Impact of primary user activity statistics in cognitive vehicular networks

• Main Authors: Patel, Dhaval K., Kavaiya, Sagar, Ding, Zhiguo, Guan, Yong Liang, Sun, Sumei
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Electrical and electronic engineering; Primary Activity Statistics; Medium-Dense Traffic
• Online Access: https://hdl.handle.net/10356/163824
• Institution: Nanyang Technological University

Due to the scarcity of channel availability in IEEE 802.11p standard, applications related to infotainment and multimedia services are vulnerable to suffer from delays and connectivity. Cognitive radio (CR) has the potential to overcome the issue of spectrum scarcity. By making use of the CR technology, secondary users (SU) can access a radio frequency spectrum other than 802.11p through spectrum sensing. Majority of low complex existing algorithms are based on energy detection that are considering the static environment of SUs. In practice, the algorithms, which considers mobility are mainly focused on low vehicle speed. However, the combined effect of primary user (PU) activity statistics and SU mobility has not been tackled while evaluating the performance of opportunistic spectrum access. In particular, this work considers the joint impact of PU activity and vehicle mobility on spectrum sensing performance by considering single lane and double lane vehicular scenarios. We also evaluate the impact of traffic densities on sensing performance. The main contribution of this work is to show the impact of PU activity statistics on sensing performance by deriving analytical expressions for miss-detection probability. These expressions are used for analysis and simulation of cognitive radio enabled vehicular communications. From our observations, it is noted that the probability of vehicle connectivity is improved approximately by 50% for initial distance of SU when spectrum sensing is employed under PU activity.