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4G/5G Wireless Communications System Modeling & Simulation

Keysight EEsof EDA

November, 2014

G: A Broad Spectrum of Opportunity

EEsof EDA SystemVue

©Keysight Technologies

2

The Mobile Data Future

Today’s 2G/3G/4G NW

Mobile data is real

Works most of the time

ₓ Works well some of the time

ₓ WiFi works but not integrated

ₓ Don’t try this in a crowd!

ₓ Consumes 2% of WW power

Gateway to

Competing NW

Tomorrow’s 5G NW

Great Service in a Crowd

Amazingly Fast

All Things Communicating

Centralized and Seamless

Networks

G Enabling Devices >> New 5G R&D Challenges

EEsof EDA SystemVue


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Multi-band • Traditional cellular bands <6GH

• WiFi, BT, GNSS bands

• 5G mmWave bands

Multi-antenna • Impedance matching

• Mutual coupling

• Multi-band, multi-RAT port

sharing

• FD / Massive MIMO

Amplifier • Envelope tracking

• Digital predistortion

• Wide, multi bands

Multiple radio access technologies • GSM/EDGE/WCDMA/HSPA/LTE

• WiFi/BT/WiGig/GNSS/5G

Advanced signal processing • Multiple MIMO modes and beamforming

• Network interference suppression

• Adaptive channel estimation / equalization

Full duplex communications • Self interference cancellation

• Dual polarization antenna

• Real time operation

New waveforms • Legacy OFDM enhancement

• FBMC, GFDM, UFDM

Access • Non-orthogonal

multiple access

• Random / scheduled /

hybrid

G Wireless: Opportunities to Innovate

EEsof EDA SystemVue


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Why this will be exciting to us:

1 GHz 10 GHz 100 GHz 1 THz 10 THz 100 THz 1PHz

10 cm 1 cm 1 mm 100 mm 10 mm 1 mm

Wavelength Frequency

Microwave mm-Wave THz Far IR Infrared UV

100X Efficiency (energy/bit)

Reliability 99.999%

1mS Latency

100X Densification

1000X Capacity

100X Data Rates

Enabling Technologies

1. mmWave (Carrier, BW, MU-MIMO)

2. New <6GHz PHY/MAC

3. Full Duplex

4. >>400GB/s Fiber

5. Hyper-Fast Data Buses

6. C-RAN & New NW Topology

Page

Link Level Simulation Challenges & Revolutions

EEsof EDA SystemVue


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Single-user Single-cell

Multi-user Single-cell

Multi-user Multi-cell

Multi-hierarchical relaying and coordination

GSM UMTS HSPA LTE/LTE-A

5G

3G • Synchronous dataflow technique

• Manual coding style language

4G • Dynamic dataflow technique

• Graphical design language

5G • Scenario aware dynamic

dataflow technique

• Graphical design +

scripting

• Incorporating data from

other sources

DB

PHY

Tx/Rx

chain 1

Link level simulator

PHY

Tx/Rx

chain 1

PHY

Tx/Rx

chain 1

System level simulator

PHY Parameters Interface

Scenario , Scripting , Control

Page

What you need for your research is…

5G New PHY Design and Test

©2014 Keysight Technologies

6

Transition naturally from Design to Test with a single “cockpit”

System Level

Platform

Software

Quickly capture “system level”

design concepts

Model implementation-level

impairments

Connect BB, RF, and T&M

for rapid validation

Rapid prototyping with

integrated measurement

RF / Analog

Channel Modeling MIMO Channel (OTA)

Digital Pre-Distortion (DPD)

RF System Design

Test Equipment RF Sources & Analyzers

AWG & Digitizers

Scopes, Logic, Modular

Test Software I/O Lib, ComExpert

89600 VSA

Signal Studio

3rd Party

BB Algorithm

Modeling MATLAB .m

FixedPoint, HDL/FPGA

Embedded C++

Filtering, EQ, Modem

IP Reference Libraries 4G LTE-Advanced, LTE ,5G

3G HSPA+, WCDMA, EDGE, GSM

WLAN 802.11ac/n/a/b/g

WPAN 802.11ad, 802.15.3c

RF EDA

Platforms

Mixed Simulation

Technologies

“Event Driven” plus

“Data Flow”

Page

Modeling New Physical Layer

Enabling Early 5G Research – A Flexible Platform for Innovation

W1906BEL 5G baseband exploration library (first in the industry)

• Physical layer modeling of 5G candidate PHYs and MIMO

• C++ source code enables early research, with a versatile simulation platform to

• Committed by Keysight to evolve toward world’s first 5G standard compliant library

EEsof EDA SystemVue


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Multi-Antenna Techniques Platform Enables “V” Lifecycle

– Provides 5G candidate

TX/RX waveforms

• Multi-carrier modem

Tx/Rx processing chain

• FBMC,OFDM, etc…

– Usable with 4G standard

library

– Advanced / adaptive signal

processing

• MIMO

• Digital beamforming

– Combined 2D/3D MIMO

channel simulation(W1715)

– Realistic RF environments

– Polymorphic Baseband

modeling

• Custom C++ model builder

• MATLAB®

• MATLAB® Script™

• HW implementation

Tackling Multi-Domain Issues

– Integrates with additional

technology domains

• SystemVue

• /ADS/EMPro/GG

• Keysight Instruments

5G New Waveform Techniques

Keysight EEsof EDA

November 14, 2014

Page

Waveform Design Considerations for 5G

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Bandwidth /

Frequency

Waveform

New RAT

3GHz 10GHz 30GHz 90GHz

Advanced Multi-Carrier Waveforms1

OFDM FBMC / OFDM / Others Single carrier

>> Wider BW, Higher Fc, much sensitive at phase noise

Note1: • Orthogonal Frequency Division Multiplexing(OFDM)

• Filter Bank Multicarrier(FBMC)

• Universal Filtered Multicarrier(UFMC)

• Generalized Frequency Division Multiplexing(GFDM)

• Biorthogonal Frequency Division Multiplexing(BFDM)

OFDMA NOMA SCMA

Page

Waveform Requirements

• Efficiently support high density users

• Optimized multiple access

• Carrier assignment schemes in asynchronous context

• Efficient usage of the allocated spectrum

• Robustness to narrow-band jammers and impulse noise

• High performance spectrum sensing

• Low computational complexity

• Compatibility OFDM vs. NEW

EEsof EDA SystemVue


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Figure 1.

– OFDM vs. FBMC

Spectrum Using

different filter overlap

factor

Figure 2.

– FBMC Fragmented

Spectrum

Figure 3.

– UFMC multiplex of

sub-bands

Page

Filter Operation

EEsof EDA SystemVue


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^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^

UFMC

OFDM

FBMC

per sub-band

per full-band

per sub-carrier

Page

UFMC - Universal Filtered Multi-Carrier

EEsof EDA SystemVue


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𝑤ℎ𝑒𝑟𝑒: N : FFT size, L : Filter length, ni : Complex QAM symbol F𝑖, 𝑘 𝑖𝑠 𝑎 𝑇𝑜𝑒𝑝𝑙𝑖𝑡𝑧 𝑚𝑎𝑡𝑟𝑖𝑥, 𝑐𝑜𝑚𝑝𝑜𝑠𝑒𝑑 𝑜𝑓 𝑡ℎ𝑒 𝑓𝑖𝑙𝑡𝑒𝑟 𝑖𝑚𝑝𝑢𝑙𝑠𝑒 𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒 V𝑖, 𝑘 𝑖𝑠 𝑎 𝐼𝐷𝐹𝑇 𝑚𝑎𝑡𝑟𝑖𝑥, 𝑎𝑐𝑐𝑜𝑟𝑑𝑖𝑛𝑔 𝑡𝑜 𝑡ℎ𝑒 𝑟𝑒𝑠𝑝𝑒𝑐𝑡𝑖𝑣𝑒 𝑠𝑢𝑏 − 𝑏𝑎𝑛𝑑 𝑝𝑜𝑠𝑖𝑡𝑖𝑜𝑛 S𝑖, 𝑘 𝑖𝑠 𝑎 𝑠𝑦𝑚𝑏𝑜𝑙 𝑚𝑎𝑡𝑟𝑖𝑥

* OFDM can be implemented by set L as 1

𝑋𝑘 = 𝐹𝑖, 𝑘

𝑁𝑆𝐵

𝑖=1

𝑉𝑖, 𝑘 𝑆𝑖, 𝑘

[ 𝑁 + 𝐿 − 1 , 1] [ 𝑁 + 𝐿 − 1 , 𝑁] [𝑁, 𝑛𝑖] [𝑛, 1]

x

+

𝑉1

x

.

.

.

.

.

.

𝐹1

𝑆1

x

𝑉2

x

𝐹2

𝑆2

x

𝑉𝑁𝑆𝐵

x

𝐹𝑁𝑆𝐵

𝑆𝑁𝑆𝐵

P/S , IFFT Sub-band block

filtering

Figure 1.

