introduction to mimo ota environment simulation ... · introduction to mimo ota environment...

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


Wi-Fi and LTE Throughput Measurement Results

with the ETS-Lindgren AMS-8700 OTA

Environment Simulator

Metrics

Outline

07-08-2011 3


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


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


“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


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


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


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.


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


Po

we

r (

dB

m)

-80

-55

-75

-70

-65

-60

Y

Z

X

Azimuth = 104.6

Elevation = -25.1

Roll = -51.5


Po

we

r (

dB

m)

-85

-55

-80

-75

-70

-65

-60

Y

Z

X

Azimuth = 104.6

Elevation = -25.1

Roll = -51.5


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.


07-08-2011 10

Y

Z

X

TRP


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.


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

(


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.


07-08-2011 12

Environment #1 Environment #2


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).


07-08-2011 13



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)



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



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



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



Each path has a different length (propagation delay).

07-08-2011 18

Transmitter

Receiver

B

A

C

D

A

B

C

D



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



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



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



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


Combining the cluster concept with the tap concept

produces realistic time domain profiles.


07-08-2011 23

Time

Sig

na

l S

tre

ng

th

Power Delay Profile

A

B

C

D

Taps


Now the modeled data looks a lot like real measured

time domain data acquired using a vector network

analyzer.


07-08-2011 24



Motion of the transmitter, receiver, or other objects

within the environment causes Doppler shift of the

frequency.

07-08-2011 25

Transmitter

Receiver



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

=+

=+


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.


07-08-2011 27


Spatial channel models for conducted testing also

apply assumed antenna patterns for the source and

receiver.


07-08-2011 28

2x2 Channel Emulation

Two Transmitter

BSE

Two Receiver

Radio

Simulated TransmitAntenna Patterns

Simulated ReflectionClusters

Simulated ReceiveAntenna Patterns


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:


07-08-2011 29


Platform Desensitization – interference from

platform components enters radio through

attached antennas.


07-08-2011 30

GPS

WCDMA

Baseband

ProcessorWi-Fi

Backlight

Bluetooth

Antenna Another

Antenna

And Yet

Another

Antenna

One More

Antenna


Near Field Influences – including platform

structure, head, hands, body, table top, etc.


07-08-2011 31


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.


07-08-2011 32


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.


07-08-2011 33



MIMOTransmitter MIMO

Receiver



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.



MIMOTransmitter MIMO

Receiver

07-08-2011 34



Example: Typical Multi-Path Power Delay Profile

from a Real World Environment

07-08-2011 35



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


A spatial channel emulator (a channel emulator with

modified channel models) simulates the desired

external environment between BSE and DUT.


07-08-2011 37

DUT

MIMOTester

SpatialChannelEmulator


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.


07-08-2011 38


Spatial channel models include clusters of scatterers

with each tap having an angular spread as well as a

delay spread.


07-08-2011 39


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


Converting a conducted channel model to an OTA

channel model:

Conducted model simulates TX and RX antennas.


07-08-2011


Two Transmitter

BSE

Two Receiver

Radio

Simulated TransmitAntenna Patterns

Simulated ReflectionClusters

Simulated ReceiveAntenna Patterns

41


Conducted channel model:

Ray paths from reflections in simulated environment are

collected at each simulated receive antenna.


07-08-2011


Two Transmitter

BSE

Two Receiver

Radio

Simulated Ray PathsBetween TX and RX Antennas

42



channel model:

Clusters produced different angles of arrival (AOA)


07-08-2011


Two Transmitter

BSE

Two Receiver

Radio

Directions of Received Signals(Angles of Arrival)

43



channel model:

Grouping AOAs, we can remove virtual RX antennas.


07-08-2011


Two Transmitter

BSE

Two Receiver

Radio

Region around Simulated DUT

44


OTA channel model:

2xN channel emulator used to feed N antennas for AOA

simulation around DUT with real antennas.


07-08-2011

DUT withIntegrated DualReceivers and

Antennas

2xN Environment Simulation

Two Transmitter

BSE

45



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



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



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




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




07-08-2011


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




07-08-2011


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




07-08-2011


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




07-08-2011


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




07-08-2011


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



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


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


07-08-2011 56


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


07-08-2011 57



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



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)



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



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



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


Net Input Path Loss Net Output Path Loss



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



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



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



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



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



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



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



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



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



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



where GChannel is the gain of a single channel path.

07-08-2011 71

Channel Emulator

Receiver1

Receiver2

Transmitter 1

Transmitter2



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



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



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



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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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



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



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


Modified TGn-C uses taps

from TGn-C model with

AOA/AOD from SCME

Urban Micro model.

07-08-2011


99



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



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



07-08-2011


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



07-08-2011


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



07-08-2011


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



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



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



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


LTE Throughput Measurement Results

LTE USB modem on test pedestal in middle of chamber

07-08-2011 108



Channel Model Definitions

07-08-2011 109

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)


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)


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)


Scale: 5/div

Min: -25

Max: 5

0

180

30

210

60

240

90 270

120

300

150

330



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°



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


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


07-08-2011 112


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




07-08-2011 113


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°


07-08-2011 114


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


07-08-2011 115


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




07-08-2011 116


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


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


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.

07-08-2011 119


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.

07-08-2011 120


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



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

07-08-2011 122


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



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



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.

07-08-2011 125


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).

07-08-2011 126


Thank You!

07-08-2011 127

introduction to mimo ota environment simulation ... · introduction to mimo ota environment...

Documents