Beamforming Antennas for
Wireless Communications
Yikun Huang, Ph.D.
ECE/CCB
Yikun@cns.montana.edu
November 24 2003
Outline
Introduction
Beamforming and its applications
Beamforming antennas vs. omnidirectional antennas
Phased Array Antennas
Direction of arrival (DOA) estimation
Beamforming
Basic configurations: fixed array and adaptive array
smart antenna systems:switched array and adaptive array
Vector Antennas
DOA and polarization
super CART
3-loop and 2-loop vector antenna array
Direction of arrival (DOA) estimation
Vector antenna vs. phased array antenna
Beamforming antennas for WLAN
Infrastructure mode
An indoor WLAN design
Ad hoc mode
Ad hoc WLAN for rural area
Conclusion
Applications of beamforming technology
Applications
Description
RADAR
Phased array RADAR; air traffic control; synthetic aperture
RADAR
SONAR
Source location and classification
Communications
Imaging
Smart antenna systems; Directional transmission and
reception; sector broadcast in satellite communications
Ultrasonic; optical; tomographic
Geophysical Exploration
Earth crust mapping; oil exploration
Astrophysical Exploration
High resolution imaging of universe
Biomedical
Neuronal spike discrimination; fetal heart monitoring;
tissue hyperthermia; hearing aids
Source: B.D.Van Veen and K.M. Buckley, University of Michigan, “Beamforming: A
Versatile approach to spatial filtering”,1988
Phased array RADAR
1
6
Phased array spike sorting
1
5
0.148
 0.534
4
t
1.210
0
t
1.210
1
4
0
0.139
1
3
Rn( 13  t )
 0.534
1
2
4
0.183
1
1
Rn( 11  t )
t
4
1.210
1
0
0
0.147
9
Rn( 9  t )
 0.534
t
4
1.210
8
0
0.147
Rn( 7  t )
7
Neuronal
spikes
recorded by
electrode
array
 0.539
 0.534
t
4
1.210
6
0
0.183
4
5
Rn( 5  t )
 0.539
4
0
t
1.210
0
t
1.210
t
1.210
0.139
2
3
Rn( 3  t )
 0.534
4
0.14
1
Rn( 1  t )
 0.534
0
4
Center for Computational Biology, MSU
Phased array spike sorting system
Rn( 15  t )
0.042
Ey 3n( t )

0.187
0
4
t
1.210
0.056
Ey 2n( t )

0.205
0
4
t
1.210
0.139
Ey 1n( t )
 0.544
0
t
4
1.210
Sorted
Spike of
individual
neurons.
top view(horizontal)
Patterns, beamwidth & Gain
side lobes
Main lobe
φ1/ 2
nulls
Half-power
beam width
side view(vertical)
Half-power
beam width
78°
Isotropic dipole
half-wave dipole
Half-power
beam width
θ1/ 2
beamformer
Beamformers vs. omnidirectional antennas
1)
Beamformers have much higher Gain than omnidirectional antennas:
Increase coverage and reduce number of antennas!
GN
 N2
Gain:
G1
90
6
120
6
60
4
150
30
2
Field( 6  0  )
Field( 2  0  )
Field( 1  0  )
180
0
0
210
330
240
300
270

9.96110
7
Beamformers vs. omnidirectional antennas
2) Beamformers can reject interference while omnidirectional
antennas can’t: Improve SNR and system capacity!
interference
user
null
interference
user
3) Beamformers directionally send down link information to the
users while omnidirectional antennas can’t: save energy!
Beamformers vs. omnidirectional antennas
4) Beamformers provide N-fold diversity Gain of omnidirectional antennas:
increase system capacity(SDMA)
5) Beamformers suppress delay spread:improve signal quality
null
user
user
multipath
DOA estimation
Plane wave
……
φk
……
1
2
3
4
5
6
7
N-3
N-2
N-1
N
d
δk  d sinφk
Δk 
phase delay
2πd
sin φk  β  kd sin φk  β
λ
Beamforming
……
φk
……
1
2
3
4
5
6
7
1,,k 2,,k 3,,k
4,,k
5,,k
6,,k
7,,k
N-3
N-2
N-1
N
N-3,,k N-2,,k N-1,,k N,,k
phase shifters
……
ΔN,k  (N  1)( kd sin φk  β )
Basic phased array configurations
sN(k)
s2(k)
.
.
.
w*N,0
Z-1
w*N,1
.
.
.
y (k )
w*2

s2(k)
.
.
.
w*N
sN(k)
Z-1
Z-1
w*N,k-1
Z-1
s1(k)
w*1
s1(k)
Z-1
w*1,0
Narrowband
w*2,1
w*2,k-1
Z-1
w*1,1
.
.
.
w*2,0
.
.
.
y (k )
w*1,k-1
broadband
phased array (fixed/adaptive) configurations-time domain

