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V2x wireless channel modeling for connected cars Taimoor Abbas - - PowerPoint PPT Presentation

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V2x wireless channel modeling for connected cars Taimoor Abbas Volvo Car Corporations taimoor.abbas@volvocars.com V2X Terminology Background I2N P2N P2I V2N V2I V2P V2V 6/12/2018 SUMMER SCHOOL ON 5G V2X COMMUNICATIONS -

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SLIDE 1

V2x wireless channel modeling for connected cars

Taimoor Abbas Volvo Car Corporations taimoor.abbas@volvocars.com

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SLIDE 2

V2X Terminology

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V2N V2I V2V P2N V2P P2I I2N

Background

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SLIDE 3

Wireless channel

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Transmit antenna Receiver antenna Propagation channel

Radio channel

Background

The wireless channel is a medium used to transmit data wirelessly from the transmitter to the receiver antenna.

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SLIDE 4

Wireless channel

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Background

Why do we need wireless channel modeling? Ideally, modeling a channel means to calculate or estimate all the processing, due to the physical environment, effecting a signal from the transmitter to the receiver. How wireless channel is modeled? Wireless channel is modeled analytically with the help of simulations or empirically by real world measurements. Where it is used? For the wireless system design, it is used for link-level or system simulations as well as to test the hardware especially where control and repeatability is required. It can also be used to bench mark multiple hardware with standard settings. The major benefits are? Easy to use, allow better control and repeatability, cost effective and could be scaled

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SLIDE 5

Propagation mechanism

5

Background

i

r

t

1

2

Reflection and transmission Diffraction Scattering Waveguiding Line-of-sight (LOS) component Multipath components Typical communication scenario

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SLIDE 6

Propagation mechanism (cont.)

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Background

d ARX If we assume the TX/RX antennas to be isotropic being in free space,

2

4

RX TX

P P d     =    

( )

2

4       =  d d Lfree

Path loss Small scale fading Large scale fading

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SLIDE 7

V2V vs v2i

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V2X Channel

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Doppler shift for v2v

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Key Differences in V2V Channel Modeling

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V2X Channel

Wr Wt dr, Truck dt g1 g2, Truck g2, XC90 dr, XC90 Truck Blue S60 XC90 Black g2, XC90

LOS: Line-Of-Sight OLOS: Obstructed Line-Of-Sight NLOS: Non Line-Of-Sight Multilink

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V2X Channel Measurements

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Modeling

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Channel Sounder

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Modeling

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Measurement based modeling

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1 2 3 4

Note:

  • Measurement tool always has certain

limitations

  • It is necessary to keep those limitations

in mind when establishing models based on the measurements

  • For a channel model to be independent
  • f object, it has to be double directional

and antennas need to be calibrated so that the response could be subtracted later on

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SLIDE 13

Measurement campaign step by step

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Antenna calibration Channel sounder mounting Conduction measure- ments

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SLIDE 14

Measurement campaign step by step

6/12/2018 SUMMER SCHOOL ON 5G V2X COMMUNICATIONS - TAIMOOR.ABBAS@VOLVOCARS.COM 14

Antenna calibration Channel sounder mounting Conduction measure- ments

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SLIDE 15

Measurement campaign step by step

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Antenna calibration Channel sounder mounting Conduction measure- ments

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General observations – v2v measurements

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Time-delay characteristics:

