Outage Analysis of Cognitive Electric Vehicular Networks over Mixed RF/VLC Channels

Galymzhan Nauryzbayev, Mohamed Abdallah, Naofal Al-Dhahir

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Modern transportation infrastructures are considered as one of the main sources of the greenhouse gases emitted into the atmosphere. This situation requires the decision-making players to enact the mass use of electric vehicles (EVs) which, in turn, highly demand novel secure communication technologies robust to various cyber-attacks. Therefore, in this paper, a novel jamming-robust communication method is proposed for different outdoor cognitive EV-enabled network scenarios over mixed radio-frequency (RF)/visible light communication (VLC) channels. One EV is designated to act as a relay enabling an aggregator to communicate with a jammed vehicle. This relay operates in both RF and VLC spectrum bands while meeting the interference restrictions defined by the primary network. Considering perfect and imperfect channel state information, exact closed-form analytical expressions are derived for the outage probability and their asymptotic analysis is provided. Moreover, we quantify the outage reduction achievable by deploying such mixed VLC/RF channels. Finally, analytical results are validated by Monte Carlo simulations.

Original languageEnglish
Article number9080067
Pages (from-to)1096-1107
Number of pages12
JournalIEEE Transactions on Cognitive Communications and Networking
Volume6
Issue number3
DOIs
Publication statusPublished - Sept 2020

Keywords

  • Cognitive radio (CR)
  • detect-and-forward (DF)
  • electrical vehicle (EV)
  • outage probability (OP)
  • visible light communication (VLC)

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

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