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Introduction to MIMO OTA
Environment Simulation: Calibration,
Validation, and Measurement Results
Dr. Michael D. Foegelle
Director of Technology Development
ETS-Lindgren
07-08-2011
Copyright 2011, ETS-Lindgren, LP
The Meaning of MIMO
MIMO and the RF Environment
The Channel Emulator
Understanding the Channel Model
Implications of OTA Testing
Spatial Environment Simulation
Calibrating the System
System Validation
Outline
07-08-2011 2
Copyright 2011, ETS-Lindgren, LP
Wi-Fi and LTE Throughput Measurement Results
with the ETS-Lindgren AMS-8700 OTA
Environment Simulator
Metrics
Outline
07-08-2011 3
Copyright 2011, ETS-Lindgren, LP
MIMO stands for Multiple Input, Multiple Output
and refers to the characteristics of the
communication channel(s) between two devices.
In communication theory, a channel is the path by
which the data gets from an input (transmitter) to
an output (receiver).
For Ethernet or USB, the channel is the cable used.
For wireless, the channel includes the RF frequency
bandwidth, the space between antennas, and anything
that reflects RF energy from one point to the other.
Often includes antennas and cables too.
The Meaning of MIMO
07-08-2011 4
Copyright 2011, ETS-Lindgren, LP
The term MIMO is often used to represent a
range of bandwidth/performance enhancing
technologies that rely on multiple antennas in a
wireless device.
These can be classified into several categories:
“True” Spatial Multiplexing MIMO.
SIMO (Single Input, Multiple Output) technologies like
beam forming and receive diversity.
While this discussion will concentrate on downlink
MIMO, uplink MIMO/MISO concepts are similar.
The Meaning of MIMO
07-08-2011 5
Copyright 2011, ETS-Lindgren, LP
“True” MIMO uses multiple transmit and receive
antennas to increase the total information
bandwidth through time-space coding.
Multiple channels of communication (streams) share
the same frequency bandwidth allocation
simultaneously.
The Meaning of MIMO
07-08-2011 6
MIMOTransmitter
MIMOReceiver
1101
0010 1010 1001 0000 1100 1110 0110 0
01 101 1001 0 1 00 111 01
1
11101 111 0
1 00
Copyright 2011, ETS-Lindgren, LP
SIMO technologies use the multiple (receive)
antennas to improve single channel performance
under edge-of-link (EOL) conditions.
Beam forming allows creating a stronger gain
pattern in the direction of the desired signal while
simultaneously rejecting undesired signals from
other directions.
The Meaning of MIMO
07-08-2011 7
Null (Low Gain)oriented in direction of interfering signal
DesiredSignal PathUnwanted
Interferer
Main Lobe(Highest Gain)
oriented in desiredcommunication direction
Copyright 2011, ETS-Lindgren, LP
Receive diversity uses multiple antennas to
overcome channel fades by using additional
antenna(s) to capture additional information that
may be missing from the first channel.
Includes simple switching diversity or more
complicated techniques like maximal ratio combining or
other combinatorial diversity techniques.
The Meaning of MIMO
07-08-2011 8 1905 19101906 1907 1908 1909
-140
-80
-130
-120
-110
-100
-90
1905 19101906 1907 1908 1909
-140
-80
-130
-120
-110
-100
-90
1905 19101906 1907 1908 1909
-140
-80
-130
-120
-110
-100
-90
Copyright 2011, ETS-Lindgren, LP
All of these multiple antenna technologies share
one thing in common – their performance is a
function of the environment in which they’re used.
The device adapts to its environment through
embedded algorithms that change its (effective)
radiation pattern.
MIMO and the RF Environment
07-08-2011 9
Radiated Performance
Po
we
r (
dB
m)
-85
-55
-80
-75
-70
-65
-60
Y
Z
X
Azimuth = 104.6
Elevation = -25.1
Roll = -51.5
Radiated Performance
Po
we
r (
dB
m)
-80
-55
-75
-70
-65
-60
Y
Z
X
Azimuth = 104.6
Elevation = -25.1
Roll = -51.5
Radiated Performance
Po
we
r (
dB
m)
-85
-55
-80
-75
-70
-65
-60
Y
Z
X
Azimuth = 104.6
Elevation = -25.1
Roll = -51.5
Copyright 2011, ETS-Lindgren, LP
Traditional TRP and TIS metrics are properties of
the mobile device only. The represent the
average performance of the device to signals
from any direction.
MIMO and the RF Environment
07-08-2011 10
Y
Z
X
TRP
Copyright 2011, ETS-Lindgren, LP
Metrics like Near Horizon Partial Radiated
Power/Sensitivity terms or Mean Effective Gain
apply simple environmental models to fixed
pattern data, but the basic behavior of the device
does not change.
MIMO and the RF Environment
07-08-2011 11
Y
Z
X
TRP
26.3 dBm
Y
Z
XY
Z
X
NHPRP +/-45° (Pi/4)
25.2 dBm
NHPRP +/-30° Pi/ 6)
23.7 dBm
(
Copyright 2011, ETS-Lindgren, LP
For MIMO technologies, performance is a
function of the system and cannot be restricted to
the mobile device.
Individual device performance can only be
evaluated compared in a given environment.
This implies the need for environment simulation.
MIMO and the RF Environment
07-08-2011 12
Environment #1 Environment #2
Copyright 2011, ETS-Lindgren, LP
A channel emulator is typically used for
conducted testing of MIMO radios.
The channel emulator simulates the wireless
channel between transmit and receive radios
using a channel model.
Channel models simulate not only a given
environment, but also properties of the base
station and mobile device including antenna
patterns, antenna separation, and angles of
departure/arrival (AOD/AOA).
The Channel Emulator
07-08-2011 13
Copyright 2011, ETS-Lindgren, LP
The Channel Emulator
A typical RF channel emulator consists of a number
of VSA receivers and VSG transmitters connected to
a DSP modeling core that introduces delay spreads,
fading, etc. at baseband.
07-08-2011 14
Receiver(VSA)
Transmitter(VSG)
DSPModeling
Core
Receiver(VSA)
Transmitter(VSG)
Receiver(VSA)
Transmitter(VSG)
Copyright 2011, ETS-Lindgren, LP
The Channel Emulator
The ideal channel emulator routes multiple inputs to
multiple outputs after applying appropriate modeled
delay spreads, fading, etc.
07-08-2011 15
Transmitter 1
Receiver1
Transmitter2
Receiver2
ChannelEmulation
Copyright 2011, ETS-Lindgren, LP
Understanding the Channel Model
In the real world, various objects in the environment
cause reflections of the transmitted signal that are
seen at the receiver.
07-08-2011 16
Reflecting Objectsin Environment
Propagation Ray Paths
Transmitter
Receiver
Copyright 2011, ETS-Lindgren, LP
Understanding the Channel Model
Signal paths are often classified as Line-of-Sight
(LOS) and Non-Line-of-Sight (NLOS).
