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 Supported by the NSF and the Wisconsin Alumni Research Foundation

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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

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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

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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)

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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

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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)

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Antenna vs Beamspace Representation

(DFT) (DFT)

Multipath Propagation Environment

n x n MIMO system

AMS - mmW MIMO

MIMO Channel Matrix

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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

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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)

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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

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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

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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

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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!