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Millimeter-Wave MIMO: Basic Theory, Architectures, and Technology Development
Akbar M. SayeedWireless Communications and Sensing Laboratory
Electrical and Computer Engineering
University of Wisconsin-Madison
http://dune.ece.wisc.edu
Huawei University DaysAugust 4-5, 2016
Chicago, IL
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Supported by the NSF and the Wisconsin Alumni Research Foundation
• mmW is mature!
• How we we estimate the channel if we don’t even know the channel characteristics?
• Non-coherent vs coherent (with training)?
• Physically accurate channel modeling vs mathematically tractable statistical models
• Dumb antennas or remote radio heads!
Some Recent Comments
AMS mmW MIMO 1
KL, VS, AS, ‘03
iid fading
reality
2
Explosive Growth in Wireless Traffic
AMS mmW MIMO 2
Current Industry Approach: Small Cells & Het Nets
Denser spatial reuse of spectrum
New Spectrum: mmW and cmW
3kHz
300kHz
3MHz
30MHz
3GHz
30GHz
300MHz
300kHz
3MHz
30MHz
300MHz
3GHz
30GHz
300GHz
mmW: 30-300 GHz
Short range mmW: 60 GHz; Longer range mmW: 30-40GHz, 70/80/90GHz
Current cellular wireless: 300MHz - 5GHz
AMS mmW MIMO 3
cmW: 6-30GHz
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• A key component of 5G
– Multi-Gigabits/s speeds
– millisecond latency
• Key Gigabit use cases
– Wireless backhaul
– Wireless fiber-to-home (last mile)
– Small cell access
• New FCC mmW allocations
– Licensed (3.85 GHz): 28, 37, 39 GHz
– Unlicensed (7 GHZ): 64-71 GHz
• New NSF-led Advanced Wireless Initiative– mmW Research Coordination Network
AMS mmW MIMO 4
Exciting Times for mmW Research
mmW Wireless: 30-300 GHz
A unique opportunity for addressing the wireless traffic growth
– Large bandwidths (GHz)
– Short wavelength (1-100mm) compact high-dimensional antenna arrays
15dBi @ 3GHz 35dBi @ 30GHz
Highly directive narrow beams
(low interference/higher security)
6” x 6” antenna @ 80GHz: 6400-element antenna array
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Beamwidth:
4 deg @ 30 GHz35 deg @ 3 GHz
Large antenna gain:
4
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mmW MIMO Potential: Dense Beamspace Multiplexing
100X antenna gain
100X spec.eff.gain
6” x 6” access point (AP) antenna array: 6000 elements @80GHz vs. 9 vs. elements @3GHz
Potential power & spectral efficiency gains over 4G
>100X increase in capacity due to beamspace multiplexing
>10X increase in capacity due to extra bandwidth
(1GHz vs 100MHz)
Small Cell Access Comparison: 4G LTE vs 5G mmW
(AS & JB GCOM’13; JB & AS SPAWC ’14)
Slice
Array
Multi User MIMO
w/ Beamforming
K users/
sector
Nb beams/sector
Small Cell
mmWave Backhaul
>1000X increase in overall small cell throughput
Idealized upper bound (non-interfering users)
Key Opportunities and Challenges
• Hardware complexity: spatial analog-digital interface
• Computational complexity: high-dimensional DSP
Electronic multi-beam steering & MIMO data multiplexing
Conceptual Framework: Beamspace MIMO
Key Challenges:
Key Operational Functionality:
AMS mmW MIMO(AS & NB Allerton’10; JB, NB, & AS TAPS ‘13)
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5
Beamspace MIMO
Antenna space multiplexing
