TY - JOUR
T1 - Outage Analysis of Cognitive Electric Vehicular Networks over Mixed RF/VLC Channels
AU - Nauryzbayev, Galymzhan
AU - Abdallah, Mohamed
AU - Al-Dhahir, Naofal
N1 - Funding Information:
Manuscript received January 29, 2019; revised November 30, 2019 and March 25, 2020; accepted April 21, 2020. Date of publication April 28, 2020; date of current version September 9, 2020. This publication was supported by the Nazarbayev University Faculty Development Competitive Research Program under Grant 240919FD3935. The associate editor coordinating the review of this article and approving it for publication was T. Watanabe. (Corresponding author: Galymzhan Nauryzbayev.) Galymzhan Nauryzbayev is with the Department of Electrical and Computer Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan 010000, Kazakhstan (e-mail: [email protected]).
Publisher Copyright:
© 2015 IEEE.
PY - 2020/9
Y1 - 2020/9
N2 - 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.
AB - 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.
KW - Cognitive radio (CR)
KW - detect-and-forward (DF)
KW - electrical vehicle (EV)
KW - outage probability (OP)
KW - visible light communication (VLC)
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U2 - 10.1109/TCCN.2020.2990771
DO - 10.1109/TCCN.2020.2990771
M3 - Article
AN - SCOPUS:85091570876
SN - 2332-7731
VL - 6
SP - 1096
EP - 1107
JO - IEEE Transactions on Cognitive Communications and Networking
JF - IEEE Transactions on Cognitive Communications and Networking
IS - 3
M1 - 9080067
ER -