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    Cognitive radio aided internet of vehicles (IoVs) for improved spectrum resource allocation

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    Authors
    Yu H
    Eze, Joy C.
    Zhang, Sijing
    Liu, Enjie
    Eze, Elias Chinedum
    Affiliation
    University of Bedfordshire
    Issue Date
    2015-12-28
    Subjects
    spectrum
    VANET
    cognitive radio
    Internet of Vehicles
    
    Metadata
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    Abstract
    The highly anticipated era of Internet of Things (IoTs) expected to empower all aspects of Intelligent Transportation Systems (ITS) will undeniably improve transport safety and significantly reduce road accidents. To promote the communication of mobile vehicles (or IoVs), US FCC officially allocated a merger 75 MHz spectrum in the 5.9 GHz band to enable vehicular communication. In this paper, we studied the application of CR technology to IoVs in order to increase the spectrum resource opportunities especially when the officially allocated 75 MHz spectrum in 5.9 GHz band is not enough due to high demands as a result of increasing number of connected devices as already foreseen in the near era of IoTs. We proposed a novel CRAVNET framework which empowers CR assisted vehicles to make opportunistic usage of licensed spectrum bands on the highways, and developed a novel co-operative three-state spectrum sensing and allocation solution which makes CR vehicular SUs aware of additional spectrum resources opportunities on their current and future positions. Both the simulation and theoretical analysis have demonstrated that our solution can significantly improve the performance of a cooperative spectrum sensing and sharing schemes, and provide vehicles with additional spectrum opportunities with zero interference with the PUs activities.
    Citation
    Eze J, Zhang S, Liu E, Chinedum E, Yu H (2015) 'Cognitive radio aided internet of vehicles (IoVs) for improved spectrum resource allocation', IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing - Liverpool, Institute of Electrical and Electronics Engineers Inc..
    Publisher
    Institute of Electrical and Electronics Engineers Inc.
    URI
    http://hdl.handle.net/10547/624333
    DOI
    10.1109/CIT/IUCC/DASC/PICOM.2015.347
    Additional Links
    https://ieeexplore.ieee.org/document/7363393
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISBN
    9781509001545
    ae974a485f413a2113503eed53cd6c53
    10.1109/CIT/IUCC/DASC/PICOM.2015.347
    Scopus Count
    Collections
    Computing

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