Beamspacemultiplexing
Discrete Fourier Transform (DFT)
n dimensional signal space
n-element array( spacing)
n orthogonal beams
Related: comm. modes in optics (Gabor ‘61, Miller ‘00, Friberg ‘07)
n spatial channels
(AS TSP ’02; AS & NB Allerton ’10; JB, NB & AS TAPS ‘13)
AMS mmW MIMO 8
Multiplexing data into multiple highly-directional (high-gain) beams
n-Element (Phased) Antenna Array
Spatial angle
TX: steering vectoror
RX: response vector
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Spatial frequency:
n-dimensional spatial sinusoid
9
6
Orthogonal Spatial Beams
n orthogonal spatial beams
DFT spatial modulation matrix:
n = 40
Spatial resolution/beamwidth:
(DFT)
Unitary
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(n-dimensional orthogonal basis)
10
Antenna vs Beamspace MIMO Representation
AMS mmW MIMO 11(AS TSP ’02)
(DFT)(DFT)
Multipath Channel
(correlated)
(decorrelated)
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AMS mmW MIMO 12
Multipath Channel
TX RX
Antenna Domain Beamspace
Beamspace channel coefficients
Dirichlet sinc
DFT
Beamwidth:
mmW MIMO Channel: Beamspace Sparsity
Point-to-point LoS Link
Point-to-multipointmultiuser link
Communication occurs in a low-dimensional (p) subspaceof the high-dimensional (n) spatial signal space
How to optimally access the p active beams with the lowest – O(p) - transceiver complexity?
(DFT)(DFT)
TX Beam Dir.
RX
Bea
m D
ir.
AMS mmW MIMO
mmW propagation X-tics• Directional, quasi-optical• Predominantly line-of-sight• Single-bounce multipath• Beamspace sparsity
13(AS & NB Allerton ’10; Pi & Khan ‘11; Rappaport et. al, ‘13)
8
Continuous Aperture Phased (CAP) MIMO
Lens computes analog spatial DFT
Data multiplexing through
O(p)active beams
Scalable performance-complexity optimization
p digital data streams
O(p) transceivercomplexity Beam Selection
O(p) << nactive beams
AMS mmW MIMO
Hybrid Analog-Digital Beamspace MIMO Transceiver Architecture
(AS & NB Allerton ‘10, APS ‘11; JB, NB & AS TAPS ‘13) 14
Focal surface feed antennas:direct access to beamspace
Lens Array for Analog Multi-Beamforming
CAP-MIMO vs Conventional MIMO: Spatial Analog-Digital Interface
CAP MIMO:Analog Multi-Beamforming
Conventional MIMO:Digital Beamforming
Beam Selectionp << n
active beams
O(p) transceiver complexityO(n) transceiver complexity
n: # of conventional MIMO array elements (1000-10,000)
p: # spatial channels/data streams (10-1000)AMS mmW MIMO 15
p data streams p data
streams
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CAP-MIMO vs Phased-Array-Based Architecture
Multi-beam forming mechanismO(p) transceiver
complexity
Lens+
Beamspace Array+
mmW Beam Selector Network
Phase ShifterNetwork (np)
+Combiner Network
CAP-MIMO:
Phased-Array-Based:n phase shifters per data stream
AMS mmW MIMO(e.g., Samsung; Qualcomm; Ayach et. al ‘12) 16
• O(np) complexity of the phase shifting network limits state-of-the-art to p=1
• All existing industry prototypes are based on single-beam phased arrays of modest size (<256 elements)
• Multiplexing is not possible with single-beam phased arrays
• Multiple apertures for multiple beams
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State-of-the-Art: Single-Beam Phased Arrays
