An environmental channel throughput and radio propagation modeling for vehicle-to-vehicle communication

Abstract

Developing a secure and smart intelligent transport system for both safety and non-safety application services requires a certain guarantee of network performance, especially in terms of throughput and packet collision performance. The vehicular ad hoc network propagation is strongly affected due to varying nature of the environment. The existing radio propagation path loss models are designed by using mean additional attenuation sophisticated fading models. However, these models do not consider the obstacle caused due to the obstacle of the vehicle in line of sight of the transmitting and receiving vehicle. Thus, the attenuation signal at the receiving vehicles/devices is affected. To address this issue, we present an obstacle-based radio propagation model that considers the effect caused due to the presence of obstructing vehicle in line of sight. This model is evaluated under different environmental conditions (i.e. city, highway, and rural) by varying the speed of vehicles and vehicles’ density. The performance of the model is evaluated in terms of throughput, collision, transmission efficiency, and packet delivery ratio. The overall result shows that the proposed obstacle-based throughput model is efficient considering varied speed and density. For instance, in the city environment, the model achieves an average improvement of 9.98% and 25.02% for throughput performance over other environments by varying the speed and density of devices respectively and an improvement of 15.04% for packet delivery ratio performance over other environments considering varied speed of devices.

Performance Enriching Channel Allocation Algorithm for Vehicle-to-Vehicle City, Highway and Rural Network

“…The Proposed PECA and existing ENCCMA [13] algorithm was written in C# object oriented programing language using Visual studio framework 4.5, 2012. The PECA and city, highway and rural (CHR) radio propagating environment model [Ours] was incorporated into the SIMITS tool [27,28,29,30]. Experiments were conducted to evaluate the performance of PECA over ENCCMA in terms of throughput achieved, successful packet transmission and packet collision.…”

An IoT-Based Ship Berthing Method Using a Set of Ultrasonic Sensors

“…Similar research and applications has been done in different fields which are similar to our system such as studies based on vehicle to vehicle (V2V) [46,47], vehicle to infrastructure (V2I) [48,49], and device to device (D2D) communications. For example, autonomous driving, road worker, construction zone warning, traffic information (traffic jam ahead warning systems and vehicle-to-grid communications).…”

Resource optimization-based network selection model for heterogeneous wireless networks

“…where 𝑁 𝑦 defines total amount of occupied slot at any given instance of times with steady state probability 𝛿 𝑎 considering presence of obstacle in line of sight [35], [36].…”