A Simulation Framework for V2V Wireless Systems · A Simulation Framework for V2V Wireless Systems...

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A Simulation Framework for V2V Wireless Systems CHRISTIAN NELSON, CARL GUSTAFSON, FREDRIK TUFVESSON DEPARTMENT OF ELECTRICAL AND INFORMATION TECHNOLOGY, LUND UNIVERSITY, SWEDEN IN COLLABORATION WITH ALEXEY VINEL AND NIKITA LYAMIN SCHOOL OF INFORMATION SCIENCE, COMPUTER AND ELECTRICAL ENGINEERING, HALMSTAD UNIVERSITY, SWEDEN

Transcript of A Simulation Framework for V2V Wireless Systems · A Simulation Framework for V2V Wireless Systems...

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A Simulation Framework for V2V Wireless SystemsCHRISTIAN NELSON, CARL GUSTAFSON, FREDRIK TUFVESSON

DEPARTMENT OF ELECTRICAL AND INFORMATION TECHNOLOGY, LUND UNIVERSITY, SWEDEN

IN COLLABORATION WITH ALEXEY VINEL AND NIKITA LYAMIN

SCHOOL OF INFORMATION SCIENCE, COMPUTER AND ELECTRICAL ENGINEERING,

HALMSTAD UNIVERSITY, SWEDEN

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Motivation

• We need realistic simulations that we can rely on for network evaluations.

• Outputs are for example, with realistic time behavior

– Received power

– Packet loss / Bit error rate

• With this information researchers and engineers working with different control

loops for the vehicles have more sound input into their models and simulations.

• This is ongoing work, hence there will be no pretty plots at the end.

Christian Nelson, IEEE VTS Workshop on Wireless Vehicular Communications, November 2016. 2

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Vehicular wireless communications

• Enables increased road safety and traffic efficiency by using

– Vehicle-to-Vehicle (V2V) communication,

– Vehicle-to-Infrastructure (V2I) communication.

• Improved safety: Collision warning, intersection assistance, congestion alert, etc.

• Cooperative ITS: Reduced emissions, improved traffic flow.

• Autonomous vehicles

• Improved positioning

• We need a cross layer approach. Within ELLIIT we have worked in

collaboration with Halmstad University to achieve this.

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Vehicular wireless communication systems

• Intelligent Transportation Systems (ITS) typically use the dedicated 5.9 GHz

band.

• Key technologies are

– IEEE802.11p standard,

– First version of LTE-V2X, available early 20171.

• In early ITS, these technologies will have to coexist.

1 ericsson.com, “LTE for Intelligent Transport Systems”, June 9, 2016.

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V2X wireless channels

• V2V channels are significantly different from conventional cellular channels

– Different propagation environments,

– Tx and Rx approximately at the same height,

– Higher mobility.

• V2I channels are more similar to cellular channels (base station static), but still

differ in mobility and environment.

→ Specific channel models are needed!

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Different scenarios

• Urban

– Parked vehicles.

– Buildings.

– Intersections.

• Rural

– Often LOS.

– Few vehicles.

• Highway

– Many moving vehicles.

– Higher speeds.

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Why do we need a simulation framework?

• Measurement campaigns are crucial since

– Realistic channel models are derived from these measurements.

– They can be used as input to the simulation framework.

• But, V2X measurement campaigns are,

– Time consuming and expensive,

– Involve fewer vehicles compared to a full-scale deployment,

– Not easy to capture all aspects of V2X systems and scenarios.

• By using a simulation framework, these drawbacks can be addressed!

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V2V Simulation Framework Challenges

A V2X system simulation should ideally include all important layers for various scenarios:

Physical (PHY)Medium Access Control

(MAC)Network (NET)

Highway

Urban

Rural

Intersections

Multi-link

Platooning

Congestion

etc.