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Multi-beam CAP-MIMO vs Single-beam Phased Arrays
14-16 Gbps100% BW/user
63 pJ/bit
1-2 Gbps1-7% BW/user
476 pJ/bit
CAP-MIMO
PHASED ARRAY
20dB
4, 25-beam CAP-MIMO Arrays(100 total beams)
(1 user/beam)
16, single-beamPhased Arrays
(16 total beams)(7 users/beam)
Beamspace MIMO framework enables optimization of both architectures
CAP-MIMO has 8X higher energy and spectral efficiency over phased arrays
Small cell design for supporting 100 users
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CAP-MIMO vs Multi-beam Phased Array
Spectral Efficiency Energy Efficiency
(X. Gao, L. Dai & AS ’16)
N=256, K=16 users, p = K =16 RF chains N=256, p = K RF chains
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2D Arrays for 3D Beamforming
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k-th user channel:
BeamspaceTransformation Matrix:
(2D DFT)
(JB & AS SPAWC ’14)
2D steering vector:
Beamspace Linear Precoding
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n x K Beamspace Precoder Matrix
n x K Multiuser Channel Matrix
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Downlink K x n system
Slice
Array
Multi User MIMO
w/ Beamforming
K users/
sector
Nb beams/sector
Small Cell
mmWave Backhaul
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Small-Cell AP Design: 2D Beam Footprints
AMS mmW MIMO(JB & AS SPAWC ’14)
0.5” x 3” antenna @ 80GHz 2.3” x 12” antenna @ 80GHz
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1.1” x 6” ant. @ 80GHz
Cell coverage (200m x 100m)
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Beam Selection: Sparsity Mask
Lower-dimensional K x p system
Full dimensional K x n system
Power-based thresholding to determine the set of dominant active beams
Beam sparsity mask
(AS & JB GCOM ‘13, JB & AS SPAWC ’14, JG & AS CISS ‘16)
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Sparse Precoding: Low Computational Complexity
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(MMSE precoder: Joham, Utschick, & Nossek 2005)
(AS & JB GCOM ‘13, JB & AS SPAWC ‘14)
Capacity:
MMSEPrecoder:
BeamspaceDownlink:
O(n) O(p) matrix operations
Performance vs Complexity: Perfect CSI
AMS mmW MIMO
Upperbound vs MMSE precoder performance
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p=16K=1600beams
2.3” x 12” ant. @ 80GHz
p=K=100beams
0.5” x 3” ant. @ 80GHz
p=4K=400beams
1.1” x 6” ant. @ 80GHz
p=K=100 (0.5” x 3”)
p=4K=400(1.1” x 6”)
p=16K=1600(2.3” x 12”)
x 3
x 10
4 beam mask/uservs
Full dimension
400 maxactive beams
p=16K=1600
Full dim. vs low-dim.# RF chains: p=K, 2K, 4K
(JB & AS SPAWC ‘14)
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Transmit SNR (dB)60 70 80 90 100
Cap
acit
y (
b/s
/Hz)
10-1
100
101
102
103
Full Dimensional Perfect CSIPerfect CSI, p=KNoisy BS, p=KNoisy CE, p=KNoisy BS+CE, p=K
Performance-vs-Complexity: with Beam Selection and Channel Estimation
Transmit SNR (dB)60 70 80 90 100
Cap
acit
y (
b/s
/Hz)
10-1
100
101
102
Full Dimensional Perfect CSIPerfect CSI, p=KNoisy BS, p=KNoisy CE, p=KNoisy BS+CE, p=K
Transmit SNR (dB)60 70 80 90 100
Cap
acit
y (
b/s
/Hz)
10-1
100
101
102