.
.
.
s2(k)
s1(k)
F
F
T
F
F
T
w*N
.
.
.
…
sN(k)

I
F
F
T
d (t )
y (k )
+
MSE
w*2
F
F
T
…
F
F
T
…
Basic phased array configurations
w*1
broadband
phased array (fixed/adaptive) configuration-frequency domain
Smart antenna systems
Military
networks
switched array
adaptive array
Cellular
communication
networks
switched array
adaptive array
3G Data rate:100kbps
Wireless
local area
networks
switched array
adaptive array
Wi-Fi Data rate:11Mbps
Smart antenna systems
top view(horizontal)
5
4
6
3
7
2
interference
8
1
9
16
10
15
11
12
14
13
Switched array (predetermined)
user
Smart antenna systems
top view(horizontal)
Interference 1
user 1
user 2
Interference 2
Adaptive array
Smart antenna system
Example: Vivato 2.4 GHz indoor & outdoor Wi-Fi Switches
(EIRP=44dBm;Gain=25 dBi;3-beam)
In door range
(Mixed Office)
11 Mbps: up to 300m
5.5 Mbps: up to 400m
2 Mbps: up to 500m
1 Mbps: up to 600m
Out door range
(outdoor to indoor)
11 Mbps: up to 1.00km
5.5 Mbps: up to 1.25km
2 Mbps: up to 2.00km
1 Mbps: up to 2.50km
Out door range
(outdoor to outdoor)
11 Mbps: up to 4.20km
5.5 Mbps: up to 5.10km
2 Mbps: up to 6.00km
1 Mbps: up to 7.20km
Active user per switch
100
www.vivato.net
100
12
Polarization
circular
Ei
E i sinγe jη
ellipse
E
linear
E
E
Z
E cos γ
i
Y

’


E

E

E
X
=90
=45
=0
Super CART
SuperCART
Compact array radiolocation technology
Flam&Russell,Inc.,1990
U.S. Patent No., 5,300,885;1994
Frequency range: 2 – 30 MHz
3-loop
V6
Y
V4

Ve   I ( ) Z L
V1
b
V2
V3
V5
kb0.5
i
I   zˆ  H 0
i
I   yˆ  E0
V0e   I (0) Z L
X
2-loop
Blind point
E
H
S
Steering vector
 e y  sin Φ0 cos Θ
  
