Research Article
Performance analysis of Cognitive Vehicular Networks under Unreliable Backhaul
@ARTICLE{10.4108/eai.8-4-2021.169178, author={Cheng Yin and Zeming Su and Ayse Kortun}, title={Performance analysis of Cognitive Vehicular Networks under Unreliable Backhaul}, journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems}, volume={8}, number={26}, publisher={EAI}, journal_a={INIS}, year={2021}, month={4}, keywords={VANET, Unreliable backhaul, Double-Rayleigh fading, Cognitive radio, Heterogeneous network}, doi={10.4108/eai.8-4-2021.169178} }- Cheng Yin
Zeming Su
Ayse Kortun
Year: 2021
Performance analysis of Cognitive Vehicular Networks under Unreliable Backhaul
INIS
EAI
DOI: 10.4108/eai.8-4-2021.169178
Abstract
This paper presents a comprehensive model including a wireless backhaul as a cost-effective backhaul alternative to wired backhaul for vehicular networks, a heterogeneous underlay cognitive vehicular network with multiple mobile secondary transmitters acting as mobile small cells, a mobile secondary receiver and a mobile primary user. To increase the spectrum utilization in this proposed vehicular network, multiple mobile secondary transmitters forward the signal to a mobile secondary receiver while using the same spectrum with a mobile primary user on the condition that the interference caused by secondary transmitters is tolerable at the primary user. A Bernoulli process is applied to model wireless backhaul reliability. The analytical closed-form expressions for outage probability as well as the asymptotic expression are derived to reveal the effects of backhaul reliability on the network performance over double-Rayleigh fading channels.
Copyright © 2021 Tran Trung Duy et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
