From Adaptive Antennas to MIMO Systems and Beyond

Yasutaka OgawaHokkaido University, Sapporo, Japan

February 2016

1

Concept of Adaptive Antenna2

S

Weight Control

q

#1

#2

#N

Array Output

1( ) ( )

N

i ii

y t w x t

1( )x t

2 ( )x t

( )Nx t

1w

2w

Nw -50

-40

-30

-20

-10

0

10

0 30 60 90 120 150 180 [deg.]

DesiredSignalInterference

Control of the array pattern

History of Adaptive Antenna Research

1950sRetrodirective arraySelf-steering array

1960sSidelobe cancellerMSN adaptive arrayMMSE adaptive array

Anti-jamming for military useCommercial applications were NOT considered

3

Beamforming

Interference suppression bynull steering

Applications to Commercial Mobile Radio

What benefits?Multipath suppression

- High-speed transmissionRange extensionInterference reduction

- Lower cell repeat pattern- Same channel reuse (SDMA) Efficient use of frequency

4

Secret History behind the Research Field

Strong Objection to Adaptive Antennas

in the Research Community

5

Objection 16

“No Need for Adaptive Antennas”An ultra low sidelobe antenna can reduce interference

InterferenceDesired Signal

Interference

Objection 27

“People who do not know radio waves study adaptive antennas”

TX Side Channel RX Side

Dual Polarized Communication ModelY. Ogawa, et al., “Basic studies on dual polarized communications in a land mobile radio system,” IEICE Technical Report, AP88-15, June 1988．

Objection 2 cont’d8

XPICCross PolarizationInterference Canceler

RX Structure

Increased Interest in Applications to Mobile Radio

Project in EuropeTechnology in Smart antennas for the UNiversal Advanced Mobile Infrastructure (TSUNAMI) (1994.1〜1995.12)

University of Bristol, Aalborg University, Alcatel SEL, Hagenuk GMBH, …

Hokkaido University GroupY. Ogawa, et al., “Behaviors of an LMS adaptive array for multipath fading

reduction,” IECE Trans., vol. E67, no. 7, pp. 395-396, July 1984.

9

SDMA with Multibeam Adaptive Antenna

- Multibeam adaptive antenna can separate multiple-user signals- Accommodation of multiple users in the same frequency band

in the same cell- Space Division Multiple Access (SDMA)

10

ユーザ1

ユーザ2

ユーザ2のパターン

ユーザ1のパターン

基地局

User 1

Basestation

Pattern for user 2User 2

Pattern for user 1

Commercial PHS-SDMA Basestation14

First commercial SDMA in the world

Emergence of MIMO Systems

- Multiple antennas at both of a transmitter and a receiver- Multipath-rich environments- Each channel is contribution of multipath signals- Correlations between channels are low

15

TX RX

#1

#2

#1

#2

Why MIMO ? (1)16

Transmit Power P According to Shannon,

Transmit Power 2P

SN

2SN

2

2

log 1 bps/Hz

log 1

SCN

S SN N

2

2

2log 1

2log

SCNS

NC

1

Why MIMO ? (2)17

Transmit Power 2P

SN

2

2

2 log 1

2log

2

SCN

SN

C

SN

P

P

A MIMO system generates parallel channels in a spatial domain in multipath-rich environments, and increases channel capacity

Transmitter Receiver

Multipath Signal: Our Friend or Enemy ?Generating multiple channels: Good !Causing fading: No Good !

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Almost no fading for maximum eigenvalue channels Fading depth is small even for minimum eigenvalue

channels in MIMO systems with many antennas

Maximum Eigenvalues of HHH Minimum Eigenvalues of HHH

Cum

ulat

ive

Dis

tribu

tion

Amplitude [dB]

4x4

4x20

4x100

-30 -20 -10 0 10 20 300

0.2

0.4

0.6

0.8

1

Cum

ulat

ive

Dis

tribu

tion

Amplitude [dB]

4x4

4x20

4x100

-30 -20 -10 0 10 20 300

0.2

0.4

0.6

0.8

1

First Paper Dealing with the MIMO Concept

Jack H. Winters, “On the Capacity of Radio Communication Systems with Diversity in a Rayleigh Fading Environment,” IEEE Journal on Selected Areas in Communications, vol. SAC-5, no. 5, pp. 871-878, June 1987.

“… the communication channels between multiple transmit and/or receive antennas can have low cross correlation even when the transmit or receive antennas are closely spaced.”

上記論文の図６を貼り付ける

Fig. 6. Radio system consisting of two users, …

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First Paper Dealing with the MIMO Concept cont’dOptimum Transmitter/Receiver Processing

The total normalized capacity is given byIs = log2 (1 + i Pi)

The Pi’s that maximize Is can be found by using the water fillanalogy …

20

This is one of my biggest regrets.

I noticed the paper, but did not recognize the importance and significance of it.

Key Technologies for 5G Cellular Network

Massive MIMO utilizing a very high number of antennas

Millimeter wave with an enormous amount of spectrum

A successful marriage of massive MIMO and millimeter waves may take on a considerably different form

F. Boccardi, R.W. Heath Jr., A. Lozano, T.L. Marzetta, and P. Popovski, “Five Disruptive Technology Directions for 5G,” IEEE Commun. Mag., vol. 52, no. 2, pp. 74-80, Feb. 2014.

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Hybrid Beamforming for Massive MIMO22

Reasonable structure Low complexity Beamforming gain available for pilot

Analog Beamformer

RFAD/DA

RFAD/DA

RFAD/DA

RFAD/DA

Digital Beamformer

Analog Beamformers23

Multibeam Phased Array (Full Array, Subarray)

Butler Matrix Lens Antenna

4x4 Buttler Matrix

Dielectric

Beam Selection in an Analog Multi-Beamformer24

Fast beam selection is important in an analogmulti-beamformer

Example:- Beamformer with a 64x64 Butler Matrix and 4 RF units- Search a port with the maximum output power of a pilot

64 x 64 Butler Matrix

RF Unit #1 RF Unit #2 RF Unit #3 RF Unit #4

Antennas

Ports

#1 #2 #3 #64

#1 #2 #3 #64

64x64 Butler Matrix Beamformer25

64 orthogonal beams realized by a 64x64 Butler Matrix

An appropriate beam toward a user terminalmust be selected out of the 64 beams

Beam Selection in a Butler Matrix Beamformer26

16 Measurements are needed if all the port powers are measured

１ 2 3 4 5 6 7 8 910111213 14 15 16

Efficient Beam Selection (1)27

4 Broad beams are formed with 4 antennas and a 4x4 Butler Matrix

S. Yuki, Y. Ogawa, T. Nishimura, and T. Ohgane, “A Study on Beam Selection in High Frequency Band Analogue Beamformer,” IEICE Technical Report, RCS2015-88, June 2015．

Efficient Beam Selection (2)28

The terminal direction is roughly estimated with the 4 antennas

Efficient Beam Selection (3)29

More accurate terminal direction is estimated with the 16 antennas and 16x16 Butler Matrix

Efficient Beam Selection (4)30

Appropriate beam for the 16 antennas is selected out of the 4 beams

Efficient Beam Selection (5)31

Appropriate beam for all the 64 antennas is selected out of the 4 beams

Efficient Beam Selection (6)32

Optimum beam is selected with the 3 measurements

For Further Development of MIMO Systems33

Digital SignalProcessing

Propagation Analysis

Analog Technology