07-08-2011 17
Transmitter
Receiver
NLOS
LOS
NLOS
Copyright 2011, ETS-Lindgren, LP
Understanding the Channel Model
Each path has a different length (propagation delay).
07-08-2011 18
Transmitter
Receiver
B
A
C
D
A
B
C
D
Copyright 2011, ETS-Lindgren, LP
Understanding the Channel Model
Plotting the signal strength vs. time gives a power
delay profile (PDP) for the model.
07-08-2011 19
A
B
C
D
Time
Sig
nal
Str
en
gth
Power Delay Profile
A
B
C
D
Copyright 2011, ETS-Lindgren, LP
Understanding the Channel Model
The individual times of arrival are called taps,
drawing from the concept of a tapped delay line.
07-08-2011 20
Time
Sig
na
l S
tre
ng
th
Power Delay Profile
A
B
C
D
Taps
Copyright 2011, ETS-Lindgren, LP
Understanding the Channel Model
Reflecting objects typically don’t just cause one
reflected signal.
Instead, scatterers produce a cluster of reflections
with slightly different delays and varied magnitude
and phase.
07-08-2011 21
Transmitter
Receiver
“Cluster” of Reflections
Copyright 2011, ETS-Lindgren, LP
Understanding the Channel Model
Each cluster produces its own unique statistical PDP.
07-08-2011 22
Transmitter
Receiver
“Cluster” of Reflections
Time
Sig
na
l S
tre
ng
th
Cluster PDP
Copyright 2011, ETS-Lindgren, LP
Combining the cluster concept with the tap concept
produces realistic time domain profiles.
Understanding the Channel Model
07-08-2011 23
Time
Sig
na
l S
tre
ng
th
Power Delay Profile
A
B
C
D
Taps
Copyright 2011, ETS-Lindgren, LP
Now the modeled data looks a lot like real measured
time domain data acquired using a vector network
analyzer.
Understanding the Channel Model
07-08-2011 24
Copyright 2011, ETS-Lindgren, LP
Understanding the Channel Model
Motion of the transmitter, receiver, or other objects
within the environment causes Doppler shift of the
frequency.
07-08-2011 25
Transmitter
Receiver
Copyright 2011, ETS-Lindgren, LP
Understanding the Channel Model
Moving towards a wave increases its frequency,
while moving away decreases the frequency.
A moving radio results in Doppler
spread since it moves towards
some reflections and away from
others.
07-08-2011 26
=+
=+
Copyright 2011, ETS-Lindgren, LP
Spatial channel models include geometric information
about the location of scatterers, and determine
channel behavior based on angles of departure and
arrival (AOD/AOA) and the angular spread for each
cluster.
Understanding the Channel Model
07-08-2011 27
Copyright 2011, ETS-Lindgren, LP
Spatial channel models for conducted testing also
apply assumed antenna patterns for the source and
receiver.
Understanding the Channel Model
07-08-2011 28
2x2 Channel Emulation
Two Transmitter
BSE
Two Receiver
Radio
Simulated TransmitAntenna Patterns
Simulated ReflectionClusters
Simulated ReceiveAntenna Patterns
Copyright 2011, ETS-Lindgren, LP
A primary goal of OTA testing is to determine
radio performance of the DUT with the actual
antenna patterns, orientation, and spacing.
If this was all that was required, a combination of
antenna pattern measurement and conducted
channel modeling would suffice.
However, traditional OTA measurements of
TRP/TIS perform simultaneous evaluation of the
entire RF signal chain for a variety of reasons:
Implications of OTA Testing
07-08-2011 29
Copyright 2011, ETS-Lindgren, LP
Platform Desensitization – interference from
platform components enters radio through
attached antennas.
Implications of OTA Testing
07-08-2011 30
GPS
WCDMA
Baseband
ProcessorWi-Fi
Backlight
Bluetooth
Antenna Another
Antenna
And Yet
Another
Antenna
One More
Antenna
Copyright 2011, ETS-Lindgren, LP
Near Field Influences – including platform
structure, head, hands, body, table top, etc.
Implications of OTA Testing
07-08-2011 31
Copyright 2011, ETS-Lindgren, LP
Mismatch and other Interaction Factors –
performance of a radio into a matched 50 Ohm
load may not be the same as that into a
mismatched or detuned antenna, resulting in non-
linear behavior.
Antenna-Antenna Interactions – mutual coupling
of antennas may not be accounted for properly in
pattern tests.
Cable Effects – currents on feed cables can alter
the radiation pattern, especially for small DUTs.
Implications of OTA Testing
07-08-2011 32
Copyright 2011, ETS-Lindgren, LP
MIMO relies on a complex multipath environment
to provide the information necessary to
reconstruct multiple source signals that have
been combined into multiple receive signals.
Spatial Environment Simulation
07-08-2011 33
Reflecting Objectsin Environment
Propagation Ray Paths
MIMOTransmitter MIMO
Receiver
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
The goal of the OTA Environment Simulator is to
place the DUT in a controlled, isolated near field
environment and then simulate everything outside
that region.
Reflecting Objectsin Environment
Propagation Ray Paths
MIMOTransmitter MIMO
Receiver
07-08-2011 34
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
Example: Typical Multi-Path Power Delay Profile
from a Real World Environment
07-08-2011 35
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
Using a fully anechoic chamber to isolate the DUT, a
matrix of antennas arrayed around the DUT can be
used to produce different angles of arrival (AOA).
07-08-2011
DUT
Path 1 (LOS)AOA = 0
Path 2 AOA ~135°
Path 3 AOA ~225°
Path 4 AOA ~45°
36
Copyright 2011, ETS-Lindgren, LP
A spatial channel emulator (a channel emulator with
modified channel models) simulates the desired
external environment between BSE and DUT.
Spatial Environment Simulation
07-08-2011 37
DUT
MIMOTester
SpatialChannelEmulator
Copyright 2011, ETS-Lindgren, LP
Evaluation of SIMO functions like beam forming and
receive diversity likely require only rudimentary
environment simulation.
Sufficient to simulate only basic directional effects and
spatial fading.
While there are a variety of simplistic ways to create
an external environment containing delay spread,
fading, and even repeatable reflection “taps”, they
may be insufficient for proper evaluation of MIMO
performance.
Spatial Environment Simulation
07-08-2011 38
Copyright 2011, ETS-Lindgren, LP
Spatial channel models include clusters of scatterers
with each tap having an angular spread as well as a
delay spread.
Spatial Environment Simulation
07-08-2011 39
Copyright 2011, ETS-Lindgren, LP
The angular spread of a given cluster is simulated by
feeding multiple antennas with an appropriate
statistical distribution of the source signal.