Five sub-band multiplexed

Page

OFDM

Advantage

– Good spectral efficiency

– Resistance against multipath interference

– Efficiently implemented using FFTs and IFFTs

– Subcarrier nulls correspond to peaks of

adjacent subcarriers for zero inter-carrier-

interference

Drawback

– Some loss of spectral efficiency due to Cyclic

Prefix insertion

– Imperfect synchronization cause loss of

orthogonality

– Large peak to average power ratio(PAR) leads to

amplifier inefficiency

– High out-of-band power

– Subcarrier intermodulation must be reduced

EEsof EDA SystemVue


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frequency

f1 f2

Page

OFDM vs. FBMC

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IFF

T

P / S

S / P

FF

T

Sym

bo

l

ma

pp

ing

Sub-c

arr

ier

ma

pp

ing

Sub-c

arr

ier

de-m

ap

pin

g

Sym

bo

l

de-m

ap

pin

g

OFDM baseband signal processing blocks

OQ

AM

pre

pro

cessin

g

IFF

T

Po

ly P

ha

se

Ne

two

rk

P / S

S / P

Po

ly P

ha

se

Ne

two

rk

FF

T

OQ

AM

p

ost p

roce

ssin

g

Synthesis Filter bank Analysis Filter bank

Sym

bo

l

ma

pp

ing

Sub

-ca

rrie

r

ma

pp

ing

Sub

-ca

rrie

r

de

-ma

pp

ing

Sym

bo

l

de

-ma

pp

ing

FBMC baseband signal processing blocks

Page

FBMC Signal Processing Block

EEsof EDA SystemVue


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Staggering Transform Poly phase

filtering

P/S

Conversion

𝑧−1

𝑧−1

.

.

.

↓ 𝑀/2

↓ 𝑀/2

↓ 𝑀/2

𝐵0(𝑧2)

𝐵1(𝑧2)

𝐵𝑀 − 1(𝑧2)

𝑭𝑭𝑻

𝛽 0, 𝑛

𝛽 1, 𝑛

𝛽 𝑀 − 1, 𝑛

x

x

x

.

.

.

𝑆𝑢𝑏𝐶𝐻 Proc



𝜃 0, 𝑛

𝜃 1, 𝑛

𝜃 𝑀 − 1, 𝑛

x

x

x

𝑑 0, 𝑛

𝑑 1, 𝑛

𝑑 𝑀 − 1, 𝑛

.

.

.

𝑅𝑒

𝑅𝑒

𝑅𝑒

𝑅2𝐶𝑘

𝑅2𝐶𝑘

𝑅2𝐶𝑘

.

.

.

.

.

.

𝐴0(𝑧2)

𝛽0, 𝑛

𝛽1, 𝑛

𝛽𝑀 − 1, 𝑛

𝐴1(𝑧2)

𝐴𝑀 − 1(𝑧2)

↑ 𝑀/2

↑ 𝑀/2

↑ 𝑀/2

x +

𝑧−1

+

𝑧−1

𝑰𝑭𝑭𝑻

x

x

𝜃0, 𝑛

𝜃1, 𝑛

𝜃𝑀 − 1, 𝑛

x

x

x

𝐶2𝑅𝑘

𝑑0, 𝑛

𝐶2𝑅𝑘

𝐶2𝑅𝑘

𝑑1, 𝑛

𝑑𝑀 − 1, 𝑛

.

.

.

.

.

.

.

.

.

.

.

.

𝑠[𝑚]

.

.

.

S/P

Conversion

Poly phase

filtering Transform De-

staggering

Sub

channel

processing

OQAM pre-

processing Synthesis Filter Bank Analysis Filter Bank OQAM post-

processing

FBMC transmitter FBMC receiver

Page

OQAM Preprocessing

EEsof EDA SystemVue


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𝑅(. )

𝑗𝐼(. )

↑ 2

↑ 2

+

𝑧−1

𝑥𝑘 𝑛

𝑐𝑘 𝑙

𝑅(. )

𝑗𝐼(. )

↑ 2

↑ 2

+

𝑧−1 𝑐𝑘 𝑙

= 1, 𝑗, 1, 𝑗, 1, . .

x

x

= 𝑗, 1, 𝑗, 1, 𝑗. .

• A time offset of half a QAM symbol period(T/2) is applied to either the real part or the

imaginary part of the QAM symbol

• For two successive sub-channels, say m and m+1, the offset are applied to the real part of

the QAM symbol in sub-channel , while it is applied to the imaginary part of the QAM

symbol in sub-channel m+1.

𝜃𝑘 𝑛

𝜃𝑘 𝑛

𝑥𝑘 𝑛

𝑑𝑘 𝑛

𝑑𝑘 𝑛

𝑓𝑜𝑟 𝑘 𝑒𝑣𝑒𝑛

𝑓𝑜𝑟 𝑘 𝑜𝑑𝑑

𝑐𝑜𝑚𝑝𝑙𝑒𝑥 𝑡𝑜 𝑟𝑒𝑎𝑙 𝑐𝑜𝑛𝑣𝑒𝑟𝑠𝑖𝑜𝑛 𝜃 pattern 𝑚𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑐𝑎𝑡𝑖𝑜𝑛

Page

Synthesis Filter Bank

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𝑠 𝑚 = 𝐴0(𝑧2)

𝛽0, 𝑛

𝛽1, 𝑛

𝐴1(𝑧2)

↑ 𝑀/2

↑ 𝑀/2

x +

𝑧−1

+ 𝑰𝑭𝑭𝑻

x

𝜃0, 𝑛

𝜃1, 𝑛

x

x

𝑑0, 𝑛

𝑑1, 𝑛

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

𝑤ℎ𝑒𝑟𝑒: M is number of subcarriers 𝑑𝑘, 𝑛 𝑖𝑠 𝑡ℎ𝑒 𝑟𝑒𝑎𝑙 𝑣𝑎𝑙𝑢𝑒𝑑 𝑠𝑦𝑚𝑏𝑜𝑙

𝜃𝑘, 𝑛 𝑖𝑠 𝑗

(𝑘 + 𝑛)

𝑔𝑘(m) is impulse response of the filters

* Filter overlap factor K : number of multicarrier symbols which

overlap in the time domain.

* OFDM can be implemented by set K as 1

.

𝑀−1

𝑘=0

𝑑𝑘, 𝑛

∞

𝑛=−∞

𝜃𝑘, 𝑛 𝑔𝑘 𝑚 − 𝑛𝑀/2

𝑠 𝑚

Page

Sub-channel Equalization

EEsof EDA SystemVue


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Maximal ratio combined diversity reception

X

𝑍-1

X

𝑍-1

+

X

+

𝑦[𝑘]

𝑤0 𝑤1 𝑤2

t[𝑘] transmitted

symbol

Channel

Estimation H[z]

3-tap Complex FIR frequency sampling-design

𝑤i

Evaluation of MRC weighted target values

distorted subcarrier

sequence 𝑙 = number of tap

𝑣𝑘 𝑛 = 𝑤𝑘, 𝑙, 𝑛

2

𝑙=0

𝑦𝑘 𝑛 − 𝑙

𝑣𝑘 𝑛

Page

OQAM post processing

EEsof EDA SystemVue


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↓ 2

𝑧−1

𝑧−1

↓ 2

+

𝑗

𝑥𝑘 𝑛 𝑐 𝑘 𝑙

↓ 2

𝑧−1

𝑧−1

↓ 2

+

𝑗 𝑐 𝑘 𝑙

x

x

𝜃 𝑘 𝑛

𝜃 𝑘 𝑛

𝑥𝑘 𝑛

𝑑 𝑘 𝑛

𝑑 𝑘 𝑛

𝑓𝑜𝑟 𝑘 𝑒𝑣𝑒𝑛

𝑓𝑜𝑟 𝑘 𝑜𝑑𝑑

𝑟𝑒𝑎𝑙 𝑡𝑜 𝑐𝑜𝑚𝑝𝑙𝑒𝑥 𝑐𝑜𝑛𝑣𝑒𝑟𝑠𝑖𝑜𝑛 𝜃 pattern 𝑚𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑐𝑎𝑡𝑖𝑜𝑛

𝑅(. )

𝑅(. )

Page

Modeling / Simulation Example for FBMC Systems

EEsof EDA SystemVue


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Simulation parameters

ChannelOut

Taps

ModelType=Pedestrian_A

C1 {CommsChannel@Data Flow Models}

• • •• • •

• • • • • •

MAPPER

ModType=QPSK [ModType]M1 {Mapper@Data Flow Models}

1 1 0 1 0

B1 {RandomBits@Data Flow Models}

DeMod IAmp

FreqPhase

Q

FCarrier=1e9 Hz

OutputType=I/Q D3 {Demodulator@Data Flow Models}

• • •• • •

• • • • • •

DEMAPPER

Bits

Node

ModType=QPSK [ModType]D2 {Demapper@Data Flow Models}

FBMC_Source

FBMC_Source_1

Re

Im

C4 {CxToRect@Data Flow Models}

ModOUT

QUADOUT

FreqPhaseQ

IAmp

M2 {Modulator@Data Flow Models}Re

Im

R3 {RectToCx@Data Flow Models}

NoiseDensity

NDensity=10e-12 W [NDensity]

NDensityType=Constant noise density A1 {AddNDensity@Data Flow Models}

FBMC_Receiver

FBMC_Receiver_2

O1 {Oscillator@Data Flow Models}

Random

bit

generation

Symbol

Mapping

FBMC

Reference

Source

LO source

Phase/

Power

Modulator

FO,IQ Im

Wireless

Channel

AWGN

Demodulator

FO,IQ Im

FBMC

Reference

Receiver

BER/FER

Measurem

ent

TEST

REF

BERFER {BER_FER@Data Flow Models}

ADC

Jitter /

Q noise

Page

Reference Transmitter

EEsof EDA SystemVue


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Pilot Insertion

Active Subcarriers Mapping Complex Splitter

Extend IFFT

PPN IFFT

OQAM Modulator Add IdleInterval

Bus=NO

Data Type=Complex Input {DATAPORT}

Preamble Sequence

OFDM _Subc arrierM ux

Input

Output

EVM Ref

CustomEVMRef=NO OversampleRatio=x2 [OFDMMuxOversampleRatio]

