Geometry-Based Propagation Modeling and Simulation of Vehicle-to-Infrastructure Links

Aygün, Bengi; Boban, Mate; Vilela, João P.; Wyglinski, Alexander M.

doi:10.1109/vtcspring.2016.7504262

Cited by 21 publications

(12 citation statements)

References 13 publications

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“…The model uses restriction parameters like the maximum acceleration and deceleration, maximum velocity, length of the vehicle, and driver's imperfection in holding the safe velocity, [37]. SUMO has been extensively applied in different projects related to network performance, traffic assignment, vehicle routing, traffic analysis [39], traffic emission, V2X [40] and other diverse traffic issues.…”

Section: B Osm Josm Sumomentioning

confidence: 99%

Spatial V2X Traffic Density Channel Characterization for Urban Environments

Granda

Azpilicueta

Celaya-Echarri

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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In this work, Vehicle-to-everything (V2X) wireless communications performance is analyzed, in order to account for inherent scenario complexity, in the deployment phase of wireless systems towards the implementation of a Context Aware environment. An urban environment has been simulated by means of an in-house three-dimensional (3D) Ray Launching algorithm, coupled with a microscopic vehicular movement simulator, accounting for embedded urban elements as well as variable traffic densities within the complex environment. Largescale and small-scale results are presented, as well as statistical analysis of the impact of different traffic densities. A campaign of measurements in the same real scenario has been performed, showing good agreement with wireless channel estimations for the considered frequency. These results can aid in V2X deployment configurations in urban environments, in order to minimize power consumption, optimize interference levels and increase overall system performance.

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Section: B Osm Josm Sumomentioning

confidence: 99%

Spatial V2X Traffic Density Channel Characterization for Urban Environments

Granda

Azpilicueta

Celaya-Echarri

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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“…In [18] it is shown that the non line of sight received signal strength is very weak due to buildings and other roadside obstacles. Furthermore, [19] shows that intersections have specific propagation characteristics that can favor or not the radio propagation.…”

Section: Canyon Effectmentioning

confidence: 99%

Vehicle to Infrastructure Communications Design in Urban Hyperfractals

Popescu

Jacquet

2018

2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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Abstract-The goal of this study is to increase the awareness about the communication opportunities that arise in urban vehicle networks when exploiting the self-similarity and hierarchical organization of modern cities. The work uses our innovative model called "hyperfractal" that captures the self-similarity of the urban vehicular networks as well as incorporating road-side infrastructure with its own self-similarity.We use analytical tools to provide achievable trade-offs in operating the road-side units under the constraint of minimum routing path delay while maintaining a reasonably balanced load.The models and results are supported by simulations with different city hyperfractal dimensions in two different routing scenarios: nearest neighbor routing with no collision and minimum delay routing model assuming slotted Aloha, signal to interference ratio (SIR) capture condition, power-path loss, Rayleigh fading.

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“…The design of accurate propagation models for realistic V2I enabling must take into account some unique characteristics in terms of antenna heights, placement of the RSUs, environment type (e.g., urban, suburban, highway) and specific considerations for small-scale fading due to particular location of antennas [ 17 ]. Urban environments are characterized by the combination of different object types such as buildings, vehicles, pedestrians, vegetation etc., as well as their number, size, and density, that have a profound impact on radio propagation [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

Deterministic Propagation Modeling for Intelligent Vehicle Communication in Smart Cities

Granda

Azpilicueta

Vargas-Rosales

et al. 2018

Sensors

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Vehicular Ad Hoc Networks (VANETs) are envisaged to be a critical building block of Smart Cities and Intelligent Transportation System (ITS) where applications for pollution, congestion reduction, vehicle mobility improvement, accident prevention and safer roads are some of the VANETs expected benefits towards Intelligent Vehicle Communications. Although there is a significant research effort in Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) communication radio channel characterization, the use of a deterministic approach as a complement of theoretical and empirical models is required to understand more accurately the propagation phenomena in urban environments. In this work, a deterministic computational tool based on an in-house 3D Ray-Launching algorithm is used to represent and analyze large-scale and small-scale urban radio propagation phenomena, including vehicle movement effects on each of the multipath components. In addition, network parameters such as throughput, packet loss and jitter, have been obtained by means of a set of experimental measurements for different V2I and V2V links. Results show the impact of factors such as distance, frequency, location of antenna transmitters (TX), obstacles and vehicle speed. These results are useful for radio-planning Wireless Sensor Networks (WSNs) designers and deployment of urban Road Side Units (RSUs).

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Geometry-Based Propagation Modeling and Simulation of Vehicle-to-Infrastructure Links

Cited by 21 publications

References 13 publications

Spatial V2X Traffic Density Channel Characterization for Urban Environments

Spatial V2X Traffic Density Channel Characterization for Urban Environments

Vehicle to Infrastructure Communications Design in Urban Hyperfractals

Deterministic Propagation Modeling for Intelligent Vehicle Communication in Smart Cities

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