Full Dimensional Perfect CSIPerfect CSI, p=2KNoisy BS, p=2KNoisy CE, p=2KNoisy BS+CE, p=2K
K=10
K=50
p=K p=2K
(Path loss: 75-101 dB)
Transmit SNR (dB)60 70 80 90 100
Cap
acit
y (
b/s
/Hz)
10-1
100
101
102
103
Full Dimensional Perfect CSIPerfect CSI, p=2KNoisy BS, p=2KNoisy CE, p=2KNoisy BS+CE, p=2K
Full dim: ñ = 158
Transmit SNR (dB)60 70 80 90 100
Cap
acit
y (
b/s
/Hz/
use
r)
10-1
100
101
102
103
Full Dimensional Perfect CSIp=K Perfect CSIp=2K Perfect CSIFull Dimensional Noisy BS+CEp=K Noisy BS+CEp=2K Noisy BS+CE
Transmit SNR (dB)60 70 80 90 100
Cap
acit
y (
b/s
/Hz/
use
r)
10-1
100
101
102
103
Full Dimensional Perfect CSIp=K Perfect CSIp=2K Perfect CSIFull Dimensional Noisy BS+CEp=K Noisy BS+CEp=2K Noisy BS+CE
Full vs low-dim
Channel estimation (not Beam Sel.) is the limiting factorAMS mmW MIMO 26(JH & AS CISS’16)
Wideband mmW MIMO: Beam Squint Problem & Multi-beam Solution
AMS mmW MIMO 27
f/fc
-0.1 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.1
|Hb
,i(f
)|2/M
(d
B)
-18-15-12-9-6-30
i = io=25
i=24i=23i=26i=27
f/fc
-0.1 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.1
Σ|H
b,i(f
)|2/M
(d
B)
-18-15-12-9-6-30
3 beam5 beam
Phased array 3-beam CAP-MIMO 5-beam CAP-MIMO
(JB & AS ICC ’15)
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10GHz CAP-MIMO Prototype: Proof of Concept
40cm x 40cm Lens array
n=676, p=4 (channels), R=10ft
10 GHz LoS prototype theoretical performance:100 Gigabits/sec (1 GHz BW) at 20dB SNR
Compelling gains over state-of-the-art
AMS mmW MIMO 28
DLA 1DLA 2
(JB, NB & AS TAPS ’13; JB, PT, DV & AS SPAWC ’14)
FPGA DAC IQ
VCO
BPF PA
FPGAADC
LNA BPF IQ
LO
Features: • RF Bandwidth: 1GHz• Symbol rate: 125MS/s• 4x4 CAP-MIMO• Real-time comm. • Channel meas.
P2P Link: Spatial Filtering + Diff. Detection
AMS mmW MIMO 29(AS and JB ICC ’15)
DLA 1DLA 2
RF Bandwidth: 1GHzSymbol rate: 125MS/s4x4 P2P CAP-MIMOReal-time comm.
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P2MP Link: Space-Time Filtering & Coherent Detection
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Raw RX samples Spatial filtering Spatial+temporalfiltering
TX Frame RX Frame (MS2)
P2MP Channel Measurements @ 10GHz
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MS1MS2
Wide MS spacing
Narrow MS spacing
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28 GHz Advanced CAP-MIMO Prototype
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6” Lens with 16-feed Array
Use cases• Real-time testing of PHY protocols• Multi-beam channel measurements• Scaled-up testbed network
Features• RF Bandwidth: 1 GHz, Symbol rate: 370 MS/s • 4 simultaneous beams/data streams• Altera Arria 10 FPGA board for backed DSP• AP – 4 MS bi-directional P2MP link• Electronic multi-beam steering & data mux.
P2MP Link
Equivalent to 600-element
conventional array!Beamwidth=4 deg
5G Outlook and Impact: Multi-scale mmW Multi-beam MIMO Networks
Key Features:• Multi-Gbps Speeds• millisecond latency• Electronic multibeam steering & data multiplexing
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Key Use Cases• Backhaul• Mobile access• Last mile fiber-to-home• Vehicular networks (sensing & comm.)• M2M comm. (Gigabit)
mmWSmall Cell
mmWBackhaul
Timeline• Fixed wireless (1-5 yr.) • Mobile access (5-10 yr.)