100 200 300 400 Propagation distance [m] Power

t = 0 s

100 200 300 400 Propagation distance [m] Power

t = 0.2 s

100 200 300 400 Propagation distance [m] Power

t = 0.4 s

100 200 300 400 Propagation distance [m] Power

t = 0.6 s

100 200 300 400 Propagation distance [m] Power

t = 0.8 s

100 200 300 400 Propagation distance [m] Power

t = 1 s

100 200 300 400 Propagation distance [m] Power

t = 1.3 s

100 200 300 400 Propagation distance [m] Power

t = 1.5 s

100 200 300 400 Propagation distance [m] Power

t = 1.7 s

100 200 300 400 Propagation distance [m] Power

t = 1.9 s

100 200 300 400 Propagation distance [m] Power

t = 2.1 s

100 200 300 400 Propagation distance [m] Power

t = 2.3 s

100 200 300 400 Propagation distance [m] Power

t = 2.5 s

100 200 300 400 Propagation distance [m] Power

t = 2.8 s

100 200 300 400 Propagation distance [m] Power

t = 3 s

100 200 300 400 Propagation distance [m] Power

t = 3.2 s

100 200 300 400 Propagation distance [m] Power

t = 3.4 s

100 200 300 400 Propagation distance [m] Power

t = 3.6 s

100 200 300 400 Propagation distance [m] Power

t = 3.8 s

100 200 300 400 Propagation distance [m] Power

t = 4.1 s

100 200 300 400 Propagation distance [m] Power

t = 4.3 s

100 200 300 400 Propagation distance [m] Power

t = 4.5 s

100 200 300 400 Propagation distance [m] Power

t = 4.7 s

100 200 300 400 Propagation distance [m] Power

t = 4.9 s

100 200 300 400 Propagation distance [m] Power

t = 5.1 s

100 200 300 400 Propagation distance [m] Power

t = 5.3 s

100 200 300 400 Propagation distance [m] Power

t = 5.6 s

RX TX

100 200 300 400 Propagation distance [m] Power

t = 5.8 s

100 200 300 400 Propagation distance [m] Power

t = 6 s

100 200 300 400 Propagation distance [m] Power

t = 6.2 s

LOS

100 200 300 400 Propagation distance [m] Power

t = 6.4 s

100 200 300 400 Propagation distance [m] Power

t = 6.6 s

100 200 300 400 Propagation distance [m] Power

t = 6.9 s

100 200 300 400 Propagation distance [m] Power

t = 7.1 s

100 200 300 400 Propagation distance [m] Power

t = 7.3 s

100 200 300 400 Propagation distance [m] Power

t = 7.5 s

100 200 300 400 Propagation distance [m] Power

t = 7.7 s

100 200 300 400 Propagation distance [m] Power

t = 7.9 s

100 200 300 400 Propagation distance [m] Power

t = 8.1 s

Discrete comp. Diffuse comp. Other vehicles Houses, road signs etc.

  • Rapidly varying channel
  • Discrete components carry significant energy and change delay bin with time
  • Diffuse components following LOS
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SLIDE 17

General observations – v2v measurements

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  • 1500
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500 1000 1500 100 200 300 400 500

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Doppler frequency [Hz] Delay [ns] Power [dB]

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500 1000 1500 100 200 300 400 500

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Doppler frequency [Hz] Delay [ns] Power [dB]

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Doppler frequency [Hz] Delay [ns] Power [dB]

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Doppler frequency [Hz] Delay [ns] Power [dB]

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Doppler frequency [Hz] Delay [ns] Power [dB]

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Doppler frequency [Hz] Delay [ns] Power [dB]

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Doppler frequency [Hz] Delay [ns] Power [dB]

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Doppler frequency [Hz] Delay [ns] Power [dB]

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Doppler frequency [Hz] Delay [ns] Power [dB]

LOS Discrete components Diffuse components

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500 1000 1500 100 200 300 400 500

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Doppler frequency [Hz] Delay [ns] Power [dB]

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Doppler frequency [Hz] Delay [ns] Power [dB]

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Doppler frequency [Hz] Delay [ns] Power [dB]

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500 1000 1500 100 200 300 400 500

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Doppler frequency [Hz] Delay [ns] Power [dB]

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500 1000 1500 100 200 300 400 500

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Doppler frequency [Hz] Delay [ns] Power [dB]

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500 1000 1500 100 200 300 400 500

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500 1000 1500 100 200 300 400 500

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Local scattering function:

  • Discrete components: small Doppler spread, but can change delay bin rapidly
  • Diffuse components: large delay and Doppler spread
  • Time-variant Doppler spectrum → Non-stationary conditions
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Measurement based modeling

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The time during which the local scattering function is ”sufficiently constant” is defined as the stationarity time Highway, opposite direction Highway, same direction Urban, same direction 23 ms 1479 ms 1412 ms

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A geometry based stochastic model

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Diffuse scatterers Mobile discrete scatterers Static discrete scatterers

Adding up all components using different antenna patterns → MIMO channels Dependent on antenna pattern

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Deterministic modeling

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  • Non-measurement based modeling could either

be statistical geometry based of deterministic

  • Deterministic approach, such as ray tracing, can

be very realistic but computationally expensive

  • Moreover, it requires accurate geometry
  • Solve approximation to Maxwell’s equation,

using high-frequency approximation

[Maurer et al. 2004]

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Ray tracing example

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Measurements vs ray tracing

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  • Very good agreement in LOS and near LOS regions.
  • In NLOS, the ray tracing model underestimates the channel

gain.

  • Gap can be reduced by increasing the order of reflection.
  • Contribution of third and higher-order specular and non-

specular reflections is missing in the simulator.

Measuremed PDP Simulated PDP (Ray-tracing) Channel gain

LOS NLOS

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SLIDE 23
  • A channel model is selected based on what part of the communication system

that is going to be studied.

