Physical Layer Comm Topics in Academia - AFCEA Layer Comm Topics in Academia ... –3G WCMDA (iPhone...
Transcript of Physical Layer Comm Topics in Academia - AFCEA Layer Comm Topics in Academia ... –3G WCMDA (iPhone...
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Physical Layer Comm Topics in Academia David J. Love
Professor
School of Electrical and Computer Engineering
Purdue University
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Mobility Driving Research and
Economy • Mobile data and
applications driving global
technology
• Crosses all age and
economic barriers
• Challenging problems:
– Communications &
Networking
– Applications
– EM compliance
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How Many Transmit Antennas?
• Easier to put multiple transmit antennas at the base station
– 3G WCMDA (iPhone 4 and before) – at most 2
– 4G LTE (iPhone 5, 5s) – 2 or 4 antennas at base station
– 4G LTE-Advanced (iPhone 6) – Up to 8 antennas at base station
– Multiple receive antennas can be easily leveraged
• Harder to put multiple transmit antennas on portable device
– 3G WCMDA – Single antenna
– 4G LTE – Single antenna
– 4G LTE-Advanced – Up to 4 antennas (not commercially available)
How many antennas will systems have in 5G+?
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Massive MIMO • Growing interest in employing a very large number of antennas at
base station
– Many names: Massive MIMO, FD-MIMO, Hyper-MIMO, Large-Scale MIMO
– Deploy 32+ antennas at base station
– Likely will leverage planar arrays at base
station
• Many benefits
– Increased network throughput,
– Power efficiency, robustness, etc…
16x8 planar antenna
array [1] F. Rusek, D. Persson, B. K. Lau, E. G. Larsson, T. L. Marzetta, O. Edfors, and F. Tufvesson, “Scaling up MIMO: opportunities and challenges with very large arrays,” IEEE Signal Processing Magazine, vol. 30, no. 1, pp. 40–60, Jan. 2013
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Why Is There a Benefit?
• Channel matrix will become really “fat”
Spatial Data Pipe
• A “fat” matrix has many good spatial channels to share
among users
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Sample of Research
• Channel information at transmitter is critical
• Advanced sounding schemes to provide CSI tracking
– Very difficult to sound a large number of antennas
– Rely on adaptive techniques
• Advanced quantization techniques to provide channel
feedback
– LTE/LTE-Advanced ideas no longer extend
– Must figure out how to accurately represent a large
dimensional channel matrix
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Millimeter Wave Systems • Many dire predictions for throughput
demand
Solutions:
1) Higher frequency reuse (Cooper’s law)
– Move users physically closer to a high rate link
2) Use non-traditional frequencies
Potential Licensed Bands for 5G
Millimeter wave = 28-100GHz
Nokia white paper: http://networks.nokia.com/file/28771/5g-white-paper
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Possible Architecture
• Networks of small cells (pico) connected by millimeter wave
backhaul
• User could access with conventional (e.g., LTE-like or mmwave)
• Likely Requirements
1) Must be easy to install
2) At least one node per network sees macro (beamforming) or
can collaborate (distributed beamforming)
3) Nodes could use self-organizing topology
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Beam Alignment
• Millimeter wave suffers from many problems
• Propagation – high path loss, oxygen absorption
• Implementation – advanced analog, analog-to-digital
constraints
• Beamforming at Tx and Rx is critical using MANY antennas
• Lower frequency beamforming algorithms don’t work due to
implementation constraints
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• Portable devices are regulated on the amount of user exposure
• Measurement: Specific absorption rate (SAR)
• SAR Units = Watts/Kg
• What if SAR is not satisfied?
– Reduce transmit power
• 5G handsets
– Power constrained
– SAR constrained
User Exposure in Wireless Systems
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SAR Model • SAR is a function of:
– Device orientation
– Polarization
• SAR has historically been difficult to simulate, but there have
been recent advances
• Multiple transmit antenna handsets
Interactions between antennas! • Working with EM researchers to
design signal processing models
for SAR
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• Objective: Low SAR values and high achievable rates
• Transmit signal design in SAR constrained channel
– SAR codes
– Low SAR Space-time codes
– Capacity Analysis
• Beamforming/precoding in SAR constrained channel
– Beamforming/precoding optimization
– SAR matrix estimation
SAR Aware Transmission
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Spectrum Sensing and Cognitive Radio
• Proliferation of wireless technology causing and
increasingly congested and contested spectrum
environment
• Critical points:
– What other RF sources are out there?
– What is the intent of these transmitters?
– What bands are available?
Interference
Available
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Software Radio Work
• Universities increasingly involved
in experimental work using
Universal Software Radio
Peripherals (USRPs)
• DARPA held Spectrum Challenge
– Competitive tournament
– Cooperative tournament
• Excellent training environment for graduate students (and
undergraduates)
Purdue #1 qualified
finalist
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Traditional MIMO Thinking
• Multiple paths interfere constructively and destructively at
different antennas
• Creates multiple effective spatial data paths of varying
reliability
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Distributed MIMO Thinking
• Multiple paths interfere constructively and destructively at
different antennas
• Creates multiple effective spatial data paths of varying
reliability
• What if antennas are distributed?
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Distributed MIMO Thinking
• Multiple paths interfere constructively and destructively at different antennas
• Creates multiple effective spatial data paths of varying reliability
• What if antennas are distributed?
• Distributed nodes would be connected through some form of (very low-rate) network
?
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Quantized Distributed Detection
• Through LAN/backhaul, nodes communicate with fusion center
• Each node connected to detector must be a very low rate link (e.g., per packet control bits within LAN/backhaul)
• Fuse all of the low-rate data streams together
Received signal compression
Detector
Data
Lower-rate data
(e.g., 10Mbps)
High-rate data
(e.g., 1Gbps)