millimeter-wave mimo architectures for 5g gigabit...
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Millimeter-Wave MIMO Architectures for 5G Gigabit Wireless
Akbar M. Sayeed Wireless Communications and Sensing Laboratory
Electrical and Computer Engineering University of Wisconsin-Madison
http://dune.ece.wisc.edu
GLOBECOM Workshop on Emerging Technologies for 5G Wireless Cellular Networks
December 8, 2014
TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.:
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Supported by the NSF and the Wisconsin Alumni Research Foundation
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Explosive Growth in Wireless Traffic
AMS - mmW MIMO 1
(2014 Cisco visual networking index)
(Qualcomm)
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Current Industry Approach: Small Cells & Heterogeneous Networks
Key Idea: Denser spatial reuse of limited spectrum
Courtesy: Dr. T. Kadous (Qualcomm) Courtesy: Dr. J. Zhang (Samsung)
Some challenges: interference, backhaul
AMS - mmW MIMO 2
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New Opportunity: mm-wave Band
3kHz
300kHz
3MHz
30MHz
3GHz
30GHz
300MHz
300kHz
3MHz
30MHz
300MHz
3GHz
30GHz
300GHz
Mm-wave - Short range: 60GHz Long range: 30-40GHz, 70/80/90GHz
Current cellular wireless: 300MHz - 5GHz
AMS - mmW MIMO 3
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Mm-wave Wireless: 30-300 GHz A unique opportunity for addressing the wireless data challenge
– Large bandwidths (GHz)
– High spatial dimension: short wavelength (1-100mm)
Beamwidth: 2 deg @ 80GHz
35 deg @ 3GHz
45dBi
15dBi
80GHz
3 GHz
Highly directive narrow beams (low interference/higher security)
6” antenna: 6400-element antenna array (80GHz)
Compact high-dimensional multi-antenna arrays
Large antenna gain
AMS - mmW MIMO 4
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Current & Emerging Applications
• Wireless backhaul; alternative to fiber
• Indoor wireless links (e.g., HDTV) IEEE 802.11ad, WiGig
• Smart base-stations for 5G mobile wireless (small cells)
• New cellular/mesh/heterogeneous network architectures
• Space-ground or aircraft-satellite links
Multi-Gigabits/s speeds Multiple Beams
AMS - mmW MIMO 5
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Key Opportunities and Challenges
• Hardware complexity: spatial analog-digital interface
• Computational complexity: high-dimensional DSP
Electronic multi-beam steering & MIMO data multiplexing
Our Approach: Beamspace MIMO
Key Challenges:
Key Operational Functionality:
AMS - mmW MIMO (AS’02, AS&NB ’10, JB, AS, & NB ‘14) 6
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Beamspace MIMO
Antenna space multiplexing
Beamspace multiplexing
Discrete Fourier Transform (DFT)
n dimensional signal space
n-element array ( spacing)
n orthogonal beams
Related: communication modes in optics (Gabor ‘61, Miller ‘00, Friberg ‘07)
spatial channels
(AS’02, AS&NB ’10, JB, AS, & NB ‘14)
AMS - mmW MIMO 7
Multiplexing data into multiple highly-directional and high-gain beams
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n-element Antenna (Phased) Array
Spatial angle
TX: steering vector or
RX: response vector
AMS - mmW MIMO
Spatial frequency:
n-dimensional spatial sinusoid
8
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Orthogonal Spatial Beams
n orthogonal spatial beams
DFT spatial modulation matrix:
n = 40 Spatial resolution/beamwidth:
(DFT)
Unitary
AMS - mmW MIMO
(n-dimensional orthogonal basis)
9
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Antenna vs Beamspace Representation
(DFT) (DFT)
Multipath Propagation Environment
n x n MIMO system
AMS - mmW MIMO
MIMO Channel Matrix
10
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Key Characteristic at mmW: Beamspace Channel Sparsity
Point-to-point Point-to-multipoint
Communication occurs in a low-dimensional (p) subspace of the high-dimensional (n) spatial signal space
How to optimally access the communication subspace with the lowest – O(p) - transceiver complexity?
(DFT) (DFT)
TX Beam Dir.
RX
Beam
Dir
.