  • For network level simulations, where communication protocols are studied, a

statistical model (e.g., Rician, Rayleigh, and Nakagami) is the predominant channel model type to keep computational time down.

  • For PHY layer, TDLs and geometry-based stochastic and deterministic channel

models are for obvious reasons the preferred channel models.

  • So selection of channel model has to be made very carefully as the channel is
  • ne of the major performance factors
  • To summarize; following is a receipe on the selection and usage of channel

models.

Channel models for test and simulations

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V2X- Channel: Specific considerations

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V2X Channel

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V2x channel models classification

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3GPP TR38.901: V2X-specific Considerations

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3GPP TR38.901: V2X-specific Considerations

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3GPP TR38.901: V2X-specific Considerations

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3GPP TR38.901: V2X-specific Considerations

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3GPP TR38.901: V2X-specific Considerations

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Summary of parameter to be used

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References

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  • I would like to thank my colleagues from Lund University as some of the work is

produced jointly, especially Fredrik Tufvesson, Johan Kåredal and Mikael Nilsson.

  • Special thanks to Mate Boban from Huawei, Munich, for sharing information

about the activities at 3GPP and for the cooperation under the umbrella of 5GCAR on channel modeling. Thank you for listening!

acknowledgement

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SLIDE 34
  • A. Paier, J. Kåredal, N. Czink, C. Dumard, T. Zemen, F. Tufvesson, A. Molisch, C. F. Mecklenbräuker, ”Characterization of

Vehicle-to-Vehicle Radio Channels from Measurements at 5.2GHz,” Wireless Personal Communications, vol. 50, no. 1,

  • pp. 19-29, 2009.
  • J. Kåredal, F. Tufvesson, N. Czink, A. Paier, C. Dumard, T. Zemen, C. Mecklenbräuker, A. Molisch, ”A geometry-based

stochastic MIMO model for vehicle-to-vehicle communications,” IEEE Transactions on Wireless Communications, vol. 8,

  • no. 7, pp. 3646-3657, 2009.
  • A. Molisch, F. Tufvesson, J. Kåredal, C. F. Mecklenbräuker, ”A Survey on Vehicle-to-Vehicle Propagation Channels,” IEEE

Wireless Communications, vol. 16, no. 6, pp. 12-22, 2009.

  • J. Kåredal, F. Tufvesson, T. Abbas, O. Klemp, A. Paier, L. Bernadó, A. Molisch, ”Radio channel measurements at street

intersections for vehicle-to-vehicle applications,” Proc. IEEE Vehicular Technology Conference (VTC2010-spring), Taipei, Taiwan, pp. 1-5, May 16-19, 2010.

  • A. Paier, L. Bernadó, J. Kåredal, O. Klemp, A. Kwoczek, ”Overview of vehicle-to-vehicle radio channel measurements for

collision avoidance applications,” Proc. IEEE Vehicular Technology Conference (VTC2010-spring), Taipei, Taiwan, pp. 1-5, May 16-19, 2010.

  • A. Molisch, F. Tufvesson, J. Kåredal, C. Mecklenbräuker, ”Propagation aspects of vehicle-to-vehicle communications - an
  • verview,” Proc. IEEE Radio and Wirless Symposium (RWS), San Diego, CA, USA, pp. 179-182, Jan. 18-22, 2009.
  • J. Kåredal, F. Tufvesson, N. Czink, A. Paier, C. Dumard, T. Zemen, C. Mecklenbräuker, A. Molisch, ”Measurement-based

modeling of vehicle-to-vehicle MIMO channels,” Proc. IEEE International Conference on Communications (ICC), Dresden, Germany, June 14-18, 2009.

Selected publications

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  • A. Paier, T. Zemen, J. Kåredal, N. Czink, C. Dumard, F. Tufvesson, C. Mecklenbräuker, A. Molisch, ”Spatial diversity and

spatial correlation evaluation of measured vehicle-to-vehicle radio channels at 5.2 GHz,” Proc. IEEE Digital Signal Processing Workshop/Signal Processing Education Workshop (DSP/SPE), pp. 326-330, Jan 1-4, 2009.

  • L. Bernadó, T. Zemen, A. Paier, J. Kåredal, B. Fleury, ”Parametrization of the local scattering function estimator for

vehicular-to-vehicular channels,” Proc. IEEE Vehicular Technology Conference (VTC2009-fall), Anchorage, AK, USA, pp. 1-5, Sept. 20-23, 2009.