OutputOrder=Neg_DC_Pos In1_CarrierIndex=(1x128) [-64,-63,-62…

In1_DimCarrierIndex=1-D In1_NumCarriers=128 [[NumActiveSubc]]

NumInput=1 DFTSize=128 [NumSubcarriers]

O1

A

BlockSizes=(3x1) [6144; 20480; 3072] A1 {AsyncCommutator@Data Flow Models}

0

Value=0 C2 {Const@Data Flow Models}

0

Value=0 C3 {Const@Data Flow Models}

Bus=NO Data Type=Complex Output {DATAPORT}

T

SampleRate=20e+6 Hz [SampleRate*(2^OversampleRatio)]S1 {SetSampleRate@Data Flow Models}

A

BlockSizes=(3x1) [6144; 20480; 3072] A2 {AsyncCommutator@Data Flow Models}

OFDM _Subc arrierM ux

Input

Output

EVM Ref

CustomEVMRef=NO OversampleRatio=x2 [OFDMMuxOversampleRatio]

OutputOrder=Neg_DC_Pos In1_CarrierIndex=(1x128) [-64,-63,-62…

In1_DimCarrierIndex=1-D In1_NumCarriers=128 [[ActiveData]]NumInput=1 [DataSym_NumInput]DFTSize=128 [NumSubcarriers]

O2

FBM C_Ex tended_IFFT

Q_Out

I_Out

Q_In

I_In

ActiveSubcAlloc=(1x2) [-64,63] FilterCoef=(1x4) [1,-0.972,0.707,-0.2…

FilterOverlapFactor=4 NumSubcarriers=128 [NumSubcarriers]

OversampleRatio=Ratio 2 FBMC_Extended_IFFT_1

FBMC_PPN_IFFT

Output_Q

Ouput_I

Q

I


FilterOverlapFactor=4 NumSubcarriers=128 [NumSubcarriers]OversampleRatio=1 [OversampleRatio]

Disabled: OPENFBMC_PPN_IFFT_1

FBMC_PPN_IFFT

Output_Q

Ouput_I

Q

I


FilterOverlapFactor=4 NumSubcarriers=128 [NumSubcarriers]OversampleRatio=1 [OversampleRatio]

Disabled: OPEN

FBMC_PPN_IFFT_2

FBM C_Com plexSplitter

I

Q

input

ShiftPhase=NO FBMC_ComplexSplitter_1

FBMC

ZC Generator

ZC_RootIndex2=3 [ZC_RootIndex2]ZC_RootIndex1=7 [ZC_RootIndex1]

ActiveSubcAlloc=(1x2) [-64,63] NumActiveSubcarriers=128

NumSubcarriers=128 [NumSubcarriers]F1 {FBMC_ZC_Generator@5G Advanced Modem Models}

FBM C_OQAM _Modulator

Output

I

Q

FilterOverlapFactor=4 OversampleRatio=1 [OversampleRatio]NumSubcarriers=128 [NumSubcarriers]

FBMC_OQAM_Modulator_1

FBM C_Com plexSplitter

I

Q

input

ShiftPhase=YES

FBMC_ComplexSplitter_2

FBM C_Ex tended_IFFT

Q_Out

I_Out

Q_In

I_In

ActiveSubcAlloc=(1x2) [-64,63]

FilterCoef=(1x4) [1,-0.972,0.707,-0.2… FilterOverlapFactor=4

NumSubcarriers=128 [NumSubcarriers]OversampleRatio=Ratio 2 FBMC_Extended_IFFT_2

Periodic=YES Offset=0 V

ExplicitValues=<empty> V [ActivePilotSequence]Disabled: OPEN

W5 {WaveForm@Data Flow Models}

nWrite=7464 [FrameSizeWithIdle]nRead=7424 [FrameSize]

C1 {Chop@Data Flow Models}

Data and Pilot Insertion

Preamble Pattern Insertion

IFFT

Mode change

(Extended /

PPN)

Data

Framing

OQAM

Modulation

Idle Interval

Insertion

Prototype filter using different filter overlap factor

Page

Reference Receiver

EEsof EDA SystemVue


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Bus=NO

Data Type=Complex

Input {DATAPORT}

nWrite=128 [NumSubcarriers]

nRead=256 [NumSubcarriers*2^OversampleRatio]


nWrite=128 [NumSubcarriers]

nRead=256 [NumSubcarriers*2^OversampleRatio]


REPEAT

BlockSize=128 [NumSubcarriers]

NumTimes=30 [NumGuardRemove+NumDataSyms]

R1 {Repeat@Data Flow Models}

0

Value=0

C2 {Const@Data Flow Models}

I nput

O ut put

FFO Est

FBMC

FracFreq Est

NumDataSyms=20 [NumDataSyms]

NumPreambleSyms=6 [NumPreambleSyms]

NumSubcarriers=128 [NumSubcarriers]

FilterOverlapFactor=4

IdleInterval=2e-6 [IdleInterval]

SampleRate=10e+6 [SampleRate]

OversampleOption=Ratio 2

F4

I nput

Tim ingEst

I FO Est

FBMC

Frame Sync

ZC_RootIndex2=3 [ZC_RootIndex2]









F5

FBM C_O Q AM _Dem odulator

I _O ut

Q _O ut

I nput



OversampleRatio=Ratio 2

FBMC_OQAM_Demodulator_1 {FBMC_OQAM_Demodulator@5G Advanced Modem Models}

FBMC

Chan Equalizer

NumEqualizerTaps=One Tap


NumActiveSubcarriers=128


F1 {FBMC_ChannelEqualizer@5G Advanced Modem Models}

OFDM _GuardRemoveI nput O ut put

OversampleRatio=x1

CIRAdjust=0

GuardStuff=CyclicShift

PostfixSize=0 [[0]]

PrefixSize=1120 [[ActiveData*NumGuardRemove]]

DFTSize=2240 [ActiveData*NumDataSyms]

O2 {OFDM_GuardRemove@Data Flow Models}

FBM C_Com plexCom binerO ut put

I _In

Q _In

FBMC_ComplexCombiner_1

Timing & Frequency Synchronization Frame DemuxOQAM Demod

Channel Estimation

FFT

Channel Equalization Phase Tracking

FBM C_PhaseTr acking

Q _O ut put

I _O ut put

Q _I nput

I _I nput

ActivePilotSequence=(16x1) [1; 1; 1]

PilotLoc=(1x16) [-64,-56,-48,-40,-32]


F3

Subcarrier Demux

O FDM _Subcar r ier Dem ux

I nput O ut put

OversampleRatio=x1

InputOrder=Neg_DC_Pos

Out1_CarrierIndex=(1x112) [-63,-62,-6…

Out1_DimCarrierIndex=1-D

Out1_NumCarriers=112 [[ActiveData]]

NumOutput=1

DFTSize=128 [NumSubcarriers]

O3 {OFDM_SubcarrierDemux@Data Flow Models}

A

BlockSizes=(2x1) [7424; 256]

A1 {AsyncCommutator@Data Flow Models}

Bus=NO

Data Type=Complex

Output {DATAPORT}

FBM C_Ext ended_FFT

I _O ut

Q _O ut

I _In

Q _In


FilterCoef=(1x4) [1,-0.972,0.707,-0.2…




Disabled: OPEN

FBMC_Extended_FFT_1 {FBMC_Extended_FFT@5G Advanced Modem Models}

FBM C_PPN_FFT

I _O ut

Q _O ut

I _In

Q _In


FilterCoef=(1x4) [1,-0.972,0.707,-0.2…




FBMC_PPN_FFT_1 {FBMC_PPN_FFT@5G Advanced Modem Models}

FBMC

Demux Frame

FreqSync=Full freq compensation








F2

FBMC

Chan Estimator

Tmax=200e-9 [Tmax]







NumActiveSubcarriers=128


F8 {FBMC_ChannelEstimator@5G Advanced Modem Models}

Fractional

Frequency

Offset

Estimation

IFO &

Timing

Estimation

Frame De-

multiplexing Analysis

Filter Bank

Sub-channel

Equalization Phase

Tracking Preamble

Remove

Channel

Estimation

Block

Diagram

Modeling using graphical

simulation tool

Auto-

correlation

Cross-correlation

with local Zadoff-

Chu sequence

Preamble symbols

with frequency

compensated

Preamble based

channel estimation

Multi-tap

equalization

Use pilot in

data symbols

Page

//The peak of auto-correlation is chosen by the midpoint of the inputs which exceed the threshold //FFO is gotten by the angle of the peak std::vector<double> AutoCorr(m_FrameSizeWithIdle,0); double maxV = 0; for (int i = 0; i < m_FrameSizeWithIdle; ++i) { AutoCorr[i] = abs(corr(m_Buffer.begin()+m_FrameSizeWithIdle-2*m_SymSize+i+1,m_Buffer.begin()+m_FrameSizeWithIdle-m_SymSize+i+1,m_SymSize)); if (AutoCorr[i] > maxV) maxV = AutoCorr[i]; } double threshold = maxV*0.75; int low_idx = 0; int upper_idx = 0; for (int i = 0; i < m_FrameSizeWithIdle; ++i) { if (AutoCorr[i] > threshold) { low_idx = i; break; } } for (int i = 0; i < m_FrameSizeWithIdle; ++i) { if (AutoCorr[i] > threshold) upper_idx = i; } int peak_idx = (low_idx + upper_idx)/2; std::complex<double> peak_corr; peak_corr = corr(m_Buffer.begin()+m_FrameSizeWithIdle-2*m_SymSize+peak_idx+1,m_Buffer.begin()+m_FrameSizeWithIdle-m_SymSize+peak_idx+1,m_SymSize); m_FFOEst = atan2(peak_corr.imag(),peak_corr.real())/(2*PI);

