vehicle-to-x communication using millimeter waves (just...

Slides © Robert W. Heath Jr. (2016)

Vehicle-to-X communication using millimeter waves (just in time for 5G)

Professor 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


Automated vehicles and 5G

2


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

CONNECTEDCAR

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

Higherautomation

levels

TRAFFICEFFICIENCY

SELFDRIVING

DRIVERASSIST


5

Myths surrounding automated vehicles

Automated vehicles can be fully autonomous, no communication is required

MYTH 1

Infrastructure has no value for automated vehicles

MYTH 2


Expand the sensing range of the vehicle

Allows interactions between vehicles with

different automation levels

More informed safety decisions

Benefits of communication

Higher levels of traffic coordination like platooning


10

Benefits of infrastructureCan 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


8

Where is thecommunicationtheory and signalprocessing research?

What are the datarate requirements for

sensors?

Key questions

What are the capabilities of current automotivecommunication solutions?


State-of-the-art invehicular sensing

9


10

Current technologies for vehicular sensing

Powerful sensing technologies with limited range in traffic conditions

Sensor Range(ideal)

Radar 200m

Camera 30m

LIDAR 100m

Sensor Range(traffic)

Radar 3-5m

Camera 3-5m

LIDAR 3-5m


Sensor applications and data rates

11

Automotive sensors generate a huge amount of data

Purpose Drawback DatarateRadar Targetdetection,

velocityestimationHardtodistinguishtargets

Lessthan1Mbps

Camera Virtualmirrorsfordrivers

Needcomputervisiontechniques

100-700Mbpsforrawimages,10-90Mbpsforcompressedimages

LIDAR Targetdetectionandrecognition,velocityestimation

Highcost 10-100Mbps


12

State-of-the-art inconnected cars


Connectivity for automated vehicles

13

Connectivitygives access to a

richer set of sensor data

Connectivity solves key challenges of

automated driving in congested urban areas

Connectivitymotivates 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

!

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

14

DSRC is not designed for the exchange of high rate sensor data

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

*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


15

4G cellular forV2X

*3GPP.LTEDevicetoDeviceProximity Services;UserEquipment (UE)RadioTransmission andReception. TR36.877,3rdGeneration Partnership Project (3GPP), 2015.**M.Rumney etal.LTEandtheevolution to4Gwireless:Designandmeasurementchallenges.JohnWiley&Sons,2013

D2D

D2D

V2V through D2D mode in LTE-A

BS helps vehicles discover other nearby vehicles

Cars communicate directlyor through infrastructure

Higher data rates than DSRC (up to 1Gbps)

Practical rates limited to several Mbps by inaccurate CSI

D2D


DSRC versus LTE-A forV2X

Features DSRC LTE-A

Channel width 10 MHz Up to 100 MHz

Frequency Band 5.86–5.92 GHz 450 MHz–4.99 GHz

Bit Rate 3–27 Mb/s 100’s of Mb/s to 1 Gb/s

Range Up to 1 km Up to 30 km

Capacity Medium Very high

Coverage Intermittent Ubiquitous

Mobility support Medium High

Market penetration Low Potentially high

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

Gbps data rates are not supported

LTE-A is interesting because of its wide expected coverage*


Massive data rates from sensors vs DSRC/4G

17

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 and 5G forconnected cars

18

5G


Millimeter wave for automated cars

19

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

V2V communication beams

Vehicle driving cloud

directionalbeamforming

blockageV2I communicationbeam

Joint communicationand radar is possible

*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


Candidate millimeter wave spectrum for V2X

20

20 GHz

* United States radio spectrum frequency allocation chart as of January 2016

60GHzunlicensed 100 GHz

UnderFCC’sconsiderationExistingbands

Automotive radar Automotive radar5Glicensed

60 GHz band: currently used indoor such as WiGig

63-64 GHz allocated for V2X in Europe

63-64 GHz allocatedforV2X in Europe

5G mmWave: 28 and 39 GHz (USA) and 10 other bands

Automotive radar: 24 GHz UWB, 76 GHz, and 79 GHz bands


© Robert W. Heath Jr. 21

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


22

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


23

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

24


Overview of mmWave V2X channel

25

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

26

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

27Junil 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

28

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


29

Multiuser hybrid precoding: application to V2I

29*A. Alkhateeb, G. Leus, and R. W. Heath Jr, “Limited feedback hybrid precoding for multi-user millimeter wave systems,” IEEE Transactions on Wireless Communications, vol.14, no.11, pp.6481-6494, Nov. 2015

Multi-user interference management

SU analog beamforming design for max. desired

power

Two-stage multi-user hybrid precoding algorithm

L=3 paths, effective channels are quantized with BBB bits

Analog combining in the cars

Hybrid precoding at the infrastructure

Performance with quantized effective channels


30

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


31

Translating spatial correlation information

MmWave has higher spatial resolution (antennas)

and temporal resolution (bandwidth)

SIMO operating at two bands

* A. Ali, N. González-Prelcic and R. W. Heath Jr., ” Estimating Millimeter Wave Channels Using Out-of-Band Measurements,” Proc. of ITA 2016

hH

hL

NH > NL

Construct an estimate of the high frequency

spatial correlation matrix

⇥s1 s2 . . . sNtr

⇤(1)

⇥y1 y2 . . . yNtr

⇤=

2

6664

h1h2...

hNr

3

7775⇥s1 s2 . . . sNtr

⇤+ noise (2)

RL = E [hLh⇤L] (3)

ˆRH = f(RL) (4)

1

Compute low frequency spatial

correlation matrix

⇥s1 s2 . . . sNtr

⇤(1)

⇥y1 y2 . . . yNtr

⇤=

2

6664

h1h2...

hNr

3

7775⇥s1 s2 . . . sNtr

⇤+ noise (2)

RH = E [hHh⇤H] (3)

RL = E [hLh⇤L] (4)

1

True angle spread of high frequency

Correlationdistance


32

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


33

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

target emulator

baseband and IF

2x2 MIMOprototype

60 GHz arrays

mmWave 60 GHz phased array testbed


34

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


Conclusion

35


© Robert W. Heath Jr. 36

Vision of cellular infrastructure supporting transportation

Sensing at the infrastructure

Combination of sensing, learning and

communication

mmWave relay

mmWavesensing-BS

mutiband BSMultiband-connectivity

supportingV2X

radarbeam

Vehicles exchangingsensor data

vehicle-to-x communication using millimeter waves (just...

Documents