Concepts of 3GPP LTE 9 Oct 2007 Page 1 MIMO MIA! …or the different faces of MIMO! Taking LTE MIMO from Standards to Starbucks Moray Rumney 30 th April

Concepts of 3GPP LTE9 Oct 2007Page 1Page 1Page 1Page 1

MIMO MIA!…or the different faces of MIMO!

Taking LTE MIMO from Standards to Starbucks

Moray Rumney 30th April 2009

Concepts of 3GPP LTE9 Oct 2007Page 2Page 2Page 2

Agenda

• Just a little MIMO theory• MIMO in the LTE air interface• LTE MIMO conformance testing• Testing MIMO in the real world



Concepts of 3GPP LTE9 Oct 2007Page 3

Agilent LTE Book

www.agilent.com/find/ltebook

www.amazon.com In print April 16th

The first LTE book dedicated to design and measurement

30 Authors460 pages

Page 3




Book overview

Chapter 1 LTE Introduction

Chapter 2 Air Interface Concepts

Chapter 3 Physical Layer

Chapter 4 Upper Layer Signaling

Chapter 5 System Architecture Evolution

Chapter 6 Design and Verification Challenges

Chapter 7 Conformance Test

Chapter 8 Looking Towards 4G: LTE-Advanced




Agenda





Basic channel access modes

TransmitAntennas

ReceiveAntennas

SISO

The Radio Channel

MISO

Single Input Single Output

Multiple Input Single Output

(Transmit diversity)

ReceiveAntennas

TransmitAntennas

MIMO

The Radio Channel

SIMO

Single Input Multiple Output

(Receive diversity)

Multiple Input Multiple Output(Multiple data streams)




MIMO principles

• Transmitting multiple data streams in the same space and time used to be called interference!

• So how does MIMO work?1. MIMO capacity gains come from taking advantage of spatial

diversity in the radio channel2. Depending on channel conditions and noise levels, the rank

(number of simultaneous streams) can be varied3. The performance can be optimized using precoding

• These three MIMO principles can seem complex to understand particularly abstract mathematical descriptions

• But we intuitively already know these MIMO principles in the way they apply to our perception of audio

Page 7




Understanding MIMO spatial diversity through Audio - Single Stream (Mono)

Page 8



SISO SIMO MISO SIMO + MISO≠ MIMO

Note, the combination of SIMO and MISO further improves robustness but does not provide any MIMO capacity gain since there is only one stream of data

M MMM MM


Understanding MIMO spatial diversity through Audio - Dual Stream (Stereo)

Page 9



Interference! MIMO!

RL R

Interference!

RL

For MIMO to work:• Must have at least as many receivers as transmitted streams• Must have spatial separation at both transmit and receive antennas• More transmitters enables beamforming in addition to MIMO

RL

Interference!

L


Understanding MIMO precoding through Audio

• MIMO Precoding is a pre-emphasis technique used to improve the separation of the streams at the receiver due to unhelpful coupling in the channel

• In audio systems precoding is similar to stereo “balance”

• If the receiver is not positioned directly between the speakers the received streams will be at different levels

• Adjusting the balance at the transmitter can mitigate the problem

• Balancing requires feedback from the receiver to the transmitter

Page 10



RL

Not enough R


Understanding MIMO precoding through Audio

• The receiver could just amplify the right channel but in the presence of noise the corrected signal would degrade:

• Precoding the transmission as L, 5R optimizes signal recovery

Page 11



RL

L + NL, 0.2 R + NR

L + NL, R + 5*NR

5RL

L + NL, R + NR

Problem!

Solution!


Understanding MIMO Rank adaptation through Audio• In good radio conditions an FM stereo receiver will attempt to

decode both the left and right signals (streams)• When the noise gets too high the receiver switches to mono

and the quality improves although stereo is lost• This is the audio equivalent of rank adaptation where the

number of streams is reduced under poor conditions• Transmit matrix encoded FM stereo as L + R, L – R

• Receive (L + R) + N1, (L – R) + N2

• Since N1 and N2 are largely correlated, adding the two streams (maximum ratio combining) cancels most of the noise

Page 12




The role of channel correlation and noise in system performance• In a ideal 2x2 system the potential capacity gain is 2x• The actual gain depends on how easily the receiver can

descramble the simultaneous transmissions – this depends on the amount of unwanted correlation and noise

• In audio systems channel correlation and noise also affects perceived stereo performance

– Spaced living room speakers - lots of correlation degrades stereo, susceptible to external noise

– Open headphones – zero correlation, good stereo but still susceptible to noise

– Closed headphones – zero correlation, minimal noise

Page 13




So what makes a good channel for MIMO?

