vehicle-to-x communication using millimeter...

Slides © Robert W. Heath Jr. (2016)

Vehicle-to-X communication using millimeter wavesProfessor Robert W. Heath Jr., PhD, PE

Wireless Networking and Communications GroupDepartment of Electrical and Computer EngineeringThe University of Texas at Austin

www.profheath.org

Thanks to sponsors including the U.S. Department of Transportation through the Data-Supported Transportation Operations and Planning (D-STOP) Tier 1 University Transportation Center, the Texas Department of Transportation under Project 0-6877 entitled “Communications and Radar- Supported Transportation Operations and Planning (CAR-STOP)”, National Instruments, Huawei, and Toyota IDC


Motivation

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3

Fifth generation (5G) cellular communication

Multidimensional objectives* New industry verticals**

* Recommendation ITU-R M.2083-0, “IMT Vision – Framework and overall objectives of the future development of IMT for 2020 and beyond,” September 2015** “5G empowering vertical industries,” 5GPPP White Paper, Feb. 2016

Aut

omot

ive

Med

ia &

Ent

erta

inm

ent

e-H

ealth

Higher rates

Lower latency

Fact

ory

of th

e Fu

ture

Ener

gy

Mobility

Spectrumefficiency

Userexp.

data rate

Peakdata rate

Energyefficiency

Areatraffic

capacity

LatencyConnectiondensity


Trends in vehicle automation

4

INCREASING NUMBER OF SENSORS

ADVANCING COMMUNICATION CAPABILITY

* 5G-PPP White Paper on Automotive Vertical Sector, October 2015, https://5g-ppp.eu/white-papers/

Higher automation

levels

TRAFFICEFFICIENCY

AUTOMATEDDRIVING

SAFETY


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Automation levels

Fullyself-driving automation

LEVEL 4

Driver providesdestination

Driver not available for control

Self driving cars

Driver can cedecontrol over a primary function (eg. ACC)Responsible for safe operation

Full driver control at alltimes

Diver can cede full control of all safety-critical functions

Driver does not have to monitor the roadway at all times

LEVEL 3

Limitedself-driving automation

LEVEL 2

Combinedfunction

automation

LEVEL 1

Function specific

automation

LEVEL 0

No automation

Driver can cedecontrol on at least two primary functions

Driver responsible for monitoring the roadway

NHTSA, “Preliminary Statement of Policy Concerning Automated Vehicles”, 2013

Driver assist


Communication for driver assist

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Both communication and automotive sensors are useful

for collision avoidance

Sensors require line-of-sight

Communication can expand sensing range

More informed safety decisions

Limited automation based on sensing + communication to assist driver


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Communication for full automation

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Sharing local sensors information ~ 100x Mbps

for safety app.

Higher data rates and lower latency will be required for full automation

V2X can be used for other functions, for example

more precise navigation

Exchanging raw sensor data provides information for fully automated safety-

critical functions

Downloading high-definition 3D map data (~Gbyte) for precise

navigation


8

Communication for traffic efficiency

V2X helps coordinate traffic through intersections,

eliminating lights

V2X leads to higher levels of traffic coordination like

platooning

Low latency but low rate connectivity may be suffiicent

Download HD 3D map

Upload local sensor data for dynamic map


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Infotainmentapplications

Download multimedia data(movie, music, apps)100x Mbps - Gbps

Mobile base station for passengers

Communication for infotainment

High rate and low latency Internet access required to keep passengers happy


Expand the sensing range of the vehicle

Allows interactions between vehicles with

different automation levels

More informed safety decisions

Communication enhances automated vehicles

Higher levels of traffic coordination like platooning

autonomous


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Ex: Passing on rural roads

What if the bus or oncoming car do not have communication capability?

82% of head-on fatal collisions take place in

rural areas

Radar requires line-of-sight

Both communication and radar are useful for collision avoidance

Alice Chu, Michael Motro, Junil Choi, Abdul Rawoof Pinjari, Chandra R. Bhat, Joydeep Ghosh, and R. W. Heath, Jr., ``Vehicular Ad-Hoc Network (VANET) Simulations Of Overtaking Maneuvers On Two-Lane Rural Highways,'' submitted February 2016.


