Vehicular mmWave Communication: Opportunities and...
Transcript of Vehicular mmWave Communication: Opportunities and...
© Robert W. Heath Jr. (2015)
Vehicular mmWave Communication: Opportunities and ChallengesProfessor 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 US Department of Transportation, the Texas Department of Transportation, Toyota IDC, and National Instruments
© Robert W. Heath Jr. (2015)
UT is a collaboration hub for wireless + transportation
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© Robert W. Heath Jr. (2015)
Transportation and wireless @ UT Austin
u WNCG brings renowned wireless expertise & deep industry connectionsu CTR has more than 50 years of transportation research experience
WIRELESS COMMUNICATION
SIGNAL PROCESSING
MACHINE LEARNING & BIGDATAPOLICY AND PLANNING
TRAFFIC MODELING
SMART TRANSPORTATION
UT is well positioned to develop wireless networks for transportation systems
© Robert W. Heath Jr. (2015)
A new transportation initiative at UT Austin
u SAVES: Center for Situation-Aware Vehicular Engineering Systemsu Focuses on wireless, networking, and sensing challenges in vehicular systems u Brings together stakeholders in different aspects of the automotive market
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SAVES is built around TOYOTA as a founding member, lookging for partners
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Why vehicular communicationsat mmWave?
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5G will enable key changes in transportation
u Automated cars needs sensing capabilitiesª Increased number of sensors in a vehicleª Vehicular communications to share sensing data and improve sensing capability
6*5G-PPP White Paper on Automotive Vertical Sector, October 2015, https://5g-ppp.eu/white-papers/
New challenges for the underlying communication system
AUTONOMOUS DRIVING
TRAFFICEFFICIENCY
ROADSAFETY
AUTOMATED CAR
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DSRC: current technology for vehicular communications
u Forward collision warning, do not pass warning, blind intersection warning, etc.u Non-safety apps also possible – improve congestion, weather, toll collection u Based on IEEE 802.11p, IEEE 1609.x, SAE standardsu Supports very low data rates (27 Mbps max, much lower in practice)
7*NHTSA, “Vehicle-to-Vehicle Communications: Readiness of V2V Technology for Application,” Aug. 2014**John B. Kenney, “DSRC: Deployment and Beyond,” WINLAB presentation, May 2015.
DSRC is expected to be mandated for all vehicles in US by NHTSA by 2017
© Robert W. Heath Jr. (2015)
Massive data rates from sensors
u Connected vehicle is expected to drive 1.5GB monthly mobile data in 2017ª May be handled with a combination of conventional cellular and DSRC
u Autonomous vehicle can generate up to 1 TB of data in a single tripª 4G and DSRC can not support these data rates
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*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
Each sensor generates data
Lots of sensors in a vehicle
Massive amount of data per vehicle
MmWave is the only viable approach for high bandwidth connected vehicles
Automotive radar
Lidar
Videocameras
Infraredcameras
Inertial motionsensor
GPS
Ultrasonicsensor
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Millimeter wave spectrum for 5G
* T. Rappaport et al., “Millimeter wave mobile communications for 5G cellular: It will work!” IEEE Access, 2013.** W. Roh et al., "Millimeter-wave beamforming as an enabling technology for 5G cellular communications: theoretical feasibility and prototype results,“, IEEE Commun. Mag.,, 2014*** A. Osseiran et al.,"Scenarios for 5G mobile and wireless communications: the vision of the METIS project," iIEEE Commun. Mag., May 2014
60 GHz7 GHz
Unlicensed6 GHz 100 GHz
E-band10 GHz total
28 GHz1.3 GHz
39 GHz1.4 GHz
37/42 GHz2.1 GHz
20 GHz x100 GHz<1 GHz
MmWave
2.4 GHz100 MHz
900 MHz2.6 MHz
5.2 GHz555 MHz
CmWave
More spectrum, in bands not previously used for cellular
Even more spectrum
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Implications of using mmWave in automotive
Cloud driven autonomous driving
Joint automotive radar and communication is possible
Increased sensing capability in the car
Sensing technologies can be used to help establishing communications
© Robert W. Heath Jr. (2015)
Key features for mmWave vehicular communications
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MmWave vehicular communications
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Vehicle driving cloud
mmWavebase station
MmWave vehicular communications introduce new challenges
V2V communication beams
V2I communication beam
blockage
directionalbeamforming
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Implications of directional beamforming in V2X
Multiuser operation strategies
Optimum beamwidth has to be selected
Beam training overhead is critical due to high mobility
New channel models for V2V and V2I are needed
© Robert W. Heath Jr. (2015)
Selecting the optimum beamwidth
u Mathematical expression relating coherence time and beamwidthª Accounts for beam pointing angular difference as oppose to classical models
u Optimum beamwidth is a tradeoff between pointing error and Doppler
14*Vutha Va, and Robert W. Heath, Jr, "Basic Relationship between Channel Coherence Time and Beamwidth in Vehicular Channels,'' IEEE Vehicular Technology Conference (VTC 2015-Fall), 2015.