Designing the OTA Environment Simulator
07-08-2011
DUT
40
Copyright 2011, ETS-Lindgren, LP
Converting a conducted channel model to an OTA
channel model:
Conducted model simulates TX and RX antennas.
Spatial Environment Simulation
07-08-2011
2x2 Channel Emulation
Two Transmitter
BSE
Two Receiver
Radio
Simulated TransmitAntenna Patterns
Simulated ReflectionClusters
Simulated ReceiveAntenna Patterns
41
Copyright 2011, ETS-Lindgren, LP
Conducted channel model:
Ray paths from reflections in simulated environment are
collected at each simulated receive antenna.
Spatial Environment Simulation
07-08-2011
2x2 Channel Emulation
Two Transmitter
BSE
Two Receiver
Radio
Simulated Ray PathsBetween TX and RX Antennas
42
Copyright 2011, ETS-Lindgren, LP
Converting a conducted channel model to an OTA
channel model:
Clusters produced different angles of arrival (AOA)
Spatial Environment Simulation
07-08-2011
2x2 Channel Emulation
Two Transmitter
BSE
Two Receiver
Radio
Directions of Received Signals(Angles of Arrival)
43
Copyright 2011, ETS-Lindgren, LP
Converting a conducted channel model to an OTA
channel model:
Grouping AOAs, we can remove virtual RX antennas.
Spatial Environment Simulation
07-08-2011
2x2 Channel Emulation
Two Transmitter
BSE
Two Receiver
Radio
Region around Simulated DUT
44
Copyright 2011, ETS-Lindgren, LP
OTA channel model:
2xN channel emulator used to feed N antennas for AOA
simulation around DUT with real antennas.
Spatial Environment Simulation
07-08-2011
DUT withIntegrated DualReceivers and
Antennas
2xN Environment Simulation
Two Transmitter
BSE
45
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
Ideally, the sphere around the DUT would define a
perfect boundary condition that exactly reproduces
the desired field distribution inside the test region.
Practicality and physical limitations impose
restrictions that create a less than ideal environment
simulation.
The chosen number of antenna positions limits the
available range of “Real” propagation directions.
Splitting clusters across discrete antennas does not
produce true plane wave behavior in test region.
Results in an interference pattern with wave-like distribution
in center of test region. 07-08-2011 46
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
Discretization results in an interference pattern with
wave-like distribution in center of test region.
Quality depends on angular spacing and number of
antennas used to create interference pattern.
07-08-2011
Plane Wave Source at 15°
Y
(m)
X (m)
-0.002
0.002
-0.001
0
0.001
-0.125 0.125-0.05 0 0.05 0.1
-0.125
0.125
-0.1
-0.05
0
0.05
0.1
Simulated 15° Source using Plane Waves at 0° and 45°
Y
(m)
X (m)
-0.002
0.002
-0.001
0
0.001
-0.125 0.125-0.05 0 0.05 0.1
-0.125
0.125
-0.1
-0.05
0
0.05
0.1
47
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
Effect of angular resolution on simulated AOA.
07-08-2011
Plane Wave Illumination with 10 cm Wavelength
Ele
ctr
ic F
ield
Y
(m)
X (m)
-0.002
0.002
-0.001
0
0.001
-0.125 0.125-0.1 -0.05 0 0.05 0.1
-0.125
0.125
-0.1
-0.075
-0.05
-0.025
0
0.025
0.05
0.075
0.1
48
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
Effect of angular resolution on simulated AOA.
07-08-2011
Coherence Region for Antennas at 10° Spacing with 10 cm Wavelength
Ele
ctr
ic F
ield
Y
(m)
X (m)
-0.002
0.002
-0.001
0
0.001
-0.125 0.125-0.1 -0.05 0 0.05 0.1
-0.125
0.125
-0.1
-0.075
-0.05
-0.025
0
0.025
0.05
0.075
0.1
49
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
Effect of angular resolution on simulated AOA.
07-08-2011
Coherence Region for Antennas at 15° Spacing with 10 cm Wavelength
Ele
ctr
ic F
ield
Y
(m)
X (m)
-0.002
0.002
-0.001
0
0.001
-0.125 0.125-0.1 -0.05 0 0.05 0.1
-0.125
0.125
-0.1
-0.075
-0.05
-0.025
0
0.025
0.05
0.075
0.1
50
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
Effect of angular resolution on simulated AOA.
07-08-2011
Coherence Region for Antennas at 20° Spacing with 10 cm Wavelength
Ele
ctr
ic F
ield
Y
(m)
X (m)
-0.002
0.002
-0.001
0
0.001
-0.125 0.125-0.1 -0.05 0 0.05 0.1
-0.125
0.125
-0.1
-0.075
-0.05
-0.025
0
0.025
0.05
0.075
0.1
51
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
Effect of angular resolution on simulated AOA.
07-08-2011
Coherence Region for Antennas at 30° Spacing with 10 cm Wavelength
Ele
ctr
ic F
ield
Y
(m)
X (m)
-0.002
0.002
-0.001
0
0.001
-0.125 0.125-0.1 -0.05 0 0.05 0.1
-0.125
0.125
-0.1
-0.075
-0.05
-0.025
0
0.025
0.05
0.075
0.1
52
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
Effect of angular resolution on simulated AOA.
07-08-2011
Coherence Region for Antennas at 45° Spacing with 10 cm Wavelength
Ele
ctr
ic F
ield
Y
(m)
X (m)
-0.002
0.002
-0.001
0
0.001
-0.125 0.125-0.1 -0.05 0 0.05 0.1
-0.125
0.125
-0.1
-0.075
-0.05
-0.025
0
0.025
0.05
0.075
0.1
53
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
Effect of angular resolution on simulated AOA.
07-08-2011
Coherence Region for Antennas at 60° Spacing with 10 cm Wavelength
Ele
ctr
ic F
ield
Y
(m)
X (m)
-0.002
0.002
-0.001
0
0.001
-0.125 0.125-0.1 -0.05 0 0.05 0.1
-0.125
0.125
-0.1
-0.075
-0.05
-0.025
0
0.025
0.05
0.075
0.1
54
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
A perfect spherical boundary condition produces
perfect spherical symmetry.
07-08-2011 55 E
lec
tric
Fie
ld
(V/m
)
Y
(m)
X (m)
0
0.00011
1e-05
2e-05
3e-05
4e-05
5e-05
6e-05
7e-05
8e-05
9e-05
0.0001
-0.5 0.5-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
-0.5
0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
Copyright 2011, ETS-Lindgren, LP
Using only eight antennas at 45° spacing produces a
uniform test volume that’s only about a wavelength.