• A perfect MIMO channel islike the closed headphones: channels 2 and 3 don’t exist

• By simple observation it follows that R0 = T0 and R1 = T1

• This is the case that creates double the capacity

• But suppose we create a simple static channel like this:

• How do we know if it will provide capacity gain?

Page 14

1 0

0 1

Channel H

0.8 0.2

0.3 -0.9

Channel H



ch1

ch4

ch2

ch3

T0

T1

R0

R1


The MIMO challenge: Recovering the signal

• If all four channels are the same the original signal cannotbe recovered since R0 = R1

R0 = T0 + T1 and R1 = T0 + T1

• But put in a phase inversion e.g. on ch3 we get:

R0 = T0 + T1 and R1 = T1 – T0

thus T0 = (R0 - R1)/2 and T1 = (R0 + R1)/2

• The original signal is completely recovered even though the apparently unwanted ch2 and ch3 exist

Page 15

1 1

1 1

Channel H

1 1

-1 1

Channel H



ch1

ch4

ch2

ch3

T0

T1

R0

R1



• So is the earlier example good or bad for MIMO?

• We can recover the original signal• In fact any H matrix other than the unity matrix can be resolved PROVIDED there is no

external or internal noise!• So what kinds of channels are robust to noise?

Page 16

0.8 0.2

0.3 -0.9

Channel HR0 = 0.8 T0 + 0.3 T1

R1 = 0.2 T0 - 0.9 T1

T0 = 1.15 R0 + 0.39 R1

T1 = 0.26 R0 - 1.03 R1

Giving:





• The receiver can untangle the two signals because it knows the coupling coefficients, based on the reference signals, but reference estimation is susceptible to noise

• But pilot estimation is susceptible to noise• If the estimate is wrong the recovered signal is impaired

• Consider these equations for T0 from different channels:

• Errors in T0 recovery happen due to estimation errors in the coefficients or large coefficients amplifying noise N0 and N1

• It is possible to analyze the matrix H to predict the impact of noise on signal recovery

Page 17

T0 = 1.15 (R0 + N0) + 0.39 (R1 + N1)T0 = 27.3 (R0 + N0) + 16.5 (R1 + N1)




Condition Number Measures the short term MIMO channel performance

R0 = 0.8 T0 + 0.3 T1

R1 = -0.9 T1 + 0.2 T0

0.8 0.2

0.3 -0.9

Channel H

0.8 0.3

0.2 -0.9

Channel HT

0.73 -0.11

-0.11 0.85

Channel HTH Eigenvalues

0.914

0.666

Singular values

0.957

0.815

К = Condition number0.957 / 0.815 = 1.17

The condition number is the ratio of the singular values of HHT

The dB value of К approximates the increase in SNR required to recover the signal


Moray Rumney 30th April 2009Page 18Page 18Page 18


MIMO needs better SNR than SISOHigh К increases SNR requirements furtherThe extra SNR required to achieve the same recovered signal quality as SISO rises as the condition number rises




Ped. A Channel Condition Number vs. Freq.

Page 20

Condition number and channel response across 10 MHz, 10 ms

0 dB




Impact of condition number frequency dependency

• The previous example of how the condition number varies across the channel during one 10 ms frame and how the pattern varies a few frames later depending on speed

• This variability is both a challenge and an opportunity• OFDMA systems can transmit at different frequencies within the channel

to target that part of the channel offering the best MIMO gains• CDMA systems cannot do this and have to accept the average

performance across the channel

Page 21




Antenna influence on performance

• The dynamic condition number example did not isolate effects from different components, including the antenna

• In real life, the instantaneous channel matrix H is made up from the interaction of three components:

• The static 3D antenna pattern of the transmitter• The dynamic multipath and Doppler characteristics of the radio channel• The static 3D antenna pattern of the receiver

• The overall antenna contribution is the product of the transmit and receive antennas known as the channel correlation matrix

Page 22




Antenna correlation

Page 23

• The correlation between antennas is a primarily a function of distance and polarization

• For non polarized antennas the correlation decreases with larger separation in the y axis - usually expressed in terms of wavelength λ




Examples of low and high antenna correlation

Page 24

Spaced non polarized:High correlation

Compound spaced and cross polarized:Low correlation




Antenna correlation by type

Page 25



AS = Azimuth Spread


Generating the overall channel correlation matrix

Page 26

Transmit antenna correlation Receive antenna correlation

The correlation matrix Rs is the Kronecker product RBS RMS

The α and β terms are complex and will vary by frequency




Example channel correlation matrices

Page 27

Cross polarized, UE (0, 90) BS (-45, 45), -8dB XPR ratio

Cross polarized, UE (-10, 80) BS (-30, 60), -8dB XPR ratio

Channelsbalanced

Diagonal = 1

Channelsunbalanced

Not ideal




Computing the instantaneous channel

Page 28

The complex instantaneous channel coefficients are obtained by applying each path of the desired fading profile to each channel of the correlation matrix

