Post on 02-May-2020
Vehicular Millimeter Wave Communications: Opportunities and Challenges
Professor Robert W. Heath Jr. Wireless Networking and Communications Group Department of Electrical and Computer Engineering The University of Texas at Austin
www.profheath.org
Introduction
u Dedicated Short Range Communication is a mature technology ª Based on 15 year old WiFi technology ª Products already available on market
• Arada LocoMate, Redpine Signals, etc.
ª Supports very low data rates (27 Mbps max)
u Connected vehicles will need gigabit per second (Gbps) data rates ª Expanding number of sensors: radar, LIDAR, camera, etc. ª Can not achieve Gpbs in the small 10 MHz channels in 5.9GHz band
u How can higher data rates be achieved?
2 Arada LocoMate Mini* * http://www.aradasystems.com/
Using the millimeter wave (mmWave) band!!
Why millimeter wave?
3
3 GHz 30 GHz
30 GHz 300 GHz
DSRC (75 MHz) 28 GHz
7 GHz @ 60 GHz
38-49 GHz 70-90 GHz
u Huge amount of spectrum (possibly repurposed) at mmWave bands u Technology advances make mmWave possible in low cost consumer devices
Note: log scale
* United States radio spectrum frequency allocation chart as of 2011
Automotive Radar (76-81 GHz)
Automotive Radar 22-29 GHz
MmWave for WLAN/WPAN
u Standards developed @ unlicensed 60 GHz band ª WirelessHD: Targeting HD video streaming ª IEEE 802.11ad: Targeting Gbps WLAN
u Compliant products already available ª Dell Alienware laptops, Epson projectors, etc. ª 11ad Chipset available from Wilocity, Tensorcom, Nitero
u Extension of 802.11ad is underway (>20 Gbps)*
4
Standard Bandwidth Rates Approval Date
WirelessHD 2.16 GHz 3.807 Gbps Jan. 2008
IEEE 802.11ad 2.16 GHz 6.76 Gbps Dec. 2012
Wilocity’s chipset***
Tensorcom’s chipset*** * http://www.ieee802.org/11/Reports/ng60_update.htm ** http://www.wirelesshd.org/consumers/product-listing/ *** http://www.dailytech.com/
Epson projector**
Dell Laptop**
MmWave is coming for 5G cellular
u Repurpose existing mmWave spectrum for mobile cellular applications ª MmWave used to provide high throughput in small geographic areas
u MmWave cellular networks differ from < 3GHz networks ª Directional beamforming for signal power and reduced interference ª Sensitivity to blockages, indoor coverage more challenging
5
Buildings Femtocell
Conventional BS
mmWave D2D
Indoor user
mmWave BS
Control signals
Multiple-BS access for fewer handovers and high rate
Wireless backhaul
Data center
LOS links
Non-line-of-sight (NLOS) link
*T. S. Rappaport, R.W. Heath, Jr. , J. N. Murdock, R. C. Daniels, Millimeter Wave Wireless Communications, Pearson, 2014 **T. Bai, A. Alkhateeb, and R. W. Heath Jr, “Coverage and Capacity of Millimeter-Wave Cellular Networks,” IEEE Coomm. Mag, vol.52, no.9, Sept. 2014 ***T. Bai and R.W. Heath Jr, “Coverage and Rate Analysis for Millimeter-Wave Cellular Networks,” IEEE Trans. Wireless Comm., vol.14, no.2, Feb. 2015
MmWave for automotive radar
u Long range radar (LRR) is used for automatic cruise control (ACC) u Medium range radar (MRR) supports CTA, LCA, stop&go and BSD u Short range radar (SRR) is used for parking aid and precrash applications
6
*J. Hasch, E. Topak, R. Schnabel, T. Zwick, R. Weigel, and C. Waldschmidt,“Millimeter-wave technology for automotive radar sensors in the 77 GHz frequency band,” IEEE Transactions on Microwave Theory and Techniques, vol. 60, no. 3, pp. 845–860, 2012. **R. Mende and H. Rohling, “New automotive applications for smart radar systems,” in Proc. German Radar Symp., Bonn, Germany, Sep. 3–5, 2002, pp. 35–40. ***R. Lachner, “Development Status of Next generation Automotive Radar in EU”, ITS Forum 2009, Tokyo, 2009, [Online]. Available. http://www.itsforum.gr.jp/Public/J3Schedule/ P22/ lachner090226.pdf
ACC !
Stop&Go!
Cross Traffic Alert !(CTA)!
Pre-crash!
Pre-crash !
Lane Change Assistance !
(LCA) !
Blind Spot !Detection !
(BSD) !
79 GHz!MRR !
77 GHz LRR !
79 GHz!SRR !
Type LRR MRR SRR
Frequency band (GHz)
76-77
77-81
77-81
Bandwidth (GHz) 0.6 0.6 4
Range (m) 10-25
0 1-100
0.15-30
Distance accuracy 0.1 0.1 0.02
Potential of mmWave V2V
u Enhanced local sensing capability in connected cars ª Share high rate sensor data: radar, LIDAR, video, IR video, other sensors ª Data fusion from other cars can enlarge the sensing range
u Enable the transition from driver assisted to autonomous vehicles ª Develop a better understanding of the local environment ª Seamlessly scales with more vehicles
7 * NHTSA, “Vehicle safety communications applications (VSC-A) final report,” Sep. 2011
Example of data fusion (Measurement)*
Sharing GPS observation improves accuracy
Potential of mmWave V2I
u Cloud processing of sensor data from vehicles ª Centralized driver assistance and traffic management ª Precise traffic monitoring and congestion control ª Improved safety through more accurate window into the roadway
u Infotainment services ª Video, multimedia, and data for passengers
8
Vehicular mmWave challenges: Channel modeling u V2V channels
ª Low antenna height ª Both TX and RX are moving
u MmWave channel characteristics* ª High path loss ª High penetration loss and poor diffraction capability
u Channel classifications considered at 5.9GHz is unlikely to scale ª More sensitive to antenna orientation ª More sensitive to traffic density (higher blockage probability) ª Effect of directive transmission is unknown
u Few measurements available
9
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.