AMS - mmW MIMO
• Directional, quasi-optical • Primarily line-of-sight • Single-bounce multipath
11
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Continuous Aperture Phased (CAP) MIMO
Lens computes analog spatial DFT: direct access to beamspace
active beams (data streams)
Performance-Complexity Optimization: Optimal Performance with Lowest Hardware Complexity
Digital modes: p data streams
Analog modes: n >> p (continuous aperture) O(p) Transceiver
Complexity
Comm. through beams
Beam Selection p << n
active beams
AMS - mmW MIMO
Practical Hybrid Analog-Digital Transceiver Architecture for Beamspace MIMO (patented)
(AS & Behdad ‘10, ‘11; Brady, AS, Behdad, ‘12) 12
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Spatial Analog-Digital Interface: Digital vs Analog Beamforming
CAP MIMO: Analog Beamforming
Conventional MIMO: Digital Beamforming
Beam Selection p << n
active beams
O(p) transceiver complexity O(n) transceiver complexity
n: # of conventional MIMO array elements (1000-100,000)
p: # spatial channels/data streams (10-100) AMS - mmW MIMO 13
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CAP-MIMO vs Phased-Array-Based Architectures for Analog Beamforming
Multi-beam forming mechanism
14
O(p) transceiver complexity
Lens +
Beamspace Array +
mmW Beam Selector Network
Phase Shifter Network (np)
+ Combiner Network
CAP-MIMO:
Phased-Array Based Architecture:
AMS - mmW MIMO (e.g., Samsung; Ayach, Heath et. Al 2012) 14
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Case Study: Line-of-Sight Link
# analog spatial modes: (~ antenna/array gain)
AMS - mmW MIMO 15
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State-of-the-Art 1: DISH System
Narrow beam
Single data stream
A (aperture)
Large antenna gain (SNR gain) Narrow beam (continuous aperture)
Pros:
Cons:
(Bridgewave)
R (link length)
continuous aperture “dish” antennas
AMS - mmW MIMO 16
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State-of-the-Art 2: MIMO System
A (aperture)
Multiplexing gain: Multiple (p) data streams
(p limited by A and R)
Reduced SNR gain Cons:
Pros:
R (link length)
Grating lobes
Discrete Antenna Arrays (wide Rayleigh spacing)
Madhow et. al. 06’
Bohagen et. al. 07’
Chalmers
AMS - mmW MIMO 17
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Beamspace MIMO: Coupled Orthogonal Beams
number of coupled beams:
Finite Receiver Aperture
n = 40 orthogonal beams coupled beams
(Fresnel number)
(channel rank) Spatial
BW: Spatial
Res.: AMS - mmW MIMO 18
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Near-Optimality of Beamspace MIMO
0
5
10
15
20
25
30
05
1015
2025
30
1
1
1
approx. eigenvalues (diagonal)
approx. eigenvectors (RX subspace)
Beamspace: power concentration
approx. eigenvectors (TX subspace)
Coupled beams ~ channel eigenvectors
AMS - mmW MIMO
Antenna/spatial domain
Subspace determination through beamspace thresholding! 19
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Capacity Comparison with State of the Art
DISH no multiplexing gain
Max. SNR gain
Conv. (widely spaced) MIMO Max. multiplexing gain
small SNR gain
SNR gain over widely spaced MIMO:
MUX gain over DISH:
CAP-MIMO: Max. multiplexing gain & Max. SNR gain
Spectral Efficiency (bits/s/Hz)
AMS - mmW MIMO 20
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Potential Gains: Backhaul and Indoor Links
Longer (backhaul) link: R=533m, A=1mx1m, 80GHz
Shorter (indoor) link: R=10ft, TX: 6inx6in, RX: 6inx2in
2 bps/Hz
> 25dB
1 bps/Hz
> 40dB
p=1 p=2
:SNR n : spatial dimension
p: # data streams
Spectral efficiency (bits/s/Hz):
60GHz
80GHz
3GHz
AMS - mmW MIMO 21
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Point-to-Multipoint Links
(Driverlayer.com)
Fixed (backhaul) and dynamic (access) links
Sparse Beamspace Channel
AMS - mmW MIMO
Lower-dimensional system
Downlink precoding:
Beamspace precoding:
Multiuser channel:
Beamspace channel:
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Dense Beamspace Multiplexing
x 2-200 increase in capacity due to beamspace multiplexing
x 10-100 increase in capacity due to extra bandwidth (~1-10GHz vs 100MHz)
200Gbps-200Tbps (per cell throughput) (20-200Gbps/user)
30dB Ant. gain
6” x 6” antenna
Key application: small-cell access points
Beamspace channel sparsity
AMS - mmW MIMO (JB & AS ’13; JB & AS ’14)
Idealized upper bound (non-interfering users)
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Performance with Linear Precoding
(JB & AS Globecom 2013)
K = # users
AMS - mmW MIMO 24
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Number of Beams and Capacity Gap
AMS - mmW MIMO
Expected number of active beams With 2-beam/user sparsity mask
Normalized capacity gap between the upper bound and the MMSE precoder (SNR =30dB)
(JB & AS Globecom 2013) (MMSE precoder:
Joham, Utschick, & Nossek 2005) 25
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Small-Cell Design: 2D Beam Footprints
AMS - mmW MIMO (JB & AS, SPAWC 2014)
0.45” x 2.8” antenna @ 80GHz 2.3” x 12” antenna @ 80GHz
26
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Performance of APs with 2D Arrays
AMS - mmW MIMO
p=K=100 p=4K=400 p=16K=1600
p=K=100
p=4K=400
p=16K=1600
4 beam mask/user vs
Full dimension
Upperbound vs MMSE precoder performance
27
2.3” x 12” ant. @ 80GHz 0.5” x 3” ant.