Ch 1 Ch 3Ch 2 Ch 4

Ch 1

Ch 3

Ch 2

Ch 4

The received signals and condition number are dynamic in both the time and frequency domains according to the chosen fading profile



ch1

ch4

ch2

ch3

T0

T1

R0

R1


Real life performance

Variation due to fading and variable interference

Page 29

Most macrocell activity takes place in this

region

Variation in the frequency

domain not shown




Precoding example for condition number 20 dBSecond stream is noise limited

No precoding Channel quality is unbalanced

Precoded with 1,1,-1,1 for equal EVM




Agenda





LTE downlink transmission modes3GPP TS 36.213 subclause 7.1

LTE has seven different downlink transmission modes:

1.Single-antenna port; port 0 SISO2.Transmit diversity MISO3.Open-loop spatial multiplexing MIMO – no precoding4.Closed-loop spatial multiplexing MIMO - precoding5.Multi-user MIMO MIMO -separate UE6.Closed-loop Rank=1 precoding MISO - beamsteering7.Single-antenna port; port 5 MISO – beamsteering

Each mode is suited to different channel and noise conditions

Page 32




The LTE MIMO toolset

• The LTE standard recognizes the complexity of the MIMO channel and has developed a very flexible air interface

• OFDMA allows for frequency-selective scheduling with 180 kHz and 1 ms granularity (one resource block)

• Comprehensive channel state information• Channel Quality Indicator (CQI) – • Precoding Matrix Indicator (PMI) – codebook based• Rank Indication (RI)

• Subband reporting for CQI & PMI, RI is wideband only• Highly configurable reporting mechanisms to account for

different scenarios• The UE can select what subbands to report on

Page 33




CQI definition3GPP TS 36.213 Table 7.2.3-1

CQI index modulation code rate x 1024 efficiency0 out of range1 QPSK 78 0.15232 QPSK 120 0.23443 QPSK 193 0.37704 QPSK 308 0.60165 QPSK 449 0.87706 QPSK 602 1.17587 16QAM 378 1.47668 16QAM 490 1.91419 16QAM 616 2.4063

10 64QAM 466 2.730511 64QAM 567 3.322312 64QAM 666 3.902313 64QAM 772 4.523414 64QAM 873 5.115215 64QAM 948 5.5547

Page 34

For each CQI reporting period the UE is required to return the highest CQI index that would have resulted in an error probability of less than 10% for a single transport block transmitted using the reported modulation and code rate.

Subband CQI reporting can be configured down to the resource block level




PMI definition3GPP TS 36.211 Table 6.3.4.2.3-1

Page 35

For single stream transmission the precoding produces beamsteering

For the 4 layer case there are 16 entries

Subband PMI reporting can be configured down to the resource block level




Agenda





LTE MIMO conformance testing

• The performance requirements for LTE are based on a number of simplifications to real world operation

• This often involves a modular approach of doing open loop testing of parts of the functionality rather than a more end-to-end approach

• This is a bit like measuring engine performance and other components rather than going for a test drive or a real track

• The modular approach is useful and separates the test equipment from the DUT but does not tell the whole story

• The consequence is that conformance test results cannot be easily mapped to real life conditions to predict typical performance

Page 37




MIMO conformance testing vs. real world

Page 38

Attribute Conformance testing Real world operation

Correlation matrixHigh, medium and zero - not linked to reference

antenna design

Real correlation based on actual antenna pattern

Fading channel Extended PA, VA, TU Channels with dynamic taps

Adaptive Modulation & coding

Off – UE becomes fading channel discriminator

On – coding aims for constant symbol to noise at UE receiver

CQI, PMI, RI Separate open loop tests Included as part of throughput

Cell-edge Interference signal

Static wideband Gaussian

Narrowband frequency-selective based on loading

Live antenna testingDeveloping open loop

Over The Air proposalsClosed loop Real loading due

to body/hand effects

Scheduling None, Single UEMultiple UE, real scheduler with

frequency selectivity base on subband CQI/PMI

Transmission mode FixedVariable based on prevailing

conditions




Agenda





Testing MIMO in the real world

• Most of the simplifications in conformance testing can be overcome with alternative test methods to get closer to real world performance

• We will now look at a few of the possibilities

Page 40




NEW N5106A PXB MIMO Receiver Tester

• The flexibility of the PXB can be used to verify MIMO receiver performance throughout the design cycle, at baseband or RF