Ele
ctr
ic F
ield
(V
/m)
Y
(m)
X (m)
0
3.5e-05
2e-06
4e-06
6e-06
8e-06
1e-05
1.2e-05
1.4e-05
1.6e-05
1.8e-05
2e-05
2.2e-05
2.4e-05
2.6e-05
2.8e-05
3e-05
3.2e-05
-0.5 0.5-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
-0.5
0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
Spatial Environment Simulation
07-08-2011 56
Copyright 2011, ETS-Lindgren, LP
Using 24 antennas at 15° spacing produces a much
larger uniform test volume.
Ele
ctr
ic F
ield
(V
/m)
Y
(m)
X (m)
0
6e-05
1e-05
2e-05
3e-05
4e-05
5e-05
-0.5 0.5-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
-0.5
0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
Spatial Environment Simulation
07-08-2011 57
Copyright 2011, ETS-Lindgren, LP
Spatial Environment Simulation
Radial fall-off from traditional antennas in close
proximity to DUT does not behave like reflections
from distant objects (i.e. non-plane-wave behavior).
07-08-2011
Relative Signal Strength for Point Source at 1.0 m Distance
Re
lati
ve
Po
we
r (
dB
)
Y
(m)
X (m)
-2.5
2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
-0.25 0.25-0.2 -0.1 0 0.1 0.2
-0.25
0.25
-0.2
-0.1
0
0.1
0.2
Relative Signal Strength for Point Source at 3.0 m Distance
Re
lati
ve
Po
we
r (
dB
)
Y
(m)
X (m)
-2.5
2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
-0.25 0.25-0.2 -0.1 0 0.1 0.2
-0.25
0.25
-0.2
-0.1
0
0.1
0.2
58
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
A typical RF channel emulator consists of a number
of VSA receivers and VSG transmitters connected to
a DSP modeling core that introduces delay spreads,
fading, etc. at baseband.
07-08-2011 59
Receiver(VSA)
Transmitter(VSG)
DSPModeling
Core
Receiver(VSA)
Transmitter(VSG)
Receiver(VSA)
Transmitter(VSG)
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
The ideal channel emulator routes multiple inputs to
multiple outputs after applying appropriate modeled
delay spreads, fading, etc.
07-08-2011 60
Transmitter 1
Receiver1
Transmitter2
Receiver2
ChannelEmulation
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
In a real system, there are external path losses that
much be accounted for.
For an OTA system, this includes cable losses,
antenna gains, and range path losses.
External amplifiers are also typically required
07-08-2011 61
ChannelEmulator
Receiver1
Receiver2
Transmitter 1
Transmitter2
Total Emulated Channel
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
Channel emulators typically have internal gain control
for addressing relative offsets of inputs and outputs.
Not necessarily capable of removing all external path loss.
07-08-2011 62
ChannelEmulator
Receiver1
Receiver2
Transmitter 1
Transmitter2
Total Emulated Channel
Net Input Path Loss Net Output Path Loss
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
For input calibration, the requirement is that
G1 1 + G1 2 = G2 1 + G2 2 = GX 1 + GX 2
so that PA = PB = PX, when PTX is applied to each
input cable.
07-08-2011 63
Channel Emulator
Receiver1
Receiver2
Transmitter 1
Transmitter2
Total Emulated Channel
Net Input Path Loss Net Output Path Loss
A
B
C
D
G1 1 G1 2
G2 1 G2 2
G1 3 G1 4
G2 3 G2 4
GA-C
GB-D
GB-C
GA-D
Channel Gain
IN1
IN2
OUT1
OUT2
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
Similarly, for output calibration, requirement is that
G1 3 + G1 4 = G2 3 + G2 4 = GX 3 + GX 4
so that net losses to test volume are equal.
07-08-2011 64
Channel Emulator
Receiver1
Receiver2
Transmitter 1
Transmitter2
Total Emulated Channel
Net Input Path Loss Net Output Path Loss
A
B
C
D
G1 1 G1 2
G2 1 G2 2
G1 3 G1 4
G2 3 G2 4
GA-C
GB-D
GB-C
GA-D
Channel Gain
IN1
IN2
OUT1
OUT2
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
Simple channel model with four equivalent inputs
(red) and eight resulting outputs (blue).
07-08-2011 65
-35
-30
-25
-20
-15
-10
-5
0
1 2 3 4 5 6 7 8
Po
we
r (d
Bm
)
Port Number
Simple Channel Model
Input
Output
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
Result of input and output path losses applied to
channel model.
07-08-2011 66
-60
-50
-40
-30
-20
-10
0
1 2 3 4 5 6 7 8
Po
we
r (d
Bm
)
Port Number
Effect of Input and Output Cables on Channel Model
Input
Output
Net Output
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
Correcting for relative input losses (purple) flattens
inputs to channel model. Net output is still wrong.
07-08-2011 67
-60
-50
-40
-30
-20
-10
0
10
1 2 3 4 5 6 7 8
Po
we
r (d
Bm
)
Port Number
Applying Input Gain to Offset Input Cable Differences
Input
Input Gain (dB)
Channel Input
Output
Net Output
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
Correcting the relative output levels reproduces the
desired impact of clusters within the environment.
07-08-2011 68
-70
-60
-50
-40
-30
-20
-10
0
1 2 3 4 5 6 7 8
Po
we
r (d
Bm
)
Port Number
Applying Output Gain to Offset Output Cable Differences
Input
Channel Input
Channel Output
Output Gain (dB)
Output
Net Output
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
Magnitude correction critical for relative power levels.
Phase correction considered optional for faded
channels with modulated signals, where phase
relationship is randomized.
Phase correction is critical for:
Single tap/static models used in system validation (field
summation vs. power summation)
Realistic dual polarized environment simulation
Magnitude and phase corrections don’t correct for
group delay – time dependent behavior could still see
some impact from mismatched system path lengths.
07-08-2011 69
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
Finally, to predict the average power level in the
center of the test volume, the average path loss must
be calculated, including the loss (gain) of the channel
model.
This requires detailed knowledge of the channel
model gains, as well as assumptions about the
relative input levels of each input path for MIMO.
Application of a SIMO output calibration to a MIMO
model requires understanding/adjustment of source
power definition.
07-08-2011 70
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
where GChannel is the gain of a single channel path.
07-08-2011 71
Channel Emulator
Receiver1
Receiver2
Transmitter 1
Transmitter2
Total Emulated Channel
Net Input Path Loss Net Output Path Loss
A
B
C
D
G1 1 G1 2
G2 1 G2 2
G1 3 G1 4
G2 3 G2 4
GA-C
GB-D
GB-C
GA-D
Channel Gain
IN1
IN2
OUT1
OUT2
N
j
GGG
iiijjjiChannelGGg
1
214310log10
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
However, when properly calibrated
and likewise
so that
which can be simplified to:
07-08-2011 72
N
j
gG
inputioutputjiChannelgg
1
10log10
413143 GGGGg jjoutput
21 iiinput GGg
N
j
G
outputinputijiChannelggg
1
10log10
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
This simplification shows that both the input and
output gain of the system can be easily altered to
address output levels and modulation headroom of
the source, and to vary total path loss in the system.