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Infrastructure has value for automated vehiclesCan be used for other functions, for example

more precise navigation

Supports sensing of the environment, does not require

all cars to have complete sensing equipment

Helps coordinate traffic through intersections,

eliminating lightsEffective with non-connected cars, bicycles, and pedestrians


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Ex: Passing on rural roads

Infrastructure has enhanced sensing, better communication range

Infrastructure w/ sensing can broadcast position, velocity, and acceleration of vehicles

With enough infrastructure, can correctly avoid more

than 95% of collisions


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Key questions

Where is thecommunicationtheory and signalprocessing research?

What are the datarate requirements for

sensors?

What are the capabilities of current automotivecommunication solutions?


State-of-the-art invehicular sensing

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Current technologies for vehicular sensing

Powerful sensing technologies with limited range in traffic conditions

Sensor Range(ideal)

Radar 200m

Camera 100m

LIDAR 100m

Sensor Range(traffic)

Radar 3-5m

Camera 3-5m

LIDAR 3-5m


Sensor applications and data rates

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Automotive sensors generate a huge amount of data

Purpose Drawback Datarate Update rateRadar Targetdetection,

velocityestimation

Hardtodistinguishtargets

Lessthan1Mbps

50-100ms

Camera Virtualmirrorsfordrivers

Needcomputervisiontechniques

100-700Mbpsforrawimages,10-90Mbpsforcompressedimages

60-100 ms

LIDAR Targetdetectionandrecognition,velocityestimation

Highcost 10-100Mbps 67-200ms


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State-of-the-art inconnected cars


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Connectivity for automated vehicles

Connectivity gives access to a

richer set of sensor data

Connectivity solves key challenges of

automated driving in congested urban areas

Connectivity motivates 5G and the

application of millimeter wave

Automated cars may have limited connectivity

Is it possible to exchange raw sensor data between cars with current technology?

Automated carsshould exploit connectivity


DSRC: current technology for vehicular communications

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!

Forward collision warning, do not pass warning, blind intersection warning, etc.

Based on IEEE 802.11p, IEEE 1609.x, SAE standards

* NHTSA, “Vehicle-to-Vehicle Communications: Readiness of V2V Technology for Application,” Aug. 2014** John B. Kenney, “DSRC: Deployment and Beyond,” WINLAB presentation, May 2015.

Supports very low data rates (27 Mbps max,

much lower in practice)

Non safety apps also possible


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DSRC: how it works for safety applications

1. Each transmitter broadcasts Basic Safety Messages

periodically (typically 10Hz)

2. Each receiver assesses collision threats

3. When threats are detected, the system warns the driver or

takes control of car

Safety messages sent on dedicated safety channel

Position, speed, etc.

DSRC is not designed for the exchange of raw sensor data


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Upcoming 3GPP standards for V2X: LTE-V2X (Rel. 14)

*3GPP Study on LTE-based V2X Services. TR 36.885, 3rd Generation Partnership Project (3GPP), July 2016.**M. Rumney et al. LTE and the evolution to 4G wireless: Design and measurement challenges. John Wiley & Sons, 2013

D2D

D2D

Standardization started in Apr. 2015

D2D-based is available both inside and outside the coverage

LTE-V2X = D2D-based + cellular-based

Higher data rates than DSRC (up to 44 Mbps for D2D and 75 Mbps for cellular)

Cellular-based is available only inside the coverage

D2D


DSRC versus LTE-A for V2XFeatures DSRC D2D LTE-V2X Cellular LTE-V2X

Channel width 10 MHz Up to 20 MHz Up to 20 MHz

Frequency Band 5.9 GHz 5.9 GHz 450 MHz-3.8 GHz

Bit Rate 3–27 Mb/s Up to 44 Mb/s Up to 75 Mb/s

Range ~ 100s m ~ 100s m Up to a few km

Spectral efficiency 0.6 bps/Hz 0.6 bps/Hz (typical) 0.6 bps/Hz (typical)

Coverage Ubiquitous Ubiquitous Inside cell only

Mobility support High speed High speed High speed

Comm. fee Free ? ?

