非理想感知下的认知无线电IoT网络性能分析
Queuing Analysis of Opportunistic Cognitive Radio IoT Network with Imperfect Sensing
摘要：
在本文中，我们分析了一个基于认知无线电的物联网（CR-IoT）网络，包括一个主网络提供商（PNP）和一个物联网运营商。PNP使用其许可频谱为其用户提供服务。物联网运营商定期识别授权频段中的空白频段，并伺机利用它们为其覆盖范围内的物联网节点提供服务。物联网节点是电池供电的设备，需要定期补充能量。我们采用微波功率传输（MPT）技术，其优越的能量传输效率在长距离。白空间检测过程并不总是完美的，物联网运营商可能会由于误检测而危及PNP的传输。为了减少这种干扰的可能性，即使物联网节点有数据要传输，一些频谱漏洞也必须保持未利用状态。物联网运营商需要决定保留未利用的空白空间的百分比，以及如何明智地使用剩余的数据传输和能量补充，以保持PNP用户受到的平均干扰与物联网节点体验的服务质量（QoS）之间的最佳平衡。由于频谱感知过程的周期性，离散时间马尔可夫链（DTMC）方法可以真实地模拟这种框架。在文献中，PNP和物联网运营商的活动被假设为相互排斥，以便于分析。我们的模型包含了这些活动之间可能的重叠，使分析更加现实。使用我们的模型，可以获得CR-IoT网络的可持续性区域。我们的分析的准确性证明通过广泛的模拟。
英文摘要：
In this paper, we analyze a Cognitive Radio-based Internet-of-Things (CR-IoT) network comprising a Primary Network Provider (PNP) and an IoT operator. The PNP uses its licensed spectrum to serve its users. The IoT operator identifies the white-space in the licensed band at regular intervals and opportunistically exploits them to serve the IoT nodes under its coverage. IoT nodes are battery-operated devices that require periodical energy replenishment. We employ the Microwave Power Transfer (MPT) technique for its superior energy transfer efficiency over long-distance. The white-space detection process is not always perfect and the IoT operator may jeopardize the PNP's transmissions due to misdetection. To reduce the possibility of such interferences, some of the spectrum holes must remain unutilized, even when the IoT nodes have data to transmit. The IoT operator needs to decide what percentage of the white-space to keep unutilized and how to judiciously use the rest for data transmission and energy-replenishment to maintain an optimal balance between the average interference inflicted on PNP's users and the Quality-of-Service (QoS) experienced by IoT nodes. Due to the periodic nature of the spectrum-sensing process, Discrete Time Markov Chain (DTMC) method can realistically model this framework. In literature, activities of the PNP and IoT operator are assumed to be mutually exclusive, for ease of analysis. Our model incorporates possible overlaps between these activities, making the analysis more realistic. Using our model, the sustainability region of the CR-IoT network can be obtained. The accuracy of our analysis is demonstrated via extensive simulation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