Fractional Frequency Estimation

EEsof EDA SystemVue


16

Page

std::copy(m_Buffer.begin()+m_FrameSizeWithIdle,m_Buffer.end(),m_Buffer.begin()); for (int i = 0; i < m_FrameSizeWithIdle; ++i) m_Buffer[i+m_FrameSizeWithIdle] = Input[i]; std::vector<double> CrossCorr1(m_FrameSizeWithIdle); std::vector<double> CrossCorr2(m_FrameSizeWithIdle); for (int i = 0; i < m_FrameSizeWithIdle; ++i) { CrossCorr1[i] = abs(corr(m_Buffer.begin()+m_FrameSizeWithIdle-m_SymSize+i+1,m_ZC_ifft1.begin(),m_SymSize)); CrossCorr2[i] = abs(corr(m_Buffer.begin()+m_FrameSizeWithIdle-m_SymSize+i+1,m_ZC_ifft2.begin(),m_SymSize)); } // Variable definition intentionally removed IFOEst[0] = (idx2-idx1)/(m_ZC_RootIndex1-m_ZC_RootIndex2)/m_OversampleRatio; TimingEst[0] = (idx2*m_ZC_RootIndex1-idx1*m_ZC_RootIndex2)/(m_ZC_RootIndex1-m_ZC_RootIndex2)-(m_FilterOverlapFactor-1)*m_SymSize+1;

Frame Synchronization

EEsof EDA SystemVue


17

IFO and Timing Estimation

//Timing synchronization is achieved by the cross-correlation between local ZC sequences and received Preamble //The number of peak is relative with the number of preamble symbols per frame //IFO and timing estimate are gotten by the difference of peaks of two ZC sequences

Page

for (int i = 0; i< ActiveSubcAllocArraySize/2; i++) { std::vector<std::complex<double> > A, ANeg, APos; A.resize(ActiveSubcAlloc[2*i+1]-ActiveSubcAlloc[2*i]+1); ANeg.resize(ActiveSubcAlloc[2*i+1]-ActiveSubcAlloc[2*i]+1); APos.resize(ActiveSubcAlloc[2*i+1]-ActiveSubcAlloc[2*i]+1); for (int k = 0; k < ActiveSubcAlloc[2*i+1]-ActiveSubcAlloc[2*i]+1; k++) A[k] = tmp[ActiveSubcAlloc[2*i]+NumSubcarriers/2+k]; ANeg[0] = 0.5*(A[ActiveSubcAlloc[2*i+1]-ActiveSubcAlloc[2*i]] + A[0]); for (int k = 1; k < ActiveSubcAlloc[2*i+1]-ActiveSubcAlloc[2*i]+1; k++) { ANeg[k] = 0.5*(A[k-1] + A[k]); } for (int k = 0; k < ActiveSubcAlloc[2*i+1]-ActiveSubcAlloc[2*i]; k++) { APos[k] = 0.5*(A[k+1] + A[k]); } APos[ActiveSubcAlloc[2*i+1]-ActiveSubcAlloc[2*i]] = 0.5*(A[ActiveSubcAlloc[2*i+1]-ActiveSubcAlloc[2*i]] + A[0]); for (int k = 0; k < ActiveSubcAlloc[2*i+1]-ActiveSubcAlloc[2*i]+1; k++) { m_WNeg[ActiveSubcAlloc[2*i]+NumSubcarriers/2+k] = ANeg[k]; m_WPos[ActiveSubcAlloc[2*i]+NumSubcarriers/2+k] = APos[k]; m_W[ActiveSubcAlloc[2*i]+NumSubcarriers/2+k] = A[k]; } }

Channel Estimation and Equalization

EEsof EDA SystemVue


18

//The repeated structure of preamble symbols formed cyclic prefix that make it robust to multipath. Preamble symbol is chosen to do channel estimation as pilot. //One Tap, Two Taps and Three Taps equalization could be done by changing the parameter NumEqualizerTaps. //Example code is partial of the entire sourece

Constellation of Pedestrian_A Channel

with SNR= 20dB

Page

Performance Analysis with Real Hardware

EEsof EDA SystemVue


19

RFIC DUT

• Wider BW (63 GHz BW)

• Higher Sampling (160 GSa/s)

BBIQ - RF

RF - BBIQ

M8190A 12 GSa/S Arbitrary

Waveform Generator

M9703A AXIe 12-bit High-Speed

Digitizer/Wideband Digital Receiver

Interleaving to get 4ch @ 3.2 GSa/s

Infiniium 90000 Q-Series Oscilloscope

I

Q

I

Q

SYSTEMVUE

TEST

REF


BPSK, QPSK, ..., up to 4096-QAM

8-PSK, 16-PSK, 16-APSK, 32-APSK16-Star QAM, 32-Star-QAM,

and Custom APSK

Data PayloadPreambleIdle

Frame Structure

Spreading CodeGenerator

X

Digital Modem Sourcefor Linear Modulation

DSSS System

Payload_ModType=16-QAM [Payload_ModType]

Preamble_ModType=BPSK [Preamble_ModType]

Decision Device

FeedwardFilter

-

-

FeedbackFilter

Decision Feedback Equalizer

Fast Computation Algorithm

CIR--->DFE coefficients

Digital Modem Receiver

TrackingAlgorithm=LMS

FreqSync_Mode=CIR Corr

FrameSync_Algorithm=DiffCorr

{DigMod_ReceiverL_FastDFE}

Automatic waveform

creation & download

Reference Source

Reference

Receiver

BER/FER Measurement

Custom modem

design

5G Reference

Library

: Replaceable

in C++, .m or

SV DSP

parts formats

MIMO and Digital Beamforming

Keysight EEsof EDA

November xx, 2014

Page

Motivation

– Higher requirement for system capacity and spectral efficiency(bits/s/Hz)

– To overcome traditional approaches ( expand bandwidth, higher modulation order,

multiple access)

– The MIMO for better use the spatial resource

• The capacity is increased by a multiplication of the number of antennas

EEsof EDA SystemVue


2

MsbitN

SBC

/1log2

Page

Classification

EEsof EDA SystemVue


3

Spatial diversity

Improve robustness

Transmit Diversity Receive Diversity

Space-time block coding (STBC)

X1, X2

-X2, X1*

y1, y2

Spatial division multiplexing

Transmit Beamforming

Spatial multiplexing

Improve user throughput

MIMO

Matrix

X1

X2

y1

y2

Spatial Expansion

Multi-user MIMO

Multi-user Increase system

efficiency

Multi streams/users

.

.

.

.

.

. M a

nte

nn

as

K t

erm

inals

S s

tre

am

s

Massive MIMO

M >> K >> 1

Massive multi-users

Use spatial channel

information? • Open-loop MIMO

• Closed-loop MIMO

Page

Transmit Diversity

– Use transmit diversity to diminish the effects of fading by

transmitting the same information from two different

antennas

– The data from the second antenna is encoded differently

to distinguish it from the primary antenna

– The transmit diversity feature uses ST(space-time) or

SF(space-frequency) block encoding to differentiate the

signals between Antenna 1 and Antenna 2

– The user equipment (UE) must be able to recognize that

the information is coming from two different locations and

properly decode the data.

EEsof EDA SystemVue


4

X1, X2

-X2, X1*

y1, y2

** 12

21

xx

xx

f1 f2

t1 t2

Tx0

Tx1

SFBC:

STBC:

* complex conjugate

Page

Spatial Multiplexing

– Operation Concept

• Transmission of multiple spatial data streams over

different antennas in the same RB

• The dimension of spatial channels is increased and

system capacity increased

– Relevant signal processing

• Perform Layer mapping and Pre-coding to lower the

receiver complexity and reduce the signal interference

between antennas

• Statistic correlation between vector(h11,h12) and

vector(h21,h22 )

EEsof EDA SystemVue


5

X1

X2

y1

y2

h11

h21

h12

h22

x: transmitted signal,

y: received signal,

H: spatial channel matrix,

Hij: channel coefficient from the jth transmit

antenna and the ith receive antenna.

y=Hx

y1=h11x1+h12x2+n1

y2=h21x1+h22x2+n2

Page

Modeling and Simulation for MIMO

– MIMO Tx/Rx simulation under Rayleigh fading and AWGN channel

– Explore different decoding algorithms and performance evaluation

• ML, MMSE-SIC, ZF-SIC, MMSE-Linear, ZF-Linear

EEsof EDA SystemVue


6

A4 {Add@Data Flow Models}

StdDev=707.1e-6 V [StdDev]I2 {IID_Gaussian@Data Flow Models}

StdDev=707.1e-6 V [StdDev]I6 {IID_Gaussian@Data Flow Models}

Re

Im


[ ]

Format=ColumnMajor NumCols=1 [RxNumCols]

NumRows=2 [RxNumRows]P2 {Pack_M@Data Flow Models}

[ ]

Format=ColumnMajor NumCols=1 [TxNumCols]

NumRows=2 [TxNumRows]

U1 {Unpack_M@Data Flow Models}

MIMO_DecoderRec ov eredData

M odType

ChannelRes ponse

Rec eiv edData

DebugFlag=0

ModType=QPSK [ModType]DecoderMethod=ML [DecoderMethod]

Mode=Spatial Multiplexing [Mode]M3 {MIMO_Decoder@5G Advanced Modem Models}

• • •• • •

• • • • • •

DEMAPPER

Bits

Node

ModType=QPSK [ModType]D1 {Demapper@Data Flow Models}

M2 {Mpy@Data Flow Models}

StdDev=0.707 V [1/sqrt(2)]I5 {IID_Gaussian@Data Flow Models}

Re

Im


[ ]