Latency x ms x10-x100 ms X10 ms

23*Giuseppe Araniti et al., “LTE for Vehicular Networking: A Survey”, IEEE Commun. Mag., May 2013

Gbps data rates are not supported


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Massive data rates from sensors vs DSRC/4G

New communication solution is needed for connected cars*http://low-powerdesign.com/sleibson/2011/05/01/future-cars-the-word-from-gm-at-idc’s-smart-technology-world-conference/**Cisco, “The Internet of Cars: A Catalyst to Unlock Societal Benefits of Transportation,” Mar. 2013***http://www.sas.com/en_us/insights/articles/big-data/the-internet-of-things-and-connected-cars.html

Automated vehicles can generate up 1 TB per

hour of driving

Current connected vehicles are expected to

drive 1.5GB monthly data in 2017**

4G and DSRC can not supportthese data rates

Handled with a combination of 4G and DSRC


Millimeter wave for connected cars

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5G


High data rates with millimeter wave (mmWave)

26Millimeter wave offers the means to achieve high rates and low latency

Arrays needed for gain and aperture

Low freq. antenna mmWave antenna

Shrinking antenna aperture 802.11n 802.11ac 802.11ad

Band

wid

th

20 MHz 160 MHz

2 GHz

With channel bonding

Large bandwidth at mmWave

Adaptive beam steering


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mmWave for automated cars

MmWave is the only viable approach for high bandwidth connected vehicles*

V2V communication beams

Vehicle driving cloud

directionalbeamforming

blockageV2I communicationbeam

Joint communicationand radar

*Junil Choi, Nuria González-Prelcic, Robert Daniels, Chandra R. Bhat, and Robert W. Heath Jr, “Millimeter Wave Vehicular Communication to Support Massive Sensing”, to appear in IEEE Communications Magazine.

Sensing technologies can be used to help establish mmWave links

Exchanging raw sensor data is possibe

Enables high data rateinfotainment applications


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How will mmWave be realized?

5G is promising for mmWave connected cars

High data rates

Modificationof IEEE

802.11ad

5G mmWave cellular

DedicatedmmWave

V2XRequires special infrastructure

*Federal Communications Commission (FCC), “FCC 15-138,” 2015

Uses cellular infrastructureAccess is highly coordinatedLeverages (coming*) mmWave spectrum

Less efficient accessUse of unlicensed band

Use new dedicated spectrum


© Robert W. Heath Jr. 29

Potential bandwidths and data rates at mmWave

10x to 100x gains in bandwidth going to mmWave

* IEEE 802.11ad is commercially available

Totalspectrum

Typicalbandwidth

Peakrates

IEEE802.11ad*in60GHz

7GHz 2GHz 6Gbps

IEEE802.11ayin60GHz

7GHz 4 GHz 100Gbps

28GHz5G 0.85GHz 200MHz 1.5Gbps39GHz5G 3GHz 400MHz 3GbpsEband5G 10GHz 2GHz 24Gbps


© Robert W. Heath Jr. 30

mmWave enabled infrastructure for transportation

Sensing at the infrastructure

Combination of sensing, learning and

communication

mmWave relay

mmWavesensing-BS

multiband BSMultiband-connectivity

supporting V2X

radarbeam

Vehicles exchanging sensor data


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mmWave spectrum challenges forV2X

Cognitive radio for shared spectrum with satellite or radar**

Regulations not

harmonizedWays to reduce license cost but allow carriers to share

spectrum * New communication technology needed

*A.K.Gupta;J.G.Andrews;R.W.Heath,"OntheFeasibilityofSharingSpectrumLicensesinmmWaveCellularSystems,"in IEEETransactionsonCommunications,toappear**A.K.Gupta,A.Alkhateeb,J.G.Andrews,RobertW.Heath,Jr, “Gains ofRestricted Secondary Licensing inMillimeter WaveCellular Systems,arxiv 2016


Designing a mmWave V2X system

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Overview of the mmWave V2X channel

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Low antenna elevation

Prone to blockage

Tx & Rx moving

Fast changing topology

Large penetration and diffraction loss

Severe blockage

Shrinking antenna aperture

Directionality

V2X channels MmWave channels

MmWaveV2X channelsCombined

challenges from both sides

There are several measurements but still limited


Channel coherence time and directional reception

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Mathematical expression relating coherence time

and beamwidthMathematical expression

relating coherence time and beamwidth

Long term beamformingcan be used

*V. Va, J. Choi, and R. W. Heath Jr. The impact of beamwidth on temporal channel variation in vehicular channels and its implications. Submitted to IEEE Trans VT

Overheads of beam training are much less significant than expected

Beams should be narrow but not too “pointy”

Optimum beamwidthis a tradeoff between

pointing error and Doppler


Efficient beam alignment leveraging position info

35Junil Choi, Vutha Va, Nuria González-Prelcic, Robert Daniels, Chandra R. Bhat, and Robert W. Heath Jr, “Millimeter Wave Vehicular Communication to Support Massive Sensing”, to appear IEEE Commun. Mag., 2016.

