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A Reliable Energy and Spectral Efficient Spectrum Sensing Approach for Cognitive Radio Based IoT Networks

机译:一种可靠的能量和谱有效频谱传感方法,用于认知无线电信带网络

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The Internet of Things (IoT) enables the connectivity of disparate devices and the exchange of real-time data among those devices. It requires large amounts of bandwidth to ensure the quality of service (QoS), but sufficient bandwidth is not always available due to the limited frequency spectrum allocated for wireless data communication. Cognitive radio (CR) is a promising technology that enhances the utilization of the spectrum by allowing unlicensed users/secondary users (SU) access to the licensed primary users (PU) spectrum under certain conditions. The CR based IoT (CR-IoT) network can overcome the spectrum scarcity problem in a conventional IoT network. In a CR-IoT network, energy efficiency must be considered for avoiding interference between the PU and the SU, as the conventional energy detection (ED) technologies consume significant energy for CR operations. To mitigate this problem, we propose a novel energy efficient sequential ED spectrum sensing technique which enhances the sensing duration of each unlicensed CR-IoT user/SU by utilizing the reporting time slot when compared to the conventional non-sequential ED spectrum sensing scheme. In addition, each unlicensed CR-IoT user calculates the weight factor based on the Kullback Liebler Divergence score, which enhances the detection performance. Thereafter, each CR-IoT user in the CR-IoT network sequentially passes on both the local sensing result and the weight factor to the corresponding fusion center (FC) via the allocated reporting channel, which extends the sensing time duration of the CR-IoT user. The FC uses the local sensing result and the weight factor of each CR-IoT user to make a global decision by using the soft fusion rule. The results obtained through simulations show that the proposed sequential ED spectrum sensing scheme achieves a better sensing performance, an enhanced sum rate, an enhanced energy and spectral efficiency when compared to the conventional non-sequential ED spectrum sensing scheme with interference constraints.
机译:事物互联网(物联网)可以在这些设备之间连接不同的设备和实时数据的交换。它需要大量的带宽来确保服务质量(QoS),但由于为无线数据通信分配的有限频谱,并且由于为无线数据通信分配的有限频谱而且,不始终可用。认知无线电(CR)是一种有前途的技术,可以通过允许未经许可的用户/二次用户(SU)在某些条件下访问许可的主要用户(PU)频谱来增强频谱的利用。基于CR基的IOT(CR-IOT)网络可以克服传统的物联网网络中的频谱稀缺问题。在CR-IOT网络中,必须考虑避免PU和SU之间的干扰的能量效率,因为传统的能量检测(ED)技术消耗CR操作的显着能量。为了缓解该问题,我们提出了一种新颖的节能顺序ED频谱感测技术,其通过利用报告时隙与传统的非顺序ED光谱感测方案相比,通过利用报告时隙来增强每个未经许可的CR-IOT用户/ SU的感测持续时间。此外,每个未许可的CR-IOT用户基于Kullback Leebler发散评分计算权重因子,这提高了检测性能。此后,CR-IOT网络中的每个CR-IOT用户通过分配的报告信道顺序地将本地感测结果和权重因子(FC)顺序地传递给相应的融合中心(FC),这延伸了CR-IOT的感测时间持续时间用户。 FC使用本地感测结果和每个CR-IOT用户的权重因子来使用软融合规则来制定全局决定。通过模拟获得的结果表明,与具有干扰约束的传统非顺序ED频谱感测方案相比,所提出的连续ED频谱感测方案达到更好的感测性能,增强的总和率,增强的能量和光谱效率。

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