Such changes must be accounted for in determining the
power in the test volume.
When changing channel models, the total channel
model gain must be recalculated.
Changing the number of active inputs and outputs
also alters the gain.
07-08-2011 73
Copyright 2011, ETS-Lindgren, LP
Calibrating the System
When evaluating the gain of a MIMO system where
the same power, PTX, is applied to each input cable,
the total gain to the test volume can be given by:
Note that this sum includes the array gain of the
multiple transmitters. For total power gain,
07-08-2011 74
M
i
g
totalig
1
10log10
M
i
g
averagei
Mg
1
101
log10
Copyright 2011, ETS-Lindgren, LP
System Validation
A wide range of tests are possible to evaluate:
Chamber/RF system quality
Channel emulation quality
Calibration quality
Combined system performance
Many tests are more interesting for research
purposes rather than system validation
It’s important to separate out tests that provide useful
system information vs. component level performance.
E.g. correlation or field distribution vs. Doppler spread
07-08-2011 75
Copyright 2011, ETS-Lindgren, LP
System Validation
Chamber and antenna system quality can be
evaluated using a modified ripple test.
Goal is to evaluate peak ripple of the field distribution
rather than integrated power quantity.
Ideally evaluate each antenna in array separately.
Implies reduced volumetric test to minimize test time.
Depending on implementation, ripple from support
structure could easily swamp chamber/array effects.
07-08-2011 76
Copyright 2011, ETS-Lindgren, LP
System Validation
Channel emulation/channel model need to be
evaluated for proper implementation of model and
proper operation.
Tests may evaluate
PDP
Doppler spread
AOA/AS distribution
Many tests can probably be done conducted.
May be considered product validation rather than on-
site system validation test.
07-08-2011 77
Copyright 2011, ETS-Lindgren, LP
System Validation
Calibration validation implies verifying proper
measurement and application of path loss
calibrations/corrections.
Tricky to do without just duplicating calibration using
different test equipment.
Use of same cables/equipment in calibration vs. validation.
Ideally measure average power of individual faded
channel models using modulated source.
Evaluate total power in center of test volume compared to
source power from BSE.
Power meter sensor on a sleeve dipole.
07-08-2011 78
Copyright 2011, ETS-Lindgren, LP
System Validation
A re-configurable ETS-Lindgren AMS-8700 MIMO
OTA system with 16 dual polarized antennas and two
8-output channel emulators was evaluated.
07-08-2011 79
Copyright 2011, ETS-Lindgren, LP
A linear positioner and turntable were used to map a
1 m diameter disc in the center of the test volume at
1 cm by 1 degree (0.87 cm at edge) resolution.
System Validation
07-08-2011 80
Copyright 2011, ETS-Lindgren, LP
System Validation
Spatial Field Mapping is used to compare the
measured environment to a theoretical model.
07-08-2011 81
Calculated Far-field Field Structure, 45 Degree Spacing
Ele
ctr
ic F
ield
(V
/m)
Y
(m)
X (m)
0
3.2e-05
1.1e-06
2.2e-06
3.3e-06
4.4e-06
5.5e-06
6.6e-06
7.7e-06
8.8e-06
9.9e-06
1.1e-05
1.21e-05
1.32e-05
1.43e-05
1.54e-05
1.65e-05
1.76e-05
1.87e-05
1.98e-05
2.09e-05
2.2e-05
2.31e-05
2.42e-05
2.53e-05
2.64e-05
2.75e-05
2.86e-05
2.97e-05
3.08e-05
-0.5 0.5-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
-0.5
0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
Calculated Far-Field Field Structure with High Resolution Boundary Condition
Ele
ctr
ic F
ield
(V
/m)
Y
(m)
X (m)
0
7.83e-05
2.7e-06
5.4e-06
8.1e-06
1.08e-05
1.35e-05
1.62e-05
1.89e-05
2.16e-05
2.43e-05
2.7e-05
2.97e-05
3.24e-05
3.51e-05
3.78e-05
4.05e-05
4.32e-05
4.59e-05
4.86e-05
5.13e-05
5.4e-05
5.67e-05
5.94e-05
6.21e-05
6.48e-05
6.75e-05
7.02e-05
7.29e-05
7.56e-05
-0.5 0.5-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
-0.5
0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
Ideal Free-Space or Continuous Boundary Condition Interference Pattern from Eight Evenly Spaced Plane Waves
Copyright 2011, ETS-Lindgren, LP
Measured Field Structure, 45 Degree Spacing, Vertically Polarized
Ma
gn
itu
de
X
(cm
)
Angle (°)
0
0.0192
0.0007
0.0014
0.0021
0.0028
0.0035
0.0042
0.0049
0.0056
0.0063
0.007
0.0077
0.0084
0.0091
0.0098
0.0105
0.0112
0.0119
0.0126
0.0133
0.014
0.0147
0.0154
0.0161
0.0168
0.0175
0.0182
Scale: 5/div
Min: 0
Max: 50
0
180
30
210
60
240
90270
120
300
150
330
System Validation
Measurement shows differences from plane wave
interference pattern.
07-08-2011 82
Calculated Far-field Field Structure, 45 Degree Spacing
Ele
ctr
ic F
ield
(V
/m)
Y
(m)
X (m)
0
3.2e-05
1.1e-06
2.2e-06
3.3e-06
4.4e-06
5.5e-06
6.6e-06
7.7e-06
8.8e-06
9.9e-06
1.1e-05
1.21e-05
1.32e-05
1.43e-05
1.54e-05
1.65e-05
1.76e-05
1.87e-05
1.98e-05
2.09e-05
2.2e-05
2.31e-05
2.42e-05
2.53e-05
2.64e-05
2.75e-05
2.86e-05
2.97e-05
3.08e-05
-0.5 0.5-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
-0.5
0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
Measured Interference Pattern from Eight Antennas, r = 2 m Interference Pattern from Eight Evenly Spaced Plane Waves
Copyright 2011, ETS-Lindgren, LP
Calculated Field Structure at 2.0 m Radius, 45 Degree Spacing
Ele
ctr
ic F
ield
(V
/m)
Y
(m)
X (m)
0
0.016
0.0006
0.0012
0.0018
0.0024
0.003
0.0036
0.0042
0.0048
0.0054
0.006
0.0066
0.0072
0.0078
0.0084
0.009
0.0096
0.0102
0.0108
0.0114
0.012
0.0126
0.0132
0.0138
0.0144
0.015
-0.5 0.5-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
-0.5
0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
Measured Field Structure, 45 Degree Spacing, Vertically Polarized
Ma
gn
itu
de
X
(cm
)
Angle (°)
0
0.0192
0.0007
0.0014
0.0021
0.0028
0.0035
0.0042
0.0049
0.0056
0.0063
0.007
0.0077
0.0084
0.0091
0.0098
0.0105
0.0112
0.0119
0.0126
0.0133
0.014
0.0147
0.0154
0.0161
0.0168
0.0175
0.0182
Scale: 5/div
Min: 0
Max: 50
0
180
30
210
60
240
90270
120
300
150
330
System Validation
Modeling a 2 m range length instead of a plane wave
shows excellent correlation.
