Paper Info
Title
A Fluid Mechanics-Based Model to Estimate VINET Capacity in an Urban Scene
Abstract
Accurate estimation of network capacity is very important for Vehicular Infrastructure-based NETwork (VINET) in an urban scene that may involve greatly dynamic typology and complex driving conditions. The node mobility, network behavior, and network scale of' a VINET are different from those of a wireless network, and, therefore, the existing capacity estimation methods of wireless networks cannot be used to estimate VINET capacity. In addition, most existing studies on VINET capacity only derive asymptotic descriptions when the number of nodes is large enough. In this work, a novel approach is proposed for the modeling and calculating VINET capacity. More specifically, we first analyze communication characteristics in a VINET, and introduce two transmission modes, i.e., a vehicle-based mode and a Road Side Unit (RSU)-based one. Then, we propose a probability-based transmission mode selecting strategy with which vehicle nodes can choose either transmission mode independently and such choice is probabilistic. Next, we analyze the characteristics of an RSU-based mode, divide a VINET into a number of communities according to the position and communication range of RSUs, and derive the capacity contributed by an RSU-based mode. Then, we calculate the capacity contributed by a vehicle-based mode based on fluid mechanics. Finally, the VINET capacity can be calculated. The proposed VINET capacity estimation approach is validated to be consistent with simulation results.
Year
DOI
Venue
2022
10.1109/TITS.2021.3083812
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
Keywords
DocType
Volume
Vehicular infrastructure-based networks, VINET capacity, interference community, fluid mechanics
Journal
23
Issue
ISSN
Citations 
7
1524-9050
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Jiujun Cheng116610.39
Guiyuan Yuan200.34
MengChu Zhou38989534.94
Shangce Gao401.35
Cong Liu502.37
Changjun Jiang61350117.57