@ 80GHz 1.1” x 6” ant.
@ 80GHz
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10GHz CAP-MIMO Prototype
40cm x 40cm DLA
R = 10ft, n=676, p=4
Multi Gbps speeds possible 10 GHz prototype theoretical performance: 100 Gigabits/sec (1 GHz BW) at 20dB SNR
Compelling performance gains over state-of-the-art
DLA 1 DLA 2
AMS - mmW MIMO 28
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Prototype TX/RX Hardware
FPGA DAC IQ
VCO
BPF PA
FPGA ADC LNA BPF IQ
LO
To DLA
From DLA
Prototype Specifications
● Operating frequency: 10 GHz ● Up to 4 spatial channels
● 125 MHz symbol rate
● 1 Gigabits/s with 4-QAM
● 8 bits/s/Hz spec. eff.
● TX-RX Clock/Oscillator
options ○ Shared clock and
oscillator ○ Separate clock or
oscillator ○ Separate clock and
oscillator
Transmitter:
Receiver: AMS - mmW MIMO 29
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Baseband to Passband
I(t)
Q(t)
10 GHz
Passband: output of TX PA
Passband: output of RX LNA
DAC output: I(t)
DAC output: Q(t)
u(t)
30 AMS - mmW MIMO
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2x2 Spatial Multiplexing Test ● 2 Spatial Channels ● 500 Mbps data rate ● Shared LO at TX and RX ● Separate TX and RX sample clocks
16 kbit test image 179 bit errors 0 bit errors
Transmitted 4-QAM Symbols Channel 1 received symbols with ISI and ICI
After MMSE MIMO processing to suppress spatial ICI
AMS - mmW MIMO 31
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Received Symbols: ICI vs ISI
ISI + ICI
With Guard
Interval (ICI only)
With Guard
Interval (suppressed ISI & ICI)
Without Guard
Interval
Suppressed ICI (MMSE Spatial Filter)
Without Guard
Interval (ISI)
AMS - mmW MIMO 32
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Outlook: Multi-scale mmW MIMO Networks
(Source: 3G.co.uk)
Availability: Atmospheric
absorption “small cell” Access Network
Backhaul network
Multi-Gbps speeds
(siliconsemiconductor.net) AMS - mmW MIMO 33
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• Channel Estimation & Discovery – compressed sensing vs thresholding?
– Analog subspace estimation
• Spatial Analog-Digital Interface – High symbol rates make DSP very power hungry
– Move more processing into analog (mmW)?
• Wideband High-Dimensional MIMO – Need to revisit “narrowband” analysis
– OFDM, SC, SC-FDMA … (limited selectivity)
• Electronic Multi-beam steering
• Channel Measurements (true beamspace)
Going Forward
AMS - mmW MIMO 34
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Conclusion • Optimal Beamspace MIMO Communication
– Versatile theory & computational framework for system design & optimization
• CAP-MIMO: practical architecture – spatial A-D interface + DSP
• Compelling advantages over the state-of-the-art – Capacity/SNR gains
– Operational functionality
– Electronic multi-beam steering & data multiplexing
• Timely applications (multi-Gigabits/s speeds) – Long-range wireless backhaul links; Indoor short-range links
– Smart 5G Basestations: High-Gain Dense Beamspace Multiplexing
• Gen 2 prototype 28GHz – channel meas. + tech. transfer
AMS - mmW MIMO 35
Performance-complexity optimization
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Relevant Publications • A. Sayeed, Deconstructing Multi-antenna Fading Channels, IEEE
Trans. Signal Processing, 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, 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.
AMS - mmW MIMO 36 Thank You!