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AMS mmW MIMO 34
CAP-MIMO Team: 2010-present
Gen 1: Hua Deng, Paul Thomas, David Virgilio & John Brady
Gen 3: John Brady, Luke Li, Sabareesh Ganapathy, Anuj Gadiyar
Gen 2: John Brady, Justin Cummings, Wasim Sheikh & John Hogan
• Innovations in basic theory & technology development
• Gen 2 prototype: 28 GHz, advanced functionality
• Channel measurements: massive, beamspace, and multi-beam
• Lens array and beam selector network optimization
• Spatial analog-digital interface design– Gigabit-rate DSP power hungry; more analog processing?
• Wideband high-dimensional MIMO– New insights into the “beam-squint” problem
– OFDM, SC, SC-OFDM? Short-Time Fourier Signaling
• Scaled up CAP-MIMO testbed & commercialization
Ongoing Work
AMS mmW MIMO 35
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Conclusion
• Beamspace MIMO: Versatile theory & design framework for mmW
• CAP-MIMO: practical modular architecture
– Scalable performance-complexity optimization
• Compelling advantages over state-of-the-art
– Capacity/SNR gains
– Operational functionality
– Electronic multi-beam steering & data multiplexing
• Timely applications (multi-Gigabits/s speeds & ms latency)
– Wireless backhaul networks: fixed point-to-multipoint links
– Smart 5G Basestations: dynamic beamspace multiplexing
– Last-mile connectivity, vehicular comm, M2M, satcom. etc.
• Prototyping & technology development
– Multi-beam CAP-MIMO vs Phased arrays?
AMS mmW MIMO 36
Relevant Publications(http://dune.ece.wisc.edu)
• A. Sayeed, Deconstructing Multi-antenna Fading Channels, IEEE Trans. Signal Proc., Oct 2002.• A. Sayeed and N. Behdad, Continuous Aperture Phased MIMO: Basic Theory and Applications, Allerton
Conference, Sep. 2010.• J. Brady, N. Behdad, and A. Sayeed, Beamspace MIMO for Millimeter-Wave Communications: System
Architecture, Modeling, Analysis, and Measurements, IEEE Trans. Antennas & Propagation, July 2013.• G.-H Song, J. Brady, and A. Sayeed, Beamspace MIMO Transceivers for Low-Complexity and Near-Optimal
Communication at mm-wave Frequencies, IEEE ICASSP 2013.• A. Sayeed and J. Brady, Beamspace MIMO for High-Dimensional Multiuser Communication at Millimeter-
Wave Frequencies, IEEE Globecom, Dec. 2013.• J. Brady and A. Sayeed, Beamspace MU-MIMO for High Density Small Cell Access at Millimeter-Wave
Frequencies, IEEE SPAWC, June 2014.• J. Brady, P. Thomas, D. Virgilio, A. Sayeed, Beamspace MIMO Prototype for Low-Complexity Gigabit/s
Wireless Communication, IEEE SPAWC, June 2014.• J. Hogan and A. Sayeed, Beam Selection for Performance-Complexity Optimization in High-Dimensional
MIMO Systems, 2016 Conference on Information Sciences and Systems (CISS), March 2016.• J. Brady and A. Sayeed, Differential Beamspace MIMO for High-Dimensional Multiuser Communication,
IEEE GlobalSIP, December 2015.• A. Sayeed and J. Brady, High Frequency Differential MIMO: Basic Theory and Transceiver Architectures,
IEEE ICC, June 2015.• J. Brady and A. Sayeed, Wideband Communication with High-Dimensional Arrays: New Results and
Transceiver Architectures, IEEE ICC, Workshop on 5G and Beyond, June 2015.• A. Sayeed and T. Sivanadyan, Wireless Communication and Sensing in Multipath Environments Using
Multiantenna Transceivers, Handbook on Array Processing and Sensor Networks, S. Haykin & K.J.R. Liu Eds, 2010.
• K. Liu, V. Raghavan, A. Sayeed, Capacity Scaling and Spectrum Efficiency in Wideband Correlated MIMO Channels, iEEE Trans. Inf. Th., Oct. 2003.
AMS mmW MIMO 37Thank You!