 sin Θ
e 
a40   z   

 h x    sin Φ 0
h 
0
 z 
cos Φ0 

jη
0
 sinγe 


cos Φ0 cos Θ cos γ 

sin Θ 
Ei0
H 
ζ
i
0
ex2  ey2  ez2  1
hx2  hy2  hz2  1
Vector antennas vs. spatial array antennas
Vector antennas measure: ,,,, and power simultaneously,
no phase shift device, or synchronization is needed.
Phased array antennas with omnidirectional element measure:
,, and power
Vector antennas vs. spatial array antennas
VA
SA
VA
SA
Source: Nehorai,A.,University of Illinois at Chicago
Vector antennas vs. spatial array antennas
Vector antenna: no ambiguities for DOA estimation
e x , e y , e z , h x , h y , hz  φ, θ,γ , η, P
Phased array antennas: spatial ambiguities exist
φk
φ1
φ2
1
2
……
3
4
5
7
6
φk
1
2
……
3
4
5
6
f1 sinφ1  f2 sinφ2
7
Vector antennas Vs. phased array antennas
Disadvantages of vector antennas
Low profile?
f=2.4GHz,  =0.125m; vector antenna size: 0.0125m ~ 0.063m
Phased array:d /2=0.063m;L=(N-1)d: 0.188m-0.69m(N=4…12)
f=800MHz,  =0.375m; antenna size: 0.04m ~ 0.19m
Phased array:d /2=0.19m;L=(N-1)d: 0.56m-2.06m(N=4…12)
Cheap?
Can use hardware and software of existing communication
systems for performance?
Working in scattering environment
source:M.R. Andrews et al., Nature, Vol. 409(6818), 18 Jan. 2001, pp 316-318.
Low profile antennas with polarization diversity
(a) 2-dipole(monopole)
(b) 2-loop
(c) dipole-loop
Packet switching
AP1
AP2
A
user
Handoff between Aps
was not standardized
at the same time as
802.11b
TDD/TDMA
Packet switching: 3 beam system
top view(horizontal)
Pi 1
d
Δφ
Pi
Δφ
φˆ DOA
Pi 1
P. Sanchis, et al. 02
Pi 1  Pi 1
Pi
i
φmax
 1 / d  2  ( Δφ / 2), d  1
 i
 φmax
 d  ( Δφ / 2),
d 1
 i
φmax  1 / d  2  ( Δφ / 2), d  1
An indoor WLAN design
A 4-story office building (including basement), high 30 m, wide 60m and long 100m. We plan
to install a Vivato switched array on the 3rd floor.
Switched array
3
2
h=30m
1
Basement
w=60m
L=100m
An indoor WLAN design
Data rate
1Mbps, 2Mbps, 5.5Mbps, 11Mbps
AP’s EIEP
44dBm
AP’s antenna Gain GA
25 dBi
PC antenna Gain GP
0 dBi
Shadowing
8dB
AP’s antenna receiving sensitivity Smin
-95dBm ,-92dBm, ,-89dBm, -86dBm
AP’s Noise floor
-178dBm/Hz
Body/orientation loss
2dB
Soft partition attenuate factor (p= number)
p1.39 dB
Concrete-wall attenuate factor(q= number)
q2.38 dB
Average floor attenuation(floor number)
14.0dB(1),19.0dB(2),23.0dB(3),26.0dB(4)
Frequency
2.4GHz
Reference pathloss PL0 (LOS/NLS, r=1m)
45.9dB/ 50.3dB
Pathloss exponent  (LOS/NLS, r=1m)
2.1/3.0
Pathloss standard deviation  (LOS/NLS)
2.3dB/4.1dB
Average floor attenuation(floor number)
14.0dB(1),19.0dB(2),23.0dB(3),26.0dB(4)
Data of AP’s antenna is from www.vivato.net
An indoor WLAN design
Mean pathloss with smin:
Allowable pathloss:
L  EIRP  Smin  GP
PLallowable  L  Lw  Lsm  Lfl  Lsd  Lo
Path loss model: PL(r )  PL0  10γ log( r )
r0
PL(r )  PLal
Case 1: user is on the 3rd floor: 3 concrete walls, 3 soft partitions
The coverage ranges are: r=176m,140m,111m and 88m for date rate at 1Mbps,
2Mbps, 5.5Mbps and 11Mbps respectively .
Case 2: user is in the basement : 3 floors; 2 concrete walls, 3 soft partitions
The coverage ranges are:r=36m,29m,23m and 18m for date rate at 1Mbps, 2Mbps,
5.5Mbps and 11Mbps respectively
Beamforming antennas in ad hoc networks
throughput obtained by each node
 W 

~
 n log n 


new
routing
protocol
P.Gupta and P.R. Kumar,00
new
channel
access
scheme
?
Beamforming
antennas
Beamforming antennas in ad hoc networks
Z0=50,L/2 Z0=25,L/2
Z0=50
Series resonant patch array
interference
Phased patch
antenna
target
Phased patch array
D.Lu and D.Rutledge,Caltech,02
Beamforming antennas in ad hoc networks
Medium Access Control Protocol(CSMA/CA)
CSMA/CA:carrier sense multiple access/collision avoidance
( for omnidirectional antennas)
 No standard MAC protocols for directional antenna
 No obvious improvement for throughput using beamforming antennas
Neighbor discovery
 Neighbor discovery become more complex using beamforming antennas.
Packet routing (Scheduled/On-demand)
 Ad hoc networks may achieve better performance in some cases
using beamforming antennas.
 Beamforming antennas can significantly increasing node and
network lifetime in ad hoc networks.
Channel access
1) traditional exposed node
problem for omnidirectional
antennas
A
B
RTS
C
D
2) Omnidirectional and
directional antennas solve
the exposed node problem
A
E
B
C
D
E
RTS
RTS
CTS
CTS
CTS
DATA DATA
DATA
CTS
RTS
CTS
CTS
DATA
The nodes
are
prohibit to
transmit or
receive
signals
DATA
DATA DATA
ACK
Source:Y Ko et al., 00
ACK
The node
is free to
transmit or
receive
signals
ACK
DATA
ACK
The node is
blocked to
communicat
e with C
1) No coverage change. May save power.
2) B may not know the location of C.
Channel access
3) beamforming antennas create new problems
A
B
C
D
E
A
B
RTS
RTS
CTS
CTS RTS
C
CTS
DATA
RTS
DATA
collision
collision
DATA
deaf
D
E
Neighbor discovery
Nt
“Hello”
B
A
t
C
E
D
A
AP
Neighbors
A
B
C
D
E
B,C
A,C
A,B,E
E
C,D
Ad hoc WLAN for rural area
Conclusion
Beamforming antenna systems improve wireless
network performance
-increase system capacity
-improve signal quality
-suppress interference and noise
-save power
Beamforming antennas improve infrastructure
networks performance. They may improve ad hoc
networks performance. New MAC protocol
standards are needed.
Vector antennas may replace spatial arrays to
further improve beamforming performance