  • A. Paier, T. Zemen, L. Bernado, G. Matz, J. Kåredal, N. Czink, C. Dumard, F. Tufvesson, A. Molisch, C. Mecklenbräuker,

”Non-WSSUS vehicular channel characterization in highway and urban scenarios at 5.2 GHz using the local scattering function,” Proc. International Workshop on Smart Antennas (WSA), pp. 9-15, 2008.

  • L. Bernadó, T. Zemen, A. Paier, G. Matz, J. Kåredal, N. Czink, C. Dumard, F. Tufvesson, M. Hagenauer, A. Molisch, C. F.

Mecklenbräuker, ”Non-WSSUS Vehicular Channel Characterization at 5.2 GHz - Spectral Divergence and Time-Variant Coherence Parameters,” Proc. URSI General Assembly, 2008.

  • A. Paier, J. Kåredal, N. Czink, H. Hofstetter, C. Dumard, T. Zemen, F. Tufvesson, C. Mecklenbräuker, A. Molisch,

”First results from car-to-car and car-to-infrastructure radio channel measurements at 5.2GHz,” Proc. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Athens, Greece, pp. 1-5, Sept. 3-7, 2007.

  • A. Paier, J. Kåredal, N. Czink, H. Hofstetter, C. Dumard, T. Zemen, F. Tufvesson, A. Molisch, C. Mecklenbräuker, ”Car-to-

car radio channel measurements at 5 GHz: Pathloss, power-delay profile, and delay-Doppler spectrum,” Proc. IEEE International Symposium on Wireless Communication Systems (ISWCS), Trondheim, Norway, pp. 224-228, Oct. 17-19, 2007.

Selected publications

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SLIDE 36
  • C. Mecklenbräuker, A. Molisch, J. Karedal, F. Tufvesson, A. Paier, L. Bernadó, T. Zemen, O. Klemp, N. Czink: Vehicular

channel characterization and its implications for wireless system design and performance, Proceedings of the IEEE, Vol. 99, No. 7, pp. 1189-1212, 2011.

  • T. Abbas, J. Karedal, F. Tufvesson, A. Paier, L. Bernadó, A. Molisch: Directional Analysis of Vehicle-to-Vehicle Propagation

Channels, IEEE Vehicular Technology Conference, IEEE 73rd Vehicular Technology Conference 2011-spring, Budapest, Hungary, 2011-05-15/2011-05-18.

  • T. Abbas, and F. Tufvesson: Line-of-Sight Obstruction Analysis for Vehicle-to-Vehicle Network Simulations in a Two Lane

Highway Scenario, Hindawi International Journal of Antennas and Propagation, Special Issue on Radio Wave Propagation and Wireless Channel Modeling (In press)

  • T. Abbas, L. Bernadó, A. Thiel, C. F. Mecklenbräuker, and F. Tufvesson: Radio Channel Properties for Vehicular

Communication: Merging Lanes Versus Urban Intersections, IEEE Vehicular Technology Magazine, December, 2013 (Invited paper)

  • T. Abbas, J. Kåredal, and F. Tufvesson: Measurement-Based Analysis: The Effect of Complementary Antennas and

Diversity on Vehicle-to-Vehicle Communication, IEEE Antennas and Wireless Propagation Letters, 2012.

  • T. Abbas, J. Nuckelt, T. Kürner, T. Zemen, C. Mecklenbräuker, and F. Tufvesson: Simulation and Measurement Based

Vehicle-to-Vehicle Channel Characterization: Accuracy and Constraint Analysis (Accepted with major revision, 2014 to IEEE Transactions on Antennas and Propagations).

  • T. Abbas: Measurement Based Channel Characterization and Modeling for Vehicle-to-Vehicle Communications, Series of

licentiate and doctoral dissertations, ISSN 1654-790X (No. 58), Department of Electrical and Information Technology, Lund University, Sweden, 2014.

Selected publications

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SLIDE 37
  • M. Boban, J. Barros, and O. Tonguz, “Geometry-based vehicle-to-vehicle channel modeling for large-scale simulation,”

IEEE Transactions on Vehicular Technology, Vol. 63, No. 9, November 2014

  • Mikael G. Nilsson et. al “On Multilink Shadowing Effects in Measured V2V Channels on Highway”, 2016
  • Mikael G. Nilsson et. al “A Measurement-Based Multilink Shadowing Model for V2V Network simulations of Highway

Scenarios”, 2017

  • Mikael G. Nilsson et. al “A Path Loss and Shadowing Model for Multilink Vehicle-to-Vehicle Channels in Urban

Intersections”, 2018

  • Mate Boban et. Al “Multi-band Spatio-Temporal Characterization of a V2V Environment Under Blockage“, 2018

Selected publications

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