07-08-2011 83
Measured Interference Pattern from Eight Antennas, r = 2 m Calculated Interference Pattern from Eight Antennas , r = 2 m
Copyright 2011, ETS-Lindgren, LP
Comparing a single cut through the test volume.
System Validation
07-08-2011 84
Comparison of Measured Field Structure to Theory for 8 Antenna Array (45° Spacing)
Re
lati
ve
Fie
ld L
ev
el
X (cm)
-50 50-40 -30 -20 -10 0 10 20 30 40
0
1
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Measured Field Theoretical Field Ideal Free-Space Field
Copyright 2011, ETS-Lindgren, LP
Measured Field Structure, 22.5 Degree Spacing
Ma
gn
itu
de
X
(cm
)
Angle (°)
0
7.04
0.25
0.5
0.75
1
1.25
1.5
1.75
2
2.25
2.5
2.75
3
3.25
3.5
3.75
4
4.25
4.5
4.75
5
5.25
5.5
5.75
6
6.25
6.5
6.75
Scale: 5/div
Min: 0
Max: 50
0
180
30
210
60
240
90270
120
300
150
330
Increasing the resolution of the boundary condition
from 8 to 16 antennas increases usable test volume.
Calculated Field Structure at 2.0 m Radius, 22.5 Degree Spacing
Ele
ctr
ic F
ield
(V
/m)
Y
(m)
X (m)
0
0.0226
0.0008
0.0016
0.0024
0.0032
0.004
0.0048
0.0056
0.0064
0.0072
0.008
0.0088
0.0096
0.0104
0.0112
0.012
0.0128
0.0136
0.0144
0.0152
0.016
0.0168
0.0176
0.0184
0.0192
0.02
0.0208
0.0216
-0.5 0.5-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
-0.5
0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
System Validation
07-08-2011 85
Measured Interference Pattern from 16 Antennas, r = 2 m Calculated Interference Pattern from 16 Antennas , r = 2 m
Copyright 2011, ETS-Lindgren, LP
Comparing a single cut through the test volume.
System Validation
07-08-2011 86
Comparison of Measured Field Structure to Theory for 16 Antenna Array (22.5° Spacing)
Re
lati
ve
Fie
ld L
ev
el
X (cm)
-50 50-40 -30 -20 -10 0 10 20 30 40
0
1
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Measured Field Theoretical Field Ideal Free-Space Field
Copyright 2011, ETS-Lindgren, LP
System Validation
Spatial Correlation evaluates field structure and
channel model behavior.
Move one dipole through test volume and evaluate
correlation vs. separation.
Requires replay of channel model at each position.
Single cluster behavior most straightforward to evaluate.
07-08-2011 87
SingleCluster
1 m slice through test volume on 1 cm steps
Copyright 2011, ETS-Lindgren, LP
Spatial Correlation evaluates RF system + emulation.
System Validation
07-08-2011 88
Spatial Correlation for 8 Antenna (45° Spacing) Configuration
Co
rre
lati
on
X (cm)
-50 50-40 -30 -20 -10 0 10 20 30 40
0.2
1
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Copyright 2011, ETS-Lindgren, LP
Single cluster model produces known correlation.
System Validation
07-08-2011 89
Spatial Correlation for 16 Antenna (22.5° Spacing) Configuration
Co
rre
lati
on
X (cm)
-50 50-40 -30 -20 -10 0 10 20 30 40
0
1
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Copyright 2011, ETS-Lindgren, LP
Comparing to theory for the same channel model. Spatial Correlation for 16 Antenna (22.5° Spacing) Configuration
Co
rre
lati
on
X (cm)
-42 42-30 -20 -10 0 10 20 30
0
1
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Measured Correlation Model Correlation Ideal Free-Space Correlation
System Validation
07-08-2011 90
Copyright 2011, ETS-Lindgren, LP
Both tests show similar system performance results. Comparison of Spatial Correlation and Field Structure for 22.5° Resolution Configuration
X (cm)
-50 50-40 -30 -20 -10 0 10 20 30 40
0
1
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Spatial Correlation Field Structure Free-Space Field Structure
System Validation
07-08-2011 91
Copyright 2011, ETS-Lindgren, LP
When field deviates from ideal, so does correlation. Comparison of Spatial Correlation and Field Structure for 22.5° Resolution Configuration
X (cm)
-50 50-40 -30 -20 -10 0 10 20 30 40
0
1
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Spatial Correlation Field Structure Free-Space Field Structure
System Validation
07-08-2011 92
Copyright 2011, ETS-Lindgren, LP
System Validation
Channel Model Pattern – Using a narrow beam
antenna, the generated angular spread profile can be
mapped.
Works well as a quick verification for single cluster
Not as agile for more complicated models
Antenna-by-Antenna Mapping – Measure channel
frequency response of each antenna across
statistically large set of IR steps and TD transform.
Evaluates PDP and AS of channel model.
Can be numerically compared to summation of all antennas
active (requires valid phase calibration).
07-08-2011 93
Copyright 2011, ETS-Lindgren, LP
System Validation
For dual polarized system, XPR must be evaluated.
A precision sleeve dipole and loop can be used to
measure each polarization separately, but has
disadvantages.
Correlate calibration of different elements
Symmetry of loops very narrow band
A directional horn rotated through polarization angles
does well for an antenna-by-antenna evaluation of
the XPR.
Three isotropic orientations of a sleeve dipole
provides a better way of evaluating XPR of a model.
07-08-2011 94
Copyright 2011, ETS-Lindgren, LP
Throughput Measurement Results
Unlike traditional TRP/TIS tests, which provide edge
of link performance metrics, MIMO performance is all
about high bandwidth with large SNRs.
The corresponding metric for measuring bandwidth is
throughput, and the equivalent evaluation would be to
determine when the throughput begins to fall off.
Initial tests were performed with 802.11n devices
supporting 2x2 MIMO, to prove the capabilities of the
system and methodology.
Now that LTE communication testers are available, it
is possible to show the first LTE MIMO OTA results.
07-08-2011 95
Copyright 2011, ETS-Lindgren, LP
Wi-Fi Throughput Measurement Results
A re-configurable MIMO OTA system was installed in
ETS-Lindgren’s Cedar Park facility for research and
development of test requirements.
