TY - JOUR
T1 - Connectivity Probability Analysis for Green Cooperative Cognitive Vehicular Networks
AU - Li, Xuan
AU - Zhou, Ruiwei
AU - Zhou, Tianqing
AU - Liu, Lei
AU - Yu, Keping
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022/9/1
Y1 - 2022/9/1
N2 - To meet the increasing demands of green communications for vehicular services, cognitive vehicular networks (CVNs) are expected to improve spectrum efficiency via cognitive radio (CR) technology. The connectivity of CVNs not only related to the communication between cognitive vehicles (CVs), but also detection of idle spectrum. Nevertheless, few existing works simultaneously consider the communication and cognitive probabilities on the road. In this paper, we use probability theory to deduce the connectivity probabilities of CVNs. The analysis scenario consists of two parts: single-hop scenario and multi-hop clustering scenario. Particularly, in multi-hop clustering scenario, we propose Inter-Cluster integration process and Intra-Cluster communication process respectively, and deduce the probability expressions for two cases. The relationships between connectivity and parameters of both channel circumstance and traffic factors are given via theoretical analysis. The simulation results show that connectivity in multi-hop clustering scenario is better than that in single-hop case and the effect of signal-to-noise ratio (SNR) on connectivity is prominent, which indicates that the cognitive probability deeply affects the connectivity probability in CVNs.
AB - To meet the increasing demands of green communications for vehicular services, cognitive vehicular networks (CVNs) are expected to improve spectrum efficiency via cognitive radio (CR) technology. The connectivity of CVNs not only related to the communication between cognitive vehicles (CVs), but also detection of idle spectrum. Nevertheless, few existing works simultaneously consider the communication and cognitive probabilities on the road. In this paper, we use probability theory to deduce the connectivity probabilities of CVNs. The analysis scenario consists of two parts: single-hop scenario and multi-hop clustering scenario. Particularly, in multi-hop clustering scenario, we propose Inter-Cluster integration process and Intra-Cluster communication process respectively, and deduce the probability expressions for two cases. The relationships between connectivity and parameters of both channel circumstance and traffic factors are given via theoretical analysis. The simulation results show that connectivity in multi-hop clustering scenario is better than that in single-hop case and the effect of signal-to-noise ratio (SNR) on connectivity is prominent, which indicates that the cognitive probability deeply affects the connectivity probability in CVNs.
KW - Cognitive vehicular networks
KW - connectivity analysis
KW - green communications
KW - vehicular clustering
UR - http://www.scopus.com/inward/record.url?scp=85126553689&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85126553689&partnerID=8YFLogxK
U2 - 10.1109/TGCN.2022.3158953
DO - 10.1109/TGCN.2022.3158953
M3 - Article
AN - SCOPUS:85126553689
SN - 2473-2400
VL - 6
SP - 1553
EP - 1563
JO - IEEE Transactions on Green Communications and Networking
JF - IEEE Transactions on Green Communications and Networking
IS - 3
ER -