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Simulation Framework Summary

OMNeT++ / OMNEST

Plexe-Veins

Plexe-SUMO

RoadTrafficSimulation

Interface

PHY Layer

MAC Layer

Mobility

Inspired by http://veins.car2x.org/documentation/veins-arch.png

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V2V System Simulation Framework

OMNeT++ - Discrete Event Simulator, (https://omnetpp.org)

Veins - Vehicles in Network Simulation, (http://veins.car2x.org)

Sumo - Simulation of Urban Mobility, (http://www.sumo.dlr.de)

Plexe - Platooning Extension for Veins, (http://plexe.car2x.org)

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OMNeT++

Objective Modular Network Testbed in C++

• A C++ class library

• Simulation control

• Utility classes

– random number generation

– statistics collection

– topology discovery

– etc…

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SUMO – Simulation of Urban Mobility

• Traffic simulation tool. It supports simulation of

– Vehicles, public transportation and

pedestrians.

– Traffic lights.

– User generated traffic flow or model based.

– Road network and buildings can be imported

from OpenStreetMap.

– (1:42)

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Veins – Vehicles in Networks Simulation

• Module under OMNeT++.

• Connects SUMO with models for the PHY and MAC layers.

• Includes an implementation of e.g. IEEE802.11p.

• LTE-extension available.

• Simpler models for the propagation channel.

• We are working on improved channel models.

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Plexe – The Platooning Extension for Veins

• Adds the ability for realistic platooning simulations.

– Vehicle dynamics.

– Different cruise control systems.

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Simulation Framework Summary

OMNeT++ / OMNEST

Plexe-Veins

Plexe-SUMO

RoadTrafficSimulation

Interface

PHY Layer

MAC Layer

Mobility

Inspired by http://veins.car2x.org/documentation/veins-arch.png

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What is missing?

• Improved pathloss models.

• Autocorrelation.

• Separation/model selection for LOS/OLOS.

• Cross-correlation modelling of multilink systems.

• The vehicles in a platoon in Plexe-SUMO, drive in a perfect straight line.

– Need to add some randomness/noise in the lateral movement.

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Two-ray and single-slope pathloss models

Two-ray LOS Single-slope OLOS

[Nilsson et al, Trans Veh Tech, submitted]

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Two-ray pathloss model

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[Nilsson et al, Trans Veh Tech, submitted]

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Autocorrelation

• We also include an autocorrelation function.

• This is based on extensive measurements for several different link pairs.

• Will be modelled as an exponential decay 𝜌 = 𝑒− Τ∆𝑡 𝑇𝑐

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Cross-correlation

• Multilink

– Based on extensive measurements.

• Cross-correlation

• If we take care of the geometrical

information regarding LOS and OLOS,

then we can neglect cross-correlation on

highway for typical scenarios.

[Nilsson et al, Trans Veh Tech, submitted]

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Model validation

• Since it is possible to import

GPS routes into SUMO,

one can simulate a scenario

with an implemented model

on a route for which we

have real measurements.

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Current and future work

• With the presented framework it is possible to perform realistic cross-layer

geometry based simulations including:

– Cross-correlation between links,

– Autocorrelation for each link,

– Model validation.

• We will extend this to enable more realistic simulations of platooning scenarios.

• Integrating the control and communication systems for improved cooperative ITS.

• Implement intersection channel model in Veins.

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References and contact information I

• Nilsson, Mikael, et al. “A Measurement Based Multilink Shadowing Model for

V2V Network Simulations of Highway Scenarios.” IEEE Transactions on

Vehicular Technology (Submitted).

• Abbas, Taimoor, et al. "A measurement based shadow fading model for vehicle-

to-vehicle network simulations." International Journal of Antennas and

Propagation 2015 (2015).

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References and contact information II

• Segata, Michele, et al. "PLEXE: A Platooning Extension for Veins," Proceedings

of 6th IEEE Vehicular Networking Conference (VNC 2014), Paderborn, Germany,

December 2014.

• Varga, András. "The OMNeT++ discrete event simulation system."Proceedings of

the European simulation multiconference (ESM’2001). Vol. 9. No. S 185. sn,

2001.

• Christian Nelson

[email protected]

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