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Connectivity properties for UAVs networks in wireless ultraviolet communication

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Abstract

The ultraviolet (UV) scattering communication can be applied in military networked on-the-move and unattended ground sensor networks. This paper focuses on the connectivity properties of unmanned aerial vehicles (UAVs) network based on UV communication that ensures the secret communications between UAVs. UAVs network is consisting of a group of UAVs, each of which moving according to a particular mobility model. We discuss random waypoint (RWP) mobility model and circle movement based model (CMBM), which can describe the actual movement of UAVs, respectively. In this paper, the approximations of the probability that the network is k-connected are provided with consideration of transmission using on–off keying and pulse position modulation. More precisely, we evaluate the effects of node density, transmission power, and data rate on k-connectivity. The numerical examples show that the mobility degrades the connectivity probability. When the numbers of nodes \(n=500\) and data rate \(R_b =10\,\hbox {kbps}\), the required transmission power for nodes moving according to RWP is lower than CMBM in order to achieve 2-connectivity of the UAVs network, but it is about twice that for uniformly distributed nodes.

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Acknowledgements

This work was supported by Natural Science Foundation of China-Civil Aviation Administration of China Joint Research Fund (No. U1433110), Xi’an beilin science and technology plan projects (No. GX1617), the Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing (No.2016CP05), Scientific Research Program Funded by Shaanxi Provincial Education Department (Program No. 17-JF024) and Fund of Robot Technology Used for Special Environment Key Laboratory of Sichuan Province. We also would like to thank the anonymous reviewers for their comprehensive reviews and comprehensive feedback.

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Zhao, T., Xie, Y. & Zhang, Y. Connectivity properties for UAVs networks in wireless ultraviolet communication. Photon Netw Commun 35, 316–324 (2018). https://doi.org/10.1007/s11107-017-0753-5

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