Beams should be narrow but not too “pointy”
© Robert W. Heath Jr. (2015)
Defining the coherence time for beam alignment
u The preferred channel direction changes much more slowly than the instantaneous fading envelope
u Beam coherence time relates to changes in the mean directionu Long term beamforming can be used
15Overheads of beam training are much less significant than expected
*V. Va, J. Choi, and R. W. Heath Jr. The impact of beamwidth on temporal channel variation in vehicular channels and its implications. arXiv preprint.
Received power
Four channeldirections
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Using position information to reduce beam alignment overhead in mmWave V2X
u Each vehicle decides candidate beams from other vehicles’ position and size info
16Junil Choi, Nuria Gonzáalez-Prelcic, Robert Daniels, Chandra R. Bhat, and Robert W. Heath Jr, “Millimeter Wave Vehicular Communication to Support Massive Sensing”, to be submitted December 2015
DSRC modules or automotive sensors can be used to reduce overhead
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Adding radar to the infrastructure for multiuser operation
u A BS with a radar can capture information of the scattering environmentu Used to design multiuser beamforming, support remote car traffic control
mmWave BS
radar
Sensing at the infrastructure can help in establishing the communication links
popsci.com
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Channel models for mmWave vehicular
u Channel classifications considered at 5.9GHz is unlikely to scaleª More sensitive to antenna orientationª More sensitive to traffic density (higher blockage probability)ª Effect of directive transmission is unknown
u Few measurements available
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Typical antenna height: 1.5 m
* T. S. Rappapport, R. W. Heath Jr., R. C. Daniels, and J. N. Murdock, “Millimeter Wave Wireless Communications,” Pearson Prentice-Hall, 2014** S. Takahashi, et al., “Distance dependence of path loss for millimeter wave inter-vehicle communications,” in VTC 2003-Fall, Oct. 2003, ** W. Schafer, “Channel modelling of short-range radio links at 60 GHz for mobile intervehicle communication,” in IEEE 41st VTC, May 1991.
© Robert W. Heath Jr. (2015)
Defining new channel models
u New models must account for mmWave propagation characteristicsu Channels are sparse in the angular domain, a few paths existu Blockage has to be introduced in the channel model
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Modified Sen-Matolak model*
Persistence process for each cluster modellating blockage
Delay of cluster c and ray p
Doppler shift for each multipath component
Steering vectors
θ
* V. Va, N. Gonzalez-Prelcic and R. W. Heath Jr., “A cluster-based approach for vehicular channel models at millimeter wave”, in preparation.
Clustered in space:intra-cluster structure
AoA anglespread
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Implications of blockage in V2X
Multibeam transmission to overcome blockage
Antenna diversity to overcome blockage
Automotive sensors can be used to predict blockage
Blockage can help to mitigate interference
© Robert W. Heath Jr. (2015)
Antenna placement and blockage
u A classic problem even at low frequencies*ª Shadowing becomes blockage for mmWaveª Directional transmission adds another challenge
u V2V require 360 degree coverage but antennas can not penetrate carª Front bumper location causes blockage at the back sideª Rooftop location causes blockage at the front side due to roof curvatureª Sensitive to antenna orientation
21* C. Mecklenbrauker, et al., “Vehicular channel characterization and its implications for wireless system design and performance,” Proc. of the IEEE, July 2011.
MmWave propagation add new challenges to antenna placement
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Antenna diversity to overcome blockage in V2I
u A BS with a radar is assumed at the infrastructure sideª Antennas are assumed to be placed at the virtual scattering points in the carª Radar info is used to design a multi-beam pattern to track several antennas
u High mobility is considered and the positions of the antennas are predicted
22* N. González-Prelcic, R. Méndez-Rial and R. W. Heath Jr., “Radar-aided multibeam directional beamforming for mmWave vehicle to infrastructure communications”, in preparation.