Format=ColumnMajor

NumCols=2 [ChannelNumCols]NumRows=2 [ChannelNumRows]

P1 {Pack_M@Data Flow Models}

StdDev=0.707 V [1/sqrt(2)]I7 {IID_Gaussian@Data Flow Models}

MIMO_Encoder

NumTx=2 [NumTx]Mode=Spatial Multiplexing [Mode]

M1 {MIMO_Encoder@5G Advanced Modem Models}

[ ]

Format=ColumnMajor NumCols=1 [TxNumCols]

NumRows=2 [TxNumRows]P3 {Pack_M@Data Flow Models}

• • •• • •

• • • • • •

MAPPER

ModType=QPSK [ModType]

M5 {Mapper@Data Flow Models}

1 1 0 1 0

B2 {RandomBits@Data Flow Models}

Fading Channel AWGN

Transmit with MIMO coding MIMO decoding and demapper

Page

Multi-User MIMO

EEsof EDA SystemVue


7

Received signal at UE k:

The challenge for MU-MIMO is to find orthogonal

users and design precoding W to minimize the

second term with the restrictions of user grouping,

power, latency and complexity

Hk: kth user’s channel, Wk: weight vector, Sk: data symbol

SU−MIMO: 𝑀𝑙𝑜𝑔(1 + 𝑆𝑁𝑅)

MU-MIMO: 𝑀𝑙𝑜𝑔 1 +𝑆𝑁𝑅

𝑀𝑙𝑜𝑔𝑈 , 𝑈 → ∞

M: TX antenna number, U: Total user number

Capacity Comparison

MU-MIMO Scenario

Page

Multi-User MIMO

Advantages

– Maintain spatial multiplexing gain without large

antenna number at terminals

– Multiple access capacity gain (proportional to

BS antennas)

– More immune to propagation limitations such

as channel rank loss, antenna correlation and

LOS

Disadvantages

– BS needs to know channel state information at

transmitter (CSIT). The challenges include

• TDD vs. FDD for CSIT

• CSI feedback path bandwidth, Code book

design

– Complexity of the scheduling procedure at BS

• User grouping scheduling, power allocation

and latency requirements

EEsof EDA SystemVue


8

Page

Modeling and Simulation for Capacity Estimation

EEsof EDA SystemVue


9

Simulation condition

– Transmit antenna number (M) : 4

– Total number of user : from 4 to 100

– SNR=10dB

– Power allocation by waterfilling algorithm

User Scheduler

Power_Selected

W_Selected

H_Selected

H

TotalPower=10 [SNR]

NumRx=1

NumTx=4 [NumTx]

TotalUsers=100 [TotalUsers]

UserScheduler {MATLAB_Script@Data Flow Models}

Channel Capacity

R

P

W

H

NumRx=1

Noise=1

NumTx=4 [NumTx]

SumRate {MATLAB_Script@Data Flow Models}

NumInputsToAverage=100

A1 {Average@Data Flow Models}

123

StartStopOption=Samples

S4 {Sink@Data Flow Models}

StdDev=0.707 V [1/sqrt(2)]

I1 {IID_Gaussian@Data Flow Models}

StdDev=0.707 V [1/sqrt(2)]

I3 {IID_Gaussian@Data Flow Models}

Re

Im


[ ]

Format=ColumnMajor

NumCols=4 [NumTx]

NumRows=1 [NumRx]P4 {Pack_M@Data Flow Models}

BlockSize=1

D2 {Distributor@Data Flow Models}

Channel transfer matrix User scheduling Capacity measurement

User K: 4->100

Su

m C

ap

acity

Page

Massive MIMO

– The use of a very large number of service antennas operated fully

coherent and adaptive

– Brings huge improvements in throughput and energy efficiency

when combined with simultaneous scheduling of a large number of

Ues

– System Model : M transmit antenna with maximum S streams, K

users each with a single antenna

– Originally envisioned for time division duplex(TDD1), but can

potentially be applied in frequency division duplex(FDD)

EEsof EDA SystemVue


10

.

.

.

.

.

. M a

nte

nn

as

K t

erm

ina

ls

S s

tre

am

s

Massive MIMO

M >> K >> 1

Massive multi-users

Note1 : Prefer TDD as not enough resources for pilots and CSI feedback.

Page

Massive MIMO Operation and Challenges

Operation

– Acquire Channel State Information from uplink

Pilots / Data

– Reciprocity calibration and adjustment

– Pre-coding1 to support multi-stream

transmission

– MMSE receiver with beamforming

• Maximum ratio combining(MRC) : interference

and noise are both white in the space

• Interference rejection combining(IRC): colored

interference

Challenges

– Pilot contamination: interference from other cells

• Blind channel estimation?

• Coordination and planning?

– New pre-coder with low-complexity, low-PAPR

– Hardware performance

• I/Q imbalance, A/D resolution, PA linearity

• Phase noise, clock distribution

– Synchronization at low SNR

– Understand mmWave MIMO channel

EEsof EDA SystemVue


11

Note1 : Linear pre-coding [maximum ratio transmission(MRT), zero-forcing(ZF)].

Non-linear pre-coding [Dirty paper coding(DPC)], full CSI required

Page

Modeling and Simulation for Large Number of Antennas

EEsof EDA SystemVue


12

quad_output

output

LO

inputMultiChannel

Modulator

ShowIQ_Impairments=NO MirrorSignal=NO

ConjugatedQuadrature=NO AmpSensitivity=1 [[1]]

InitialPhase=0 ° [[0]]FCarrier=1e6 Hz

NumChannels=1 M1 {MultiCh_Modulator@5G Advanced Modem Models}

TxBeamformer

weights

output

InPhi

InTheta

input

Phi=0 °Theta=0 °

Dy=0.5 Dx=0.5

NumOfAnty=4 NumOfAntx=4

BeamformingType=Calculate by antenna … T1 {Tx_Beamformer@5G Advanced Modem Models}

Env

OutputFc=Center

M4 {MultiCh_AddEnv@5G Advanced Modem Models}

MultiChNoise Density

NDensity=0.0 WNDensityType=Constant noise density

M6 {MultiCh_AddNDensity@5G Advanced Modem Models}

MultiChannel

Demodulator

ShowIQ_Impairments=NO MirrorSignal=NO

AmpSensitivity=1 [[1]]InitialPhase=0 ° [[0]]

FCarrier=1e6 HzNumChannels=1

M2 {MultiCh_Demodulator@5G Advanced Modem Models}

RxBeamformer

weights

output

ref

input

BlockSize=1024 ABF_Algorithm=Sample Matrix Inversion

NumOfTxAnts=16 R1 {Rx_Beamformer@5G Advanced Modem Models}

Power=.010 WFrequency=1000000 HzO1 {Oscillator@Data Flow Models}

Transmit

Beamformer

Multi-CH

Modulator

Multi-CH

Envelope Adder

Multi-CH

AWGN

Multi-CH

De-Modulator

Receive

Beamformer

Plotting • Antenna pattern review

• Interference analysis

between different

streams

• Beam pattern vs. pre-

coding analysis(MRT,ZF)

Scripting • Multiuser scheduling

• Capacity analysis

• Quick algorithm

implementation and test

• Calibration

Page

Channel Sounding / Parameter Extraction / Simulation

EEsof EDA SystemVue


13

𝑧[𝑘] t[𝑘]

Reference transmit signal(chirp/pn)

channel

H[z] ∑ CIR

correlation

Channel

impulse

response

Channel sounding

Estimation

algorithms

Channel

parameters

• PDP (Path delay, path loss)

• AOA, AOD

• Doppler shift

Parameters estimation

• Scenario selection

• Network layout

• Antenna parameters

Large/Small scale

parameters

generation

Fading coefficient

generation

• AS AoA/AoD

• PAS

• Doppler spectrum

• Correlation

• Rician K factor

Statistics & modeling

¤ 𝑥[𝑘] 𝑦[𝑘]

Input signal faded signal

SystemVue Simulation

SAGE

Maximum likelihood

estimation algorithm

No limitation for number

of path, suitable for both

LOS and NLOS scenarios

Can estimate all the

channel parameters

including path loss and path

delay of each path

Iteration needed, large

computing amount

ESPRIT

Subspace based algorithm

Maximum estimating

number of path is limited by

number of Rx, will be fail

under NLOS scenario

cannot estimate path loss

and path delay

small computing amount

Page

Prototyping and Testing in Real Time Hardware

EEsof EDA SystemVue


14

FPGA

ARRAY M9703

REAL-TIME PROCESSING

Up to 40 Channels x 1GHz wide

CUSTOM

ALGORITHMS

FPGA

ARRAY

– Move forward from largely theoretical massive MIMO research to real hardware

implementation and test

– Open FPGA and download custom algorithms for MIMO and Beamforming

– Test and measure in real-time

Tacking Cross Domain Issue

Keysight EEsof EDA

November xx, 2014

Page

Motivation

– Design problem spans to different technology domains (Baseband signal processing,

RF circuit design, Radio access networking)

– System level problem cannot be solved in any one domain alone

– RF circuit verification now needs using a realistic representation of the complex

modulated RF signal

– Baseband and RF team entirely isolated and use different type of tools

– Needs unified BB/RF design and verification flow

EEsof EDA SystemVue


2

Page

Modeling Transmitter Path

EEsof EDA SystemVue


3

Signal quality degraded by:

