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基于认知无线电的低功耗广域网中物联网服务的动态频谱接入

Dynamic Spectrum Access for Internet of Things Service in Cognitive Radio-Enabled LPWANs.

作者信息

Moon Bongkyo

机构信息

Department of Computer Science and Engineering, Dongguk University-Seoul, 30 Pildong-ro 1 gil, Jung-gu, Seoul 04620, Korea.

出版信息

Sensors (Basel). 2017 Dec 5;17(12):2818. doi: 10.3390/s17122818.

Abstract

In this paper, we focus on a dynamic spectrum access strategy for Internet of Things (IoT) applications in two types of radio systems: cellular networks and cognitive radio-enabled low power wide area networks (CR-LPWANs). The spectrum channel contention between the licensed cellular networks and the unlicensed CR-LPWANs, which work with them, only takes place within the cellular radio spectrum range. Our aim is to maximize the spectrum capacity for the unlicensed users while ensuring that it never interferes with the licensed network. Therefore, in this paper we propose a dynamic spectrum access strategy for CR-LPWANs operating in both licensed and unlicensed bands. The simulation and the numerical analysis by using a matrix geometric approach for the strategy are presented. Finally, we obtain the blocking probability of the licensed users, the mean dwell time of the unlicensed user, and the total carried traffic and combined service quality for the licensed and unlicensed users. The results show that the proposed strategy can maximize the spectrum capacity for the unlicensed users using IoT applications as well as keep the service quality of the licensed users independent of them.

摘要

在本文中,我们专注于两种类型无线电系统中物联网(IoT)应用的动态频谱接入策略:蜂窝网络和支持认知无线电的低功耗广域网(CR-LPWAN)。有执照的蜂窝网络与与之协同工作的无执照CR-LPWAN之间的频谱信道争用仅在蜂窝无线电频谱范围内发生。我们的目标是在确保不干扰有执照网络的同时,最大化无执照用户的频谱容量。因此,在本文中,我们为在有执照和无执照频段运行的CR-LPWAN提出了一种动态频谱接入策略。给出了使用矩阵几何方法对该策略进行的仿真和数值分析。最后,我们得到了有执照用户的阻塞概率、无执照用户的平均驻留时间,以及有执照和无执照用户的总承载业务量和综合服务质量。结果表明,所提出的策略可以最大化使用物联网应用的无执照用户的频谱容量,同时保持有执照用户的服务质量不受其影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/832e/5750700/8e0102a6123b/sensors-17-02818-g001.jpg

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本文引用的文献

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A Study of LoRa: Long Range & Low Power Networks for the Internet of Things.
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2
Cognitive radio wireless sensor networks: applications, challenges and research trends.
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