Eight dual polarized antenna elements were mounted
on adjustable fixtures and arranged around a DUT
positioning turntable.
The Elektrobit Propsim F8 channel emulator was
used to provide the spatial channel emulation
required for the OTA environment simulation.
Eight 30 dB gain power amplifiers drive eight vertical
antenna elements.
07-08-2011 96
Copyright 2011, ETS-Lindgren, LP
Wi-Fi Throughput Measurement Results
An 802.11n 2x2 MIMO Wireless Router with
removable, adjustable external antennas was chosen
as the DUT.
A matching NIC was used as the downlink source.
07-08-2011
Directly cabled conducted tests
were used to verify MIMO
operation with appropriately
higher throughput compared to
SIMO/SISO cabled
configurations.
97
Copyright 2011, ETS-Lindgren, LP
Wi-Fi Throughput Measurement Results
Conducted tests of throughput vs. attenuation were
performed with Propsim F8 using circulators/isolators
to provide a single return uplink.
Direct single tap models were used to replicate
cabled results.
Several 2x2 MIMO models suitable for OTA testing
were evaluated to determine typical MIMO
performance.
Modified SCME Urban Micro w/ 3 km/h fading & zero delay
spread.
Modified TGn-C w/ AOD/AOA based on SCME
Modified TGn-C w/ low TX correlation (10 wavelength sep.) 07-08-2011 98
Copyright 2011, ETS-Lindgren, LP
Modified TGn-C uses taps
from TGn-C model with
AOA/AOD from SCME
Urban Micro model.
07-08-2011
Wi-Fi Throughput Measurement Results
99
Copyright 2011, ETS-Lindgren, LP
Wi-Fi Throughput Measurement Results
Using standard 20 MHz 802.11 channels, conducted
tests show maximum SIMO throughput around 25
MBPS, with MIMO performance around 40-45 MBPS
with typical channel models.
Initial OTA tests with stock antennas using low
correlation TGn-C OTA model produces similar
results but shows angular dependence of MIMO
performance while SIMO (diversity) performance
remains uniform.
07-08-2011 100
Copyright 2011, ETS-Lindgren, LP
Wi-Fi Throughput Measurement Results
07-08-2011
Throughput vs. Total Path Loss
Th
rou
gh
pu
t (
Mb
ps
)
Attenuation (dB)
30 8035 40 45 50 55 60 65 70 75
10
50
15
20
25
30
35
40
45
0° 30° 60° 90° 120° 150° 180° 210° 240°
270° 300° 330° 360° SIMO TX1 SIMO TX2
101
Copyright 2011, ETS-Lindgren, LP
Wi-Fi Throughput Measurement Results
07-08-2011
Throughput vs. Total Path Loss
Th
rou
gh
pu
t (
Mb
ps
)
Attenuation (dB)
30 8035 40 45 50 55 60 65 70 75
10
50
15
20
25
30
35
40
45
0° 30° 60° 90° 120° 150° 180° 210° 240°
270° 300° 330° 360° SIMO TX1 SIMO TX2
MIMO
Operating
Region
102
Copyright 2011, ETS-Lindgren, LP
Wi-Fi Throughput Measurement Results
07-08-2011
Throughput vs. Total Path Loss
Th
rou
gh
pu
t (
Mb
ps
)
Attenuation (dB)
30 8035 40 45 50 55 60 65 70 75
10
50
15
20
25
30
35
40
45
0° 30° 60° 90° 120° 150° 180° 210° 240°
270° 300° 330° 360° SIMO TX1 SIMO TX2
SIMO
Operation
103
Copyright 2011, ETS-Lindgren, LP
Wi-Fi Throughput Measurement Results
07-08-2011
Throughput vs. Total Path Loss
Th
rou
gh
pu
t (
Mb
ps
)
Attenuation (dB)
30 8035 40 45 50 55 60 65 70 75
10
50
15
20
25
30
35
40
45
0° 30° 60° 90° 120° 150° 180° 210° 240°
270° 300° 330° 360° SIMO TX1 SIMO TX2
TX
Beam- Forming
Region
104
Copyright 2011, ETS-Lindgren, LP
Wi-Fi Throughput Measurement Results
07-08-2011
Attenuation at 35 Mbps
Att
en
ua
tio
n
(dB
)
Angle (°)
Scale: 2/div
Min: 36
Max: 56
0
180
30
210
60
240
90 270
120
300
150
330
105
Copyright 2011, ETS-Lindgren, LP
Wi-Fi Throughput Measurement Results
07-08-2011
Attenuation at 30 Mbps
Att
en
ua
tio
n
(dB
)
Angle (°)
Scale: 1/div
Min: 50
Max: 60
0
180
30
210
60
240
90 270
120
300
150
330
106
Copyright 2011, ETS-Lindgren, LP
Wi-Fi Throughput Measurement Results
07-08-2011
Attenuation at SIMO Data Rates
Att
en
ua
tio
n
(dB
)
Angle (°)
Scale: 2/div
Min: 60
Max: 78
0
180
30
210
60
240
90 270
120
300
150
330 10.00 Mbps
15.00 Mbps
20.00 Mbps
107
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LTE Throughput Measurement Results
LTE USB modem on test pedestal in middle of chamber
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LTE Throughput Measurement Results
Channel Model Definitions
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6.2.1 - SCME Urban Micro Cluster Map
Rela
tiv
ePow
er(dB)
Angle of Arrival (°)
Scale: 1/div
Min: -9
Max: 1
0
180
30
210
60
240
90 270
120
300
150
330
6.2.2 - Modified SCME Urban Micro Cluster Map
Rela
tiv
ePow
er(dB)
Angle of Arrival (°)
Scale: 1/div
Min: -9
Max: 1
0
180
30
210
60
240
90 270
120
300
150
330
6.2.3 - SCME Urban Macro Cluster Map
Rela
tiv
ePow
er(dB)
Angle of Arrival (°)
Scale: 2/div
Min: -14
Max: 2
0
180
30
210
60
240
90 270
120
300
150
330
6.2.4 - Modified WINNER II Cluster Map
Rela
tiv
ePow
er(dB)
Angle of Arrival (°)
Scale: 5/div
Min: -25
Max: 5
0
180
30
210
60
240
90 270
120
300
150
330
Copyright 2011, ETS-Lindgren, LP
LTE Throughput Measurement Results
07-08-2011 110
Throughput vs. Power vs. Orientation, SCME Urban Micro, 16 QAM LTE DUT
Th
rou
gh
pu
t (
Mb
ps
)
Power (dBm)
-79 -60-78 -76 -74 -72 -70 -68 -66 -64 -62
8
24
10
12
14
16
18
20
22
0° 45° 90° 135° 180° 225° 270° 315°
Copyright 2011, ETS-Lindgren, LP
LTE Throughput Measurement Results
07-08-2011 111
Average Throughput vs. Power, 16 QAM LTE DUT
Th
rou
gh
pu
t (
Mb
ps
)
Power (dBm)
-78 -64-76 -74 -72 -70 -68 -66
10
24
12
14
16
18
20
22
6.2.1 - SCME Urban Micro 6.2.2 - Modified SCME Urban Micro 6.2.3 - SCME Urban Macro
6.2.4 - Modified WINNER2
Copyright 2011, ETS-Lindgren, LP
Power at 20 Mbps Throughput, 16 QAM LTE DUT
Po
we
r (
dB
m)
Angle (°)
Scale: 1/div
Min: -79
Max: -71
0
180
30
210
60
240
90 270
120
300
150
330
6.2.1 - SCME Urban Micro, Avg = -74.0 dBm 6.2.2 - Modified SCME Urban Micro, Avg = -74.4 dBm