Sensing at the infrastructure can help to manage blockage
© Robert W. Heath Jr. (2015)
Predicting blockage from out-of band sensing
u A BS equipped with a radar is assumedu Radar and communication operate at different mmWave bandsu Radar can detect potential obstacles and their associated mobilityu Machine learning can classify particular radar responses as blockages
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Sensing & learning are symbiotic technologiesJunil Choi, Nuria Gonzáalez-Prelcic, Robert Daniels, Chandra R. Bhat, and Robert W. Heath Jr, “Millimeter Wave Vehicular Communication to Support Massive Sensing”, to be submitted December 2015
© Robert W. Heath Jr. (2015)
Joint vehicular communicationand radar
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© Robert W. Heath Jr. (2015)
Combining communication and radar at mmWave
u MmWave radars widely used in automotive safety applicationsª Expensive: automotive radar modules cost around $1,500ª Easy to get spoofed compared to communication
u Why not share common equipment with communication?ª Combines the objectives of radar and communication
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Direction of Cruise
Communication Signal
Emergency Van
Radar Multi-beam
Emergency Event
Shared hardware reduces cost/size and makes efficient spectrum usage
© Robert W. Heath Jr. (2015)
MmWave communication-radar challenges
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LFM# : Linear frequency modulated waveform, which is a radar waveformDSSS# : Direct spread spectrum, which is a communication waveform*L. Han and K.Wu,``Joint wireless communication and radar sensing systems-state of the art and future aspects,'' IET Microwaves, Antennas & Propagation, vol. 7, no. 11, pp. 876-885, 2013.
Communication-radar (RadCom) Application Scenario
u Optimization of sensing and data communication ª LFM # waveform provides low data rate ª DSSS# exhibits poor radar performance ª No single waveform yet available ª Interference issue
u Assumption of full-duplexª Separate transmit and receive antennaª Use directional antennas
Many open problems to design joint communication and radar systems
© Robert W. Heath Jr. (2015)
Joint automotive radar and communications based on 802.11ad
u IEEE 802.11ad mmWave waveform works well for radarª Special structure of preamble enables good ranging performanceª Leverages existing WLAN receiver algorithms for radar parameter estimation
u Target vehicle information from 11ad radar can be directly used for communication
27*P. Kumari, N. González Prelcic and R. W. Heath, Jr, ̀ `Investigating the IEEE 802.11ad Standard for Millimeter Wave Automotive Radar,'' IEEE VTC-Fall, 2015.
Joint system provides safety capabilities at lower cost
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Prototyping and measurements
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UHF radar and mmWave communication
29Platform can be used to obtain out-of-band information for communication at mmWave
Transmit 802.11 OFDM waveform (DSRC) through single forward-directional antenna at 5.9 GHz
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DSP
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u UT custom DSP separates simultaneous TX/RX operationsu It provides meter-level range of largest target
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UT mmWave communication and radar prototype
Custom RF
Steerable, Multi-level Scanning
LRRSRR MRR
TX Antenna RX Antenna Custom RFProcessing in
NI FPGA module
FPGA for real-time processing
NI Signal Generator
(TX)
Processing in NI FPGA module
NI Digitizer(RX)
National InstrumentsPXI Chassis Interfaces with
custom RF
RX AntennaCustom RFProcessing in
NI FPGA module
NI Digitizer(RX)
Communication transmitter and radar receiver Communication receiver
Platform allows V2V communication link prototyping, new radar waveform
development, and joint communication and radar waveform testing
© Robert W. Heath Jr. (2015)
Multi-sensor measurement campaign
u Joint measurements using the WiFi-based radar, off-the-shelf mmWave radar, GPS, and DSRC
31Collect sensing data in different bands and asses limitations of different technologies
L-COM 23-dBi HG4958-23P Patch- 2 receive (RX)- 1 transmit (TX)
TXRX RX
Delphi ESR 2.5 77 GHz RADAR
National InstrumentsUSRP-RIO w/ 5.8
GHzRF, 802.11p PHY+MAC
National InstrumentsPXI Chassis Interfaces with USRP-RIO & ESR
Cohda Wireless DSRC unit
© Robert W. Heath Jr. (2015)
Conclusions
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Conclusions
Opportunities• Millimeter wave is ripe for V2X applications• Natural synergies with automotive radar, circuit design, etc.• Only feasible way to enable connected + autonomous
Challenges• Unlicensed band, co-exist with radar, new spectrum?• Complete redesign of physical layer required, mobility• Support of full duplex for more complicated waveforms• Antenna mounting, packaging, cabling