Application aware networks' resource selection decision making technique using group mobility in vehicular cognitive radio networks

Nowadays detonation of holding vehicle has wrought overcrowded traffic. The US Federal Communication Commission officially allocated nearly 75 MHz spectrum in 5.8 GHz band to support vehicular communication and many studies found this band incapable to handle the demand for future data traffic. The application of Cognitive Radio (CR) technology will be utilized to make the Internet of Vehicles (IoV) environment in order to increase the spectrum resource opportunities available for vehicular communication. In the CR networks environment, each network supporting multiple attributes likes mobility, Quality of Service, data rates and bandwidth. Therefore, new challenges including link failures, network volatility, group mobility and decision making for the fair selection of optimal networks' resource in vehicular CR networks have become the focus of the global concern. Contrarily, future applications require the vehicular CR networks to support safety and non-safety applications and services. The contribution of this article is two folds. First, the group mobility feature of vehicular communication is considered in this work and two techniques (GRA based Vehicular CR node Assisted Networks' resource Selection (VANS) and Network Assisted Networks' resource Selection (NANS)) for vehicular CR networks are proposed. Second, a testbed using coded scripting programme and LabVIEW communications system design suite software to universal software radio peripheral (USRP-2954) is considered to analyze the practical realization issues in vehicular CR networks. Furthermore, the performance of the proposed techniques is analyzed and validated through experimental testbed and compared with the conventional decision-making techniques. Results show that the proposed techniques have outperformed traditional techniques.

Language

  • English

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Filing Info

  • Accession Number: 01743041
  • Record Type: Publication
  • Files: TRIS
  • Created Date: May 6 2020 3:05PM