6.2.3 - SCME Urban Macro, Avg = -74.5 dBm 6.2.4 - Modified WINNER2, Avg = -73.1 dBm
LTE Throughput Measurement Results
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20 Mbps Throughput Sensitivity Pattern, 16 QAM LTE DUT
Po
we
r (
-dB
m)
Angle (°)
Scale: 1/div
Min: 71
Max: 79
0
180
30
210
60
240
90 270
120
300
150
330
6.2.1 - SCME Urban Micro, Avg = -74.0 dBm 6.2.2 - Modified SCME Urban Micro, Avg = -74.4 dBm
6.2.3 - SCME Urban Macro, Avg = -74.5 dBm 6.2.4 - Modified WINNER2, Avg = -73.1 dBm
LTE Throughput Measurement Results
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Throughput vs. Power vs. Orientation, SCME Urban Micro, 64 QAM LTE DUT
Th
rou
gh
pu
t (
Mb
ps
)
Power (dBm)
-68 -56-66 -64 -62 -60 -58
15
65
20
25
30
35
40
45
50
55
60
0° 45° 90° 135° 180° 225° 270° 315°
LTE Throughput Measurement Results
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Average Throughput vs. Power, 64 QAM LTE DUT
Th
rou
gh
pu
t (
Mb
ps
)
Power (dBm)
-66 -56-65 -64 -63 -62 -61 -60 -59 -58 -57
20
60
25
30
35
40
45
50
55
6.2.1 - SCME Urban Micro 6.2.2 - Modified SCME Urban Micro 6.2.3 - SCME Urban Macro
6.2.4 - Modified WINNER2
LTE Throughput Measurement Results
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40 Mbps Throughput Sensitivity Pattern, 64 QAM LTE DUT
Po
we
r (
-dB
m)
Angle (°)
Scale: 1/div
Min: 56
Max: 67
0
180
30
210
60
240
90 270
120
300
150
330
6.2.1 - SCME Urban Micro, Avg = -61.1 dBm 6.2.2 - Modified SCME Urban Micro, Avg = -61.0 dBm
6.2.3 - SCME Urban Macro, Avg = -58.8 dBm 6.2.4 - Modified WINNER2, Avg = -60.6 dBm
LTE Throughput Measurement Results
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Metrics
The data acquired thus far can be evaluated
in a number of ways to define different metrics
for MIMO performance.
Removing the position axis produces average
throughput vs. power (attenuation) curves.
This could be done as a post processing step,
but if position (pattern) information is not
needed, average throughput performance can
be determined by moving DUT continuously
through simulated environment. 07-08-2011 117
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Metrics
07-08-2011 118
Average Azimuthal Throughput vs. Total Path Loss
Th
rou
gh
pu
t (M
bp
s)
Attenuation (dB)
30 7535 40 45 50 55 60 65 70
5
45
10
15
20
25
30
35
40
TGn-C Low Correlation TGn-C Normal Correlation
Copyright 2011, ETS-Lindgren, LP
Metrics
This test can be further reduced by choosing
to determine average throughput performance
at a given field level (no power level search).
E.g. At an attenuation value of 50 dB, this DUT
has an average throughput of 36 Mbps for the low
correlation TGn-C model and 30 Mbps for the
normal correlation TGn-C model.
This is similar to many conformance tests with
a simple pass/fail result, and assumes a
minimum expected network capability.
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Copyright 2011, ETS-Lindgren, LP
Metrics
By retaining angular information, or by
measuring throughput over short dwell times
as the DUT moves, peak throughput
performance can be determined.
This metric may have limited usefulness, but
does illustrate a slightly different reaction to
the two models.
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Copyright 2011, ETS-Lindgren, LP
Metrics
07-08-2011 121
Peak Azimuthal Throughput vs. Total Path Loss
Th
rou
gh
pu
t (M
bp
s)
Attenuation (dB)
30 7535 40 45 50 55 60 65 70
5
50
10
15
20
25
30
35
40
45
TGn-C Low Correlation TGn-C Normal Correlation
Copyright 2011, ETS-Lindgren, LP
Metrics
By retaining throughput vs. attenuation or
using a throughput vs. attenuation search
mode, one can define a “MIMO Sensitivity”
where throughput falls below a certain target.
This can be defined in two ways, with varying
test time requirements.
Average power required to produce the target
throughput at each angle (integrated TIS pattern)
Power required to produce desired average
throughput as device is rotated through all angles
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Copyright 2011, ETS-Lindgren, LP
Metrics
07-08-2011 123
(Linear) Average Attenuation vs. Throughput
Av
era
ge
Att
en
ua
tio
n (
dB
)
Throughput (Mbps)
10 3515 20 25 30
40
80
45
50
55
60
65
70
75
TGn-C Low Correlation TGn-C Normal Correlation
Copyright 2011, ETS-Lindgren, LP
Metrics
07-08-2011 124
Attenuation vs. Average Throughput
Att
en
ua
tio
n (
dB
)
Average Throughput (Mbps)
10 3515 20 25 30
40
80
45
50
55
60
65
70
75
TGn-C Low Correlation TGn-C Normal Correlation
Copyright 2011, ETS-Lindgren, LP
Metrics
While the statistics of these two metrics are
slightly different and provide slightly different
results, both provide considerably more
information on the DUT, offering an “edge of
MIMO link” performance indicator.
Such information can be used to rank
products and influence improvements, while
the previous pass/fail options only offer basic
acceptability criteria.
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Copyright 2011, ETS-Lindgren, LP
Conclusion
Extensive efforts are underway to standardize on a
next generation platform for wireless testing.
The ability to perform realistic RF environment
simulation and evaluate end user metrics in real-
world scenarios is an invaluable resource to wireless
technology developers.
Detailed calibration and validation methods are
required to ensure the validity of measured data.
While a throughput related metric is the logical
choice, the industry must still choose the desired
target metric (e.g. throughput sensitivity).
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Copyright 2011, ETS-Lindgren, LP
Thank You!
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