• PA Compression

• Intermods

• Spectral Spread

• LO Phase Noise

• BPF Filter Effects

Phase

Noise

ModOUT

QUAD

OUT

Freq

Phase

Q

I

Amp

FCarrier=897e6Hz

InputType=I/QM5 {Modulator@Data Flow Models}

Power=0.01WFrequency=897e+6Hz [Fcarrier]


Amplifier

TOIout=10W

GCType=noneNoiseFigure=0

Gain=1GainUnit=voltage

A2 {Amplif ier@Data Flow Models}

Re

Im

Poly Phase

FBMC_Tx

OversampleRatio=2 [OversampleRatio]MappingType=5 [MappingType]

FilterCoef=(3x1) [-0.972; 0.707; -0.235…

FilterOverlapFactor=4ActiveSubcAlloc=(2x2) [-64,-31; 10,63]

NumSubc=128 [NumSubc]Subnetwork1 {PPN IFFT Transmitter}

1 1 0 1 0

Spectrum Analyzer

ResBW=5000HzStart=0s

Mode=ResBW

SPECTRUM_PPN {SpectrumAnalyzerEnv@Data Flow Models}

CCDF

Stop=2e-2sStart=0s

Distribution_PPN {CCDF_Env@Data Flow Models}PassRipple=1

PassBandwidth=100e6Hz

FCenter=897e+6Hz [Fcarrier]F1 {BPF_ChebyshevI@Data Flow Models}

Gain, NF &

Compression

Characteristics Ripple, Group

Delay & BPF

Characteristics

Signal quality degraded by:

• Different multi-carrier waveform

• Apply different prototype filter

Gain, phase

imbalance, IQ

offset

Different

waveform,

modulation

Page

Modeling Receiver Path

EEsof EDA SystemVue


4

NoiseDensity

NDensity=31.62e-12W [NDensity]

NDensityType=Constant noise density

A1 {AddNDensity@Data Flow Models}

DeModI

Amp

FreqPhase

Q

FCarrier=80e6Hz

OutputType=I/Q

D3 {Demodulator@Data Flow Models}

RF_Rx

Subnetwork3 {RF_Rx}

Re

Im


FBMC_Rx

Poly Phase

OversampleRatio=2 [OversampleRatio]

MappingType=4 [MappingType]

FilterCoef=(3x1) [-0.972; 0.707; -0.235…


ActiveSubcAlloc=(2x2) [-128,-1; 0,127]

NumSubc=256 [NumSubc]

Subnetwork2 {PPN FFT Receiver}

Bus=NO

Data Type=Envelope Signal

RF_Signal

Bus=NO

Data Type=Envelope Signal

BB_Signal {DATAPORT}

IN OUT

LO

TOIout=1.0e17W

SOIout=1.0e17W

Sideband=Lower

NoiseFigure=0 [NoiseFigure_Mixer]

EnableNoise=YES

ConvGain=0

M3

SampleRate=100e+6Hz [IF_SamplingRate]

Power=0dBm

Frequency=975e+6Hz [RF_Freq-IF_Freq]

O1

PassAtten=0.02

PassBandwidth=5e+6Hz [BandWidth]

FCenter=25e+6Hz [IF_Freq]

F1 {BPF_Butterworth@Data Flow Models}

Amplif ier

RefR=50Ω

GCType=none [GCType_IFGain]

NoiseFigure=0 [NoiseFigure_IFGain]

Gain=1 [IF_Gain]

A1

Amplif ier

RefR=50Ω

GCType=none [GCType_RFGain]

NoiseFigure=0 [NoiseFigure_RFGain]

Gain=1 [RF_Gain]

A2

LNA Characteristic

• Gain

• Noise Figure

• Compression

Phase

Noise

RF/Analog Modeled Effects

• Multipath

• Path Loss

• LNA NF

• LO Phase Noise

• ADC, Clock Jitter

BB Modeled Effects

• Baseband algorithm

performance Add

Noise

Page

Baseband & RF cross domain simulation

EEsof EDA SystemVue


5

Spe c t rum A nalyzer

SpecRxIn


SpecRxOut

123SigRxIn

123SigRxOut

NoiseDensity

Noise_Power

Attenuation

Attenuation=54 [Atten]

Subnetwork1 {Attenuation}

1 1 0 1 0

DataPattern=PN15

B2 {DataPattern@Data Flow Models}

TEST

REF


Re

ImFc

CxEnv

E2 {EnvToCx@Data Flow Models}


SpecRxWnoi

ModOUT

QUADOUT

FreqPhaseQ

IAmp

InitialPhase=0°

FCarrier=81e+9Hz [FCarrier]

InputType=I/Q

RF_Link

SYS

BPSK, QPSK, ..., up to 4096-QAM8-PSK, 16-PSK, 16-APSK, 32-APSK

16-Star QAM , 32-Star-QAM, and Cus tom APSK

Data Pay loadPreambleId le

Fram e Struc ture

Spreading Code

Generator

X

D ig it a l M ode m Source

f o r L ine a r M odu lation

DSSS Sy s tem

Payload_ModType=16-QAM [Payload_ModType]

Preamble_ModType=BPSK [Preamble_ModType]

Dec ision

Dev ice

Feedward

Fi l ter-

-

Feedback

Fi l ter

Dec is ion Feedbac k Equal izer

Fas t Com putation Algori thm

CIR--->DFE c oeffic ients

D ig it a l M ode m R e ceiver

TrackingAlgorithm=LMS

FreqSync_Mode=CIR Corr

FrameSync_Algorithm=DiffCorr

{DigMod_ReceiverL_FastDFE}

Baseband

Source

Baseband

Receiver

BER &

FER

DATAFLOW

SIMULATION

R I

L

IP1dB=5dBmLO=7dBm

ConvGain=0dBMixer_1 {MIXER_BASIC}

PhaseN=(4) [-60; -80; -100; -96]dB

Pwr=7dBmF=60750MHz [3*FTXIF]LO7 {PwrOscillator}

Fhi=20375MHz [FTXIF+CS/2]

Flo=20125MHz [FTXIF-CS/2]N=3

IL=0.01dB

BPF_Butter_9 {BPF_BUTTER}

OP1dB=8dBm [RXIFOP1dB]NF=10dB [RXIFNF]

G=4dB [RXIFG]RFAmp_2 {RFAMP}

OP1dB=4dBm

NF=26.16dBG=0dB

RFAmp_5 {RFAMP}

ZO=50ΩRECEIVEROUT {*OUT}

Fhi=86.5GHz

Flo=80.5GHzN=5

IL=0.01dB

BPF_Butter_8 {BPF_BUTTER}

IP1dB=100dBm

L=1dBAttn_4 {ATTN_NonLinear}

Fhi=86GHzFlo=81GHz

N=3IL=0.01dB

BPF_Butter_6 {BPF_BUTTER}Source1=FTXRF MHz at -12 dBm, BW: CS MHzTX_IF_IN {MultiSource}

OP1dB=4dBm [RXLNAOP1dB]

NF=8dB [RXLNANF]G=22dB [RXLNAG]RFAmp_1 {RFAMP}

SpectraSys RF Modeling

RF SYSTEM

ANALYSIS

ADS Cosim

ADS RF Modeling

Page

Verification Test Benches (VTB) System Designer’s perspective: 3 levels of lifecycle validation

Page 6

MATLAB

.m models

C++

Schematics

Waveforms

1 Compare Algorithms

Vs. SV Libraries

• Validate anywhere in the R&D lifecycle

• Same measurement IP throughout

• Unified, cross-platform approach 3 Connect to live

Test & Measurement

T&M leverage

Sources,

Analyzers,

89600 VSA,

Much more

Ongoing

Baseband + RF

Integration 2

Create Custom VTBs

for RF Team to validate early using

realistic signals

Return path:

Troubleshoot & Document

- post-process VTB data

- validate with SystemVue using

RF models (X-params, FCE)

- or, deeper dive w/ true, live co-sim

EEsof EDA SystemVue ©Keysight

Technologies

Page

Use BB Model to RF Simulation

EEsof EDA SystemVue ©Keysight

Technologies

7

Page

Where Cross-Domain Simulation Approach Need for 5G?

EEsof EDA SystemVue


8

Page

Full Duplex Communication Radio

EEsof EDA SystemVue


9

f2

Backhaul on radio

access frequencies

Point-to-Point links

or WiFi STA 2

f1 f2

Interference

Self Interference

BTS

STA 1

Small Cell

– The devices transmit and

receive signals

simultaneously at the

same frequency

– The new breakthrough in

wireless communications

– Theoretically double the

spectral efficiency

– Self interference

cancellation need to be

addressed at both

baseband and RF domain

Page

Different Tools Used in Different Domains

EEsof EDA SystemVue


10

– Electro magnetic simulation

– RF circuit simulation

– Baseband algorithm verification

– System level simulation and performance evaluation

Hybrid transformer

* Full duplex transceiver chain example (image from : DUPLO project # 316369, doc: D2.1)

Electrical balance

Dual polarized antenna

Variable delay and gain Adaptive algorithms

Reference PHY IPs

• WIFI, LTE/A, Future 5G

Page

Full Duplex Transceiver Modelling

EEsof EDA SystemVue


11

Required Block Set

A to D D_I

A_out

D_Q

EnableExtJitter=NO

NyquistZone=1

CenterFreq=0 Hz

UserDigitalFormat=Twos-complement

UserInputSpan=2 V

UserCommonModeOffset=0 V

UserMaxSR=1e12 Hz

UserMinSR=0 Hz

UserNBits=8

UserModel=

ModelDirType=Default

Model=User specified model

A1 {AtoD_ADI@Data Flow Models}

D to A

HarmonicDistortion=None

DNL=0.0

INL=0.0

RJrms=0.0 s

RepeatOutput=1

InputDigitalFormat=Twos-complement

VRef=1.0 V

NBits=8

D1 {DtoA@Data Flow Models}

Fc

CxEnv

E1 {EnvToCx@Data Flow Models}

Amplifier

RefR=50 Ω

GCType=none

NoiseFigure=0

Gain=1

GainUnit=voltage

A2 {Amplifier@Data Flow Models}

ShowAdvancedParams=NO

RefR=50 Ω

NDensity=0 W

RefClock=

PN_Type=Random PN

PhaseNoiseData=

RandomPhase=NO

Phase=0.0 °

Power=.010 W

Frequency=1000000 Hz


MATLAB_Script

M1 {MATLAB_Script@Data Flow Models}

Env

OutputFc=Center

A3 {AddEnv@Data Flow Models}

TEST

REF

BitsPerFrame=100

StartStopOption=Auto

B1 {BER_FER@Data Flow Models}

Link Adaptation & HARQ Keysight EEsof EDA

November 14, 2014

Page

Motivation

• Varying radio channel

- Time variant with Doppler spread

- Frequency selective delay spread

- Interference

• How to tackle?