Vehicular mmWave challenges: Antenna placement
u A classic problem even at low frequencies* ª Shadowing becomes blockage for mmWave ª Directional transmission adds another challenge
u V2V require 360 degree coverage but antennas can not penetrate car ª Front bumper location causes blockage at the back side ª Rooftop location causes blockage at the front side due to roof curvature ª Sensitive to antenna orientation
10 * C. Mecklenbrauker, et al., “Vehicular channel characterization and its implications for wireless system design and performance,” Proceedings of the IEEE, vol. 99, no. 7, pp. 1189-1212, July 2011.
Vehicular mmWave challenges: Beam alignment
u Beamforming with narrow beams required to compensate high path loss ª Narrow beam needed for reasonable coverage range ª Narrow beam needed to suppress Doppler spread
u Existing methods are designed for low mobility environment ª Beam sweeping based on hierarchical beam codebook
u Alignment overhead within coherence time: gain vs. overhead tradeoff
11
Hierarchical Beam Codebook Beam Sweeping Example Sector level training Beam level training
* J. Wang, et al., “Beam codebook based beamforming protocol for multi-Gbps millimeter-wave WPAN systems,” JSAC, vol. 27, no. 8, pp. 1390-1399, Oct. 2009. * K. Hosoya, et al., “Multiple sector id capture (MIDC): A novel beamforming technique for 60-GHz band multi-Gbps WLAN/PAN systems,” IEEE Trans. On Antennas and Propagation, vol. 63, no. 1, pp. 81-96, Jan. 2015.
Preliminary result: Coherence time and beamwidth
u Mathematical expression relating coherence time and beamwidth ª Accounts for beam pointing angular difference as oppose to classical models ª Dependent on angle between beam direction and direction of travel ª There exists optimal beamwidth maximizing the coherence time
12 *Vutha Va, and Robert W. Heath, Jr, "Basic Relationship between Channel Coherence Time and Beamwidth in Vehicular Channels,'' Submitted to IEEE Vehicular Technology Conference (VTC 2015-Fall), 2015.
Combining communication and radar at mmWave
u MmWave is already used for radar, why not share with communication? ª Combines the objectives of radar and communication ª Shared hardware reduces cost, size, and spectrum usage
13
state_car0(t) radar_car1(t- Δ01 ) comm_car1(t- Δ0c ) comm_car2(t- Δ02)
comm_Emergency(t- Δ0e) comm_Pedestrian(t- Δ0p)
state_car1(t) radar_car2(t- Δ12) comm_car2(t- Δ1c)
comm_EmergencyVan(t- Δ1e) radar_Pedestrian(t- Δ1p)
comm_Emergency(t- Δ2e) state_Car2(t)
Car-0 Data Matrix
Car-1 Data Matrix
Car-2 Data Matrix
Direction of Cruise
Communication Signal
Emergency Van
Radar Multi-beam
Emergency Event
A communication-radar framework
u Common optimized waveform for radar and communication u Develop software-defined radio prototype w/ National Instruments
14 *Preeti Kumari, Nuria González Prelcic and Robert W. Heath, Jr, ``Investigating the IEEE 802.11ad Standard for Millimeter Wave Automotive Radar,'' Submitted to IEEE Vehicular Technology Conference (VTC 2015-Fall), 2015.
MmWave USRP (TX)
Steerable, Multi-level Scanning
LRR SRR MRR
MIMO cable
Ethernet
Signal Energy Source TX Antenna RX Antenna MmWave
(RX) Recording
System Laptop
STF CEF BLK … BLK Header BLK Optional Subfields
Radar Pulse Data Communication
Channel Estimation for Communication
MmWave Prototype Testbed
Common Waveform: SCPHY Frame Structure of IEEE 802.11ad
MmWave communication-radar challenges
15
LFM# : Linear frequency modulated waveform, which is a radar waveform DSSS# : 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-duplex ª Separate transmit and receive antenna ª Use of directional antennas
Preliminary result: Range and velocity estimation
u IEEE 802.11ad waveform works well for radar ª Leverages existing WLAN receiver algorithms for parameter estimation ª Special structure of preamble enables improved radar performance
16
Delay Index
Am
plitu
de
*Preeti Kumari, Nuria González Prelcic and Robert W. Heath, Jr, ``Investigating the IEEE 802.11ad Standard for Millimeter Wave Automotive Radar,'' Submitted to IEEE Vehicular Technology Conference (VTC 2015-Fall), 2015.
Composite Ambiguity Function
Car-A
wt
wr s
Mt
Mr
TX Antenna Array
RX Antenna Array
Direction of Cruise
Point Target
Transmit Beamforming
Receive Combining
Car-B
Combining Long Range Radar and V2V MmWave Communication
-Ga128 -Gb128 Gb128 -Ga128 -Gb128 Ga128 -Ga128 -Gb128 -Gb128
Gu512 Gv512 Gv128
a256 b256
Ga128 Ga128 -Ga128
16 X Ga128 + -Ga128
Preamble Sequences
Conclusions
u MmWave brings new benefits to V2V and V2I ª Higher data rates using existing mmWave radar waveforms ª Exchange of sensor/camera/radar data among connected vehicles ª Sensor fusion between communication and radar for collision avoidance
u Many challenges remain to make mmWave a reality
17
D-STOP at UT is making fundamental progress in mmWave for V2X