract

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.

摘要

在认知无线电网络(CRN)中,频谱感知对于确保次要用户(SU)的机会频谱接入不会干扰合法的主要用户(PU)至关重要。将全双工无线电应用于频谱感知可使SU同时进行感知和传输,从而提高频谱感知能力和CRN吞吐量。然而,在异构环境中部署全双工无线电进行频谱感知的问题尚未得到解决,在这种环境中,SU可能会观察到不同的频谱活动。在本文中,我们首次探讨了这个问题,并开发了一种名为PaCoSIF的轻量级协作感知框架,该框架仅涉及成对的SU发射机(SU-Tx)及其接收机(SU-Rx)进行协作。由于感知结果是通过全双工无线电提供的反向信道收集和融合的,因此成对协作感知(PaCoSIF)与瞬时反馈不需要专用控制信道。我们给出了详细的协议描述来说明PaCoSIF的工作原理。然而,优化PaCoSIF的感知性能是一项挑战,因为这两个传感器存在频谱异构性和不同类型的干扰。我们的目标是在给定误检率界限的情况下,通过自适应调整每个传感器的检测阈值,使PaCoSIF的误报率最小化。我们使用拉格朗日方法推导了最优阈值的表达式,并提出了一种快速二分搜索算法进行数值求解。仿真结果表明,当SU部署在频谱异构环境中时,在具有完美信干噪比(SINR)信息的情况下,PaCoSIF相对于传统协作感知可以显著降低误报率并提高CRN吞吐量。最后,通过大量仿真评估了SINR误差对PaCoSIF性能的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f464/5579765/62b72a88589a/sensors-17-01773-g001.jpg

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