RF

Analog I/QDirect from PXB

Connect to any DUT or RF vector signal generator with analog I/Q inputs

RF

Digital I/Q

Signal OutputsSignal Inputs Signal Creation Tools

ESG or MXGPXBMXA

N5102A




PXB creates real correlation based on reference antenna designs

Page 42

Rx antenna pattern, omni, 3 sector or 6 sector

Rx antenna #1 location and polarization

Rx antenna #2 location and polarization




Flexible Antenna Configuration and Correlation

In this example, there are 6 paths, each with

complex cross coupling coefficients

Path 1

Path 6

Path 2




PXB customizable fading simulation including dynamic channel taps




Flexible MIMO test using SystemVue

• TD-LTE or LTE-FDD MIMO Baseband data is generated by SystemVue and sent to PXB

• Flexible Fading applied by PXB• Two phase locked ESGs/MXGs driven by PXB

generate Receiver test signals for the DUT• Two MXAs capture received signals from DUT

output and send to SystemVue• SystemVue demodulates and decodes MIMO

signals to measure receiver performance

2xE4438C Signal Gen2xN9020A Signal Analyzer

N5106A PXB

SystemVue

DUT




Modeling MIMO crosstalk in SystemVue

Specify LO Phase Noise

dBc/Hz @ Freq. Offset

Specify 1dB

Comp. Pt.




Measuring impact of crosstalk and phase noise on demodulated MIMO streams

-29dB Tx0 / Rx1

QPSK 64 QAM

-29dB Tx0 / Rx1

• These measurement were made using the MIMO features of the Agilent 89601A Vector Signal Analyzer which fully integrates with the SystemVue design software




Upcoming TOL webcast

• For further information on SystemVue:

LTE MIMO System-Level Design and Test5/27/2009Greg Jue




Testing closed loop AMC with CQI, PMI and RI with integral fading• Open loop testing with no AMC avoids having to define the

reference behaviour of the test equipment• However, it is still necessary to investigate closed loop• The E6620A wireless

communications test set is designed to go beyond basicconformance to test closed loop MIMO up to 4x2

• Central to this is the inclusion of a baseband fading emulator

• This solution is the basis for development of scheduling algorithms and transmission mode selection criteria



E6620A Wireless Communications Test Set


Conclusion:Making MIMO work and testing it is tough!• The standards are very flexible and complex• The conformance tests are simple and largely open loop

with corner case SNR and artificial correlation• Real life is way more complex• Real antennas• Real channels• Real schedulers with multiple UE per cell• Dynamic configuration for CSI reporting• Real TX/RX distortion impacting channel feedback• Non Gaussian frequency-selective cell-edge interference

But Agilent is here to help you clear the way for MIMO

Page 50




RF Module Development

RF Proto RF Chip/Module

Design

SimulationBTS and Mobile

BB Chipset Development

L1/PHYFPGA and ASIC

Pre-

Conformance

Conformance

RF and BB Design

Integration

L1/PHY

System

Design

Validation

System Level

RF Testing

BTS orMobile

Protocol Development

L2/L3

Manufacturing

Network Deployment

Systems for RF and Protocol Conformance

ADS and SystemVue

LTE VSA SW

Spectrum and signal Analyzers, Scopes, LA

and ADS

Spectrum Analyzers

Signal Studio

Logic Analyzers

& Scopes

Signal Generators

Battery Drain

Characterization

Distributed Network AnalyzersDrive Test

PXB MIMO Rx Tester

DigRF v4

N9912A RF Analyzer

RDX for

DigRF v4

E6620A Wireless Communications Platform

Agilent/Anite SAT Protocol

Development Toolset

Page 51



LTE Lifecycle

Concepts of 3GPP LTE9 Oct 2007Page 52Page 52

Finding MIMO: Don’t stop now! Learn more atwww.agilent.com/find/MIMO and www.agilent.com/find/lte

MIMO Poster (5989-9618EN)

LTE Brochure(5989-7817EN)

Webcasts on• LTE Concepts• LTE Uplink• LTE Design and Simulation• LTE signaling

Webcasts on• LTE Concepts• LTE Uplink• LTE Design and Simulation• LTE signaling



PXB Brochure(5989-8970EN)

The 3GPP MIMO song: ftp.3gpp.org/tsg_ran/WG1_RL1/TSGR1_56/Docs/R1-091041.zip

Documents

Concepts of 3GPP LTE 9 Oct 2007 Page 1 MIMO MIA! …or the different faces of MIMO! Taking LTE MIMO from Standards to Starbucks Moray Rumney 30 th April