DSRC modules or automotive sensors can be used to reduce overhead

Even with poor accuracy of position information the beam alignment overhead is reduced


Multipath fingerprint for V2I beam alignment

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Reflection off building could be used in NLOS

Such paths via static objects can be learned

beforehand

Location Path RxPower AoA AoD

1 #1 -59.81 84 87

#2 -67.66 80 61

… … … …

2 #1 -60.9 82 87

… … … …

Example of multipath fingerprint

Junil Choi et al., “Millimeter Wave Vehicular Communication to Support Massive Automotive Sensing”, to appear in IEEE Commun. Mag., 2016

blocked

Infra collect database of multipath fingerprint(i.e. AoA/AoD) of paths indexed by location

1. Rx request link via DSRC and inform its position

2. RSU responses with list of beam indices for training

3. Perform beam training


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Radar-aided millimeter wave V2XRadar can be used to configure

communication link more efficiently

Radar can be used to design

multiuser beamforming

* N. González-Prelcic, Roi Mendez-Rial, and R. W. Heath Jr., ”Radar aided beamforming in mmWave V2I communications supporting antenna diversity," Proc. of ITA 2016 .

0.5

1

30

210

60

240

90

270

120

300

150

330

180 0

Azimut

Rela

tive P

ath

Gain

Com Signal at 65 GHz

Radar Signal at 76.5 Ghz

0.5

1

30

210

60

240

90

270

120

300

150

330

180 0

Elevation

Com Signal at 65 GHz

Radar Signal at 76.5 Ghz The dominant DoAs for the communication signal also appear at the radar echo in a different band

Algorithms for hybrid precoder& combiner design based on covarianceinformation of the radar signal


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Joint mmWave comm. and radar using IEEE 802.11ad

* P. Kumari, N. González Prelcic, and R. W. Heath, Jr., “ Investigating the IEEE 802.11ad Standard for Millimeter Wave Automotive Radar ,” Proc. of the Vehicular Technology Conference, Boston, USA, September 6-9, 2015

Joint system provides safety capabilities at lower cost

Special structure of preamble enables good ranging performance

Existing WLAN RX algorithms for

radar parameter estimation fine range estimation

achieves the desired accuracy of 0.01m


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Prototyping mmWave forV2X

National InstrumentsPXI chassis interfaces with

custom RF

communication transmitter radar receiver

automotive radar & DSRC

communication receiverautomotive radar &

DSRC

mmWaveV2X and joint mmWave / radar prototype

automotive radar test

mmWave tx/rx

baseband and IF

2x2 MIMOprototype

60 GHz arrays

mmWave 60 GHz phased array testbed


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Research challenges for PHY design

Effect of hardware impairments on mmWave V2X

Fast beam alignment and tracking

MIMO architectures for mmWave V2X: analog or hybrid?

Diversity solutions againstblockage


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What are we doing at UT to address these

challenges?


Transportation and wireless @ UT Austin

WIRELESS COMMUNICATION

SIGNAL PROCESSING

MACHINE LEARNING & BIGDATAPOLICY AND PLANNING

TRAFFIC MODELING

SMART TRANSPORTATION

UT is well positioned to develop wireless networks for transportation systems

Deep industryconnections

Renowed wirelessexpertise

50 years of experienceon transportation

Strong conection with transportationadministrations


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Situation-aware vehicular engineering systems

UT-SAVES

Sensing

Data analytics and learning

Communication

Trafficcontrol center

An initiative in partnernshipwith Toyota IDC, Huawei, & National Instruments*

* Looking for more partners!


Research challenges

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Open research challenges

o Fast beam training /channel estimation strategieso How and where to place the antennas in the carso Channel models are needed for the different scenarios

(rural road, highway, urban area, …)o Leveraging side information for beam trainingo More advanced MIMO communication techniques o Better integration with transportation simulators

Details on existing solutions and research challenges can be found here

General millimeter wave information here


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mmWaveV2X

vehicle-to-x communication using millimeter...

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