Performance of Cooperative Detection in Joint Communication-Sensing Vehicular Network: A Data Analytic and Stochastic Geometry Approach

Abstract

The increasing complexity of urban environments introduces additional uncertainty to the deployment of the autonomous vehicular network. A novel road infrastructure cooperative detection model using Joint Communication and Sensing (JCS) technology is proposed in this article to simultaneously achieve high-efficient communication and obstacle detection for urban autonomous vehicles. To suppress the performance fluctuation caused by shadowing and obstruction to the JCS signals, we first derive the statistic of road obstacles from the Geographic Information System (GIS). Then, the analysis of JCS channel characteristics and shadowing factors are presented using Line-of-Sight and Non-Line-of-Sight (LoS and NLoS) channel models under the complex urban scenario. A stochastic geometry approach is applied to analyze the interference factors and the probability distribution of successful JCS detection and communication. Simulations have been made to verify the cooperative detection model by probability analysis based on LoS and NLoS channels, and the numerical results demonstrate several different optimization methods for the deployment of JCS road infrastructures. Finally, we simulated and analyzed a deployment optimization method for JCS road infrastructures that complied with the standard of urban traffic-spot structure placement.

On the outage probability of energy harvested cooperative multiuser cognitive NOMA network

“…However, there exist power limitation, multipath fading, interference and noise in CR network, which reduce the reliability of traditional point‐to‐point communication. Cooperative relaying has advantages in terms of resisting the fading of wireless channel, improving the reliability of wireless links and enlarging the coverage of wireless transmission by using the antennas of the cooperative partner [13–16]. Owing to its characteristics, applying cooperative relaying to CR network and building efficient cooperative CR system has been recognized as an effective way to improve system performance [17, 18].…”