Exploit the channel variation prior to transmission

- Link adaption: set transmission parameters to handle radio channel variation

Handle the channel variation after transmission

- Hybrid ARQ: retransmission request of erroneously received data

EEsof EDA SystemVue


2

Page

Adaptive Modulation and Coding

EEsof EDA SystemVue


3

LTE-A DL 2x2 MIMO Throughput, Extended Vehicle Channel, AMC enabled

Simulation Results with Ideal Receiver Design

Page

Measurement Based Throughput Evaluation

EEsof EDA SystemVue


4

Page

How to adapt to channel variation?

EEsof EDA SystemVue


5

• Periodic reporting: PUCCH(Physical Uplink Control Channel)

• Aperiodic reporting: PUSCH(Physical Uplink Shared Channel)

CQI

IndexModulation Coding

0 QPSK 1/3

1 QPSK 1/2

2 16QAM 1/2

3 64QAM 1/2

x x x

x x x

* Adaptive modulation and coding can be used to adjust the modulation scheme and coding rate, and thus the data rate,

to match the instantaneous channel conditions.

Decide MCS

Predict feedback

Schedule feedback

Adapt feedback rate

CQI Quantize

DOWNLINK

UPLINK CQI

Measure SNR

Base

Station

Mobile

Station

Page

What affect CQI Reporting Level?

EEsof EDA SystemVue


6

• Channel, noise and interference level

• Performance of receiver (e.g. noise figure of analog front end, performance of the

DSP modules)

Page

Model Based Simulation

EEsof EDA SystemVue


7

ModOUT

QUAD

OUT

Freq

Phase

Q

I

Amp


InputType=I/QM1

SampleRate=7.68e+6Hz [SamplingRate]

Power=1W

Frequency=2e+9Hz [FCarrier]

O2

Re

Im

C1

ModOUT

QUAD

OUT

Freq

Phase

Q

I

Amp


InputType=I/Q

M3

DeModI

Amp

Freq

Phase

Q


OutputType=I/Q

D2

DeModI

Amp

Freq

Phase

Q


OutputType=I/QD1

NoiseDensity



A1

Re

Im

R2

Re

Im

R1

NoiseDensity


NDensityType=Constant noise densityA2

Re

Im

C2

MIMOChannel

Velocity=2.7 [Velocity]

ModelType=Extended_Vehicular_A

CorrelationType=Low [CorrelationType]

AntennaConfig=TR_2x2L1

Frame

UE1_RawBits

UE1_ChannelBits

UE1_M odSymbols

UE2_M odSymbols

UE3_M odSymbols

UE4_M odSymbols

UE5_M odSymbols

UE6_M odSymbols

PDCCH_M odSymbols

PHICH_M odSymbols

PCFICH_M odSymbols

PBCH_M odSymbols

SSS_M odSymbols

PSS_M odSymbols

DataOutUE1_HARQ_BitsUE1_TBS

UE1_PMIUE1_CQI

LTE_A

DL

Baseband

Receiver

UE1_CQIToMCS=(1x16) [0,0,0,2,4,6,8,11,1…

UE1_SNRToCQI=(1x15) [-4,-0.4,1.4,3.8,5.…

UE1_SNRFilterAlpha=0.01

UE1_SNREstimatorMode=Ideal

UE1_AMC_Delay=4 [UE1_AMC_Delay]

UE1_AMC_Enable=YESUE1_RB_Alloc=(1x2) [0,25] [UE1_RB_Alloc]

LTE_A_DL_Rcv_1

1 1 0 1 0

DataPattern=PN9


1 1 0 1 0

DataPattern=PN9


UE1_Data

CQI_Bits

frm _TD

frm _FD

UE1_M odSymbols

UE1_ChannelBits

SC_Status

HARQ_Bits

LTE_A

DL

Src

CSIRS_Enable=NO

UE1_CQIToMCS=(1x16) [0,0,0,2,4,6,8,11,1…

UE1_AMC_Delay=4 [UE1_AMC_Delay]

UE1_AMC_Enable=YES [UE1_AMC_Enable]

UEs_TransMode=(1x6) [2,1,1,1,1,1]

LTE_A_DL_Src_1 {LTE_A_DL_Src@LTE Advanced Models}

Fading

channel

Implement dynamic feedback mechanism for

• Hybrid ARQ

• CQI

• Transport block size information

Define link level system parameters

• FDD/TDD

• Transmission Mode

• Bandwidth etc…

Map CQI to MCS LTE

ThroughputCRC

TBS

StatusUpdatePeriod=10

SubframeStop=2000 [NumSimSubframes]

SubframeStart=10

L2 {LTE_Throughput@LTE 8.9 Models}

Throughput measurement

Page

HARQ Process

EEsof EDA SystemVue


8

Hybrid Automatic Repeat reQuest

– Protocol : the number of HARQ retransmissions

targeted by HARQ protocol

– MAC : HARQ is lower part of the MAC entity. If a

radio block fails due to the CRC evaluation, a

retransmission is issued

– PHY : L1 is used for signaling to indicate need for

retransmission

– Using different mode between

• UL / DL

• FDD / TDD

Transport block

CRC attachment

Code block segmentation

Code block CRC attachment

Channel coding

Rate matching

Code block

attachment

Data and control

multiplexing

Channel

coding

CQI

Channel Interleaver

Channel

coding

RI

Channel

coding

ACK/

NACK

* Transport channel processing

How to implement this behavior in link level simulation?

Page

HARQ Modeling Example

EEsof EDA SystemVue


9

LTE_A_DL_ChannelCoder

LTE

CodeBlkSeg

CodeBlockSegmentation

LTE

CRCENCODER

CRC_Length=CRC_24A

L2

[ ]D ynamic

# rows # cols

Format=ColumnMajor

D1

TBS

LTE

TurboECODER

L3

MATCH

Rate

LTE

DataIn

ProcNum

RSN

TBS

Qm

NIR

NL

G

DataOut

LinkDir=DL

RV_Sequence=(1x4) [0,1,2,3]

MaxHARQTrans=4 [MaxHARQTrans]

NumHARQ=8 [NumHARQ]

L4

Bus=NO

Data Type=Integer Matrix

Direction=Output

PORT=2

DataOut

Bus=NO

Data Type=Integer

Direction=Output

PORT=3

Qm

Optional=YES

Bus=NO

Data Type=Integer

Direction=Input

PORT=4

HARQ_Bits

Bus=NO

Data Type=Integer

Direction=Input

PORT=1

DataIn

M2

LOGIC

NOT

Logic=NOT

L1

LimiterType=linear

Top=1

Bottom=0

K=1

L5

LTE

SCRAMBLER

PDSCH_MCH=PDSCH

q=0 [q]

n_RNTI=0 [n_RNTI]

CellID_Group=0 [CellID_Group]

CellID_Sector=0 [CellID_Sector]

LinkDir=DL

Scrambler

Optional=YES

Bus=NO

Data Type=Integer

Direction=Input

PORT=5

CQI_Bits

Controller

LTE_A

HARQ

HARQ_Bits

ProcNum

RSN

TBS

Qm

Msymb

NIR

NL

G

CQI_Bits

DMRS_NumAntPorts=1 [DMRS_NumAntPorts]

UE_TransMode=TM 1:Single Ant Port(por…

HARQ_Controller

Page

Simulation Technique

– Real world systems (ex: AMC, HARQ) may involve dynamic behavior that cannot be

modeled under SDF(synchronous data flow) semantics

– The number of samples consumed and produced for each execution of a

DDF(dynamic data flow) block can change dynamically at runtime

EEsof EDA SystemVue


10

Dynamic Data Flow

[ ]Dynamic

# rows # cols

Format=ColumnMajor

D1

the consumption rate can change dynamically at runtime

Dynamic connection : # of M x N samples M x N

N M

Page

Demo & Discussion

– Use LTE-A_DL_AMC example

– Review Transmitter and Receiver Blocks

– Review fading channel model parameters

– Review throughput simulation result using graph

– Show HARQ process

– Discuss about dynamic data flow

EEsof EDA SystemVue


11

Carrier Aggregation and Dual Band DPD

Keysight EEsof EDA

November 14, 2014

Page

Carrier Aggregation

• Wider bandwidth transmission using carrier aggregation (CA) to support higher

data rate

• Bandwidth of 1.4, 3, 5, 10, 15 or 20 MHz, maximum of five component

carriers(CC) up to 100 MHz

• Contiguous and non-contiguous

• TDD and FDD

• Intra-band and Inter-band

20 MHz LTE terminal

LTE-Advanced terminal, 100MHz

(a) Contiguous carrier aggregation

… …

(b) Non-contiguous carrier aggregation

20 MHz LTE terminal

LTE-Advanced terminal, 100MHz

EEsof EDA SystemVue


Page

MAC and Physical Layer for CA

EEsof EDA SystemVue


MUX UE1 MUX UE2

HARQ

TB

SCHEDULING MAC

PHY

Scheduling of data

on multiple CCs

HARQ per CC

PDCCH, HARQ

ACK/NACK & CSI

for multiple CC

HARQ HARQ

TB2 TB1

UE1, R10 UE2, R8

PCC SCC

There will be 1 TB per CC unless spatial multiplexing is used

Logical Channel

Transport Channel

Page

CA Modeling for Link Level Simulation

EEsof EDA SystemVue


BER

CC2 @ LTE-A PHY LTE-A BB Receiver @ CC1

CC1 @ LTE-A PHY LTE-A BB Receiver @ CC1

Re

Im

R2 {Rec tToCx @Data Flow M odels }

Re

Im

R1 {Rec tToCx @Data Flow M odels }

A

Bloc k Siz es =(1x 2) [1 ,1] [[1 ,1]]

A3 {As y nc Com m utator@Data Flow M odels}

[ ] Dynam ic

# r ows # cols

Form at=Colum nM ajor

D2 {Dy nam ic Unpac k _M @Data Flow M odels}

1 1 0 1 0

DataPattern=PN9

B6 {DataPattern@Data Flow M odels}

OutputTim ing=EqualToInput

N=90000 [10*CC1_UE1_Pay load+10*CC2_UE1_Pay load]

D4 {Delay @Data Flow M odels}

DeModI

Am p

Fr eq

Phase

Q

FCarrier=2.594e+9 Hz [FCarrier1]

OutputTy pe=I/Q

D1

DeModI

Am p

Fr eq

Phase

Q


OutputTy pe=I/Q

D3

SignalCom biner

out put

com bined

OutputSam pleRate=61.44e+6

OutputSam pleRateOption=Us er Defined

OutputFc =2.606e+9 [FCarrier2]

Bandwidth=61.44e+6 [Sam pl ingRate]

Fc =2.606e+9 [FCarrier2]

Sam pleRate=61.44e+6 [Sam pl ingRate]

S2 {SignalCom biner@Data Flow M odels}

FcChange

Bandwidth=0 Hz

OutputFc =2.594e+9 Hz [FCarrier1]

E2 {Env Fc Change@Data Flow M odels}

FcChange

Bandwidth=0 Hz

OutputFc =2.606e+9 Hz [FCarrier2]

E1 {Env Fc Change@Data Flow M odels}

M ax im um Order=1000

StopRipple=80

StopBandwidth=10e+6 Hz [CC2_BW]

Pas s Ripple=0.1

Pas s Bandwidth=9e+6 Hz [CC2_Trans BW]

FCenter=2.606e+9 Hz [FCarrier2]

F1 {BPF_Park s M c Cle l lan@Data Flow M odels}

SignalCom biner

out put

com bined



OutputFc =2.594e+9 [FCarrier1]

Bandwidth=61.44e+6 [Sam pl ingRate]

Fc =2.594e+9 [FCarrier1]

Sam pleRate=61.44e+6 [Sam pl ingRate]


M ax im um Order=1000

StopRipple=80

StopBandwidth=10e+6 Hz [CC1_BW]

Pas s Ripple=0.1

Pas s Bandwidth=9e+6 Hz [CC1_Trans BW]

FCenter=2.594e+9 Hz [FCarrier1]

F2 {BPF_Park s M c Cle l lan@Data Flow M odels}

Fr ame

UE1_RawBits

UE1_ChannelBits

UE1_M odSym bols

UE2_M odSym bols

UE3_M odSym bols

UE4_M odSym bols

UE5_M odSym bols

UE6_M odSym bols

PDCCH_M odSym bols

PHI CH_M odSym bols

PCFI CH_M odSym bols

PBCH_M odSym bols

SSS_M odSym bols

PSS_M odSym bols

Dat aOutUE1_HARQ _BitsUE1_TBS

UE1_PMIUE1_CQI

LTE_A

DL

Bas eband

Rec eiver

LTE_A_DL_Rc v _1

Fr ame

UE1_RawBits

UE1_ChannelBits

UE1_M odSym bols

UE2_M odSym bols

UE3_M odSym bols

UE4_M odSym bols

UE5_M odSym bols

UE6_M odSym bols

PDCCH_M odSym bols

PHI CH_M odSym bols

PCFI CH_M odSym bols

PBCH_M odSym bols

SSS_M odSym bols

PSS_M odSym bols

Dat aOutUE1_HARQ _BitsUE1_TBS

UE1_PMIUE1_CQI

LTE_A

DL

Bas eband

Rec eiver

LTE_A_DL_Rc v _2

TEST

REF

Bi ts PerFram e=90000 [BER_Sam pleStart]

StartStopOption=Sam ples

B3 {BER_FER@Data Flow M odels }

LTE

DL_EVM

Dis abled: OPEN

CC1 {LTE_DL_EVM @LTE 8.9 M odels }

LTE

DL_EVM

Dis abled: OPEN

CC2 {LTE_DL_EVM @LTE 8.9 M odels }Noise

Density

NDens i ty =21.08e-12 W [NDens i ty]

NDens i ty Ty pe=Cons tant no is e density

A1

SignalCom biner

out put

com bined



OutputFc =2.6e+9 [FCarrier]

Bandwidth=(1x 2) [61.44e+6,61.44e+6]

Fc =(1x 2) [2 .594e+9,2.606e+9] [[FCarrier1 FCarrier2]]

Sam pleRate=(1x 2) [61.44e+6,61.44e+6]


Re

Im

C2

1 1 0 1 0

DataPattern=PN9


Offs et=-5000 [-CC1_UE1_Pay load]

nWri te=4000 [CC2_UE1_Pay load]

nRead=9000 [CC1_UE1_Pay load+CC2_UE1_Pay load]

C4 {Chop@Data Flow M odels }

Sam pleRate=61.44e+6 Hz [CC2_Sam pl ingRate]

Power=1 W

Frequenc y =2.606e+9 Hz [FCarrier2]

O1

ModO UT

Q UAD

O UT

Fr eq

Phase

Q

I

Am p


InputTy pe=I/Q

M 1

UE1_Data

CQ I _Bits

f r m _TD

f r m _FD

UE1_M odSym bols

UE1_ChannelBits

SC_St atusHARQ _Bits

LTE_A

DL

Src

CSIRS_Enable=NO

UE1_AM C_Enable=NO

CC2_Src

Re

Im

C1

ModO UT

Q UAD

O UT

Fr eq

Phase

Q

I

Am p


InputTy pe=I/Q

M 2

1 1 0 1 0

DataPattern=PN9


Sam pleRate=61.44e+6 Hz [CC1_Sam pl ingRate]

Power=1 W

Frequenc y =2.594e+9 Hz [FCarrier1]

O2

UE1_Data

CQ I _Bits

f r m _TD

f r m _FD

UE1_M odSym bols

UE1_ChannelBits


LTE_A

DL

Src

CSIRS_Enable=NO

UE1_AM C_Enable=NO

CC1_Src

Offs et=0

nWri te=5000 [CC1_UE1_Pay load]

nRead=9000 [CC1_UE1_Pay load+CC2_UE1_Pay load]

C3 {Chop@Data Flow M odels }

Page

PUCCH Formats

EEsof EDA SystemVue


Format

TypeControl Information

Modulation

Scheme

No. of bits /

Subframe

PUCCH Format 1 (Rel 8);

1 SR (Scheduling Request) Not Applicable Not Applicable

1a HARQ ACK/NACK BPSK 1 bit

1b HARQ ACK/NACK (for MIMO) QPSK 2 bits

PUCCH Format 2;

2 CSI (Channel State Info.) QPSK 20 bits

2a CSI+HARQ ACK/NACK QPSK+BPSK 21 bits

2bCSI+HARQ ACK/NACK (for

MIMO)QPSK + BPSK 22 bits

PUCCH Format 3 (Rel 10);

3SR HARQ ACK/NACK (for

CA)QPSK 48 bits

• ACK/NACK for each carrier separately (1b)

• ACK/NACK for each carrier on single

PUCCH (format 3)

LTE-Advanced carrier aggregation

DL: 300 Mbps

UL: 50 Mbps

Page

LTE-Advanced CA signals

EEsof EDA SystemVue


Scenario number

Deployment scenario Transmission BWs of LTE-A carriers

# of LTE-A component carriers Bands for LTE-A

carriers Duplex modes

1 Single-band contiguous spec. alloc. @ 3.5GHz band for FDD

UL: 40 MHz

DL: 80 MHz

UL: Contiguous 2x20 MHz CCs DL: Contiguous 4x20 MHz CCs

3.5 GHz band FDD

2 Single-band contiguous spec. alloc. @ Band 40 for TDD

100 MHz Contiguous 5x20 MHz CCs Band 40 (2.3 GHz)

TDD

4

Single-band, non-contiguous spec. alloc. @ 3.5GHz band for FDD

UL: 40 MHz

DL: 80 MHz

UL: Non-contiguous 1x20 + 1x20 MHz CCs DL: Non-contiguous 2x20 + 2x20 MHz CCs

3.5 GHz band FDD

Re

Im

Env

1 1 0 1 0

1 1 0 1 0

UE1_Dat a

HARQ _Bit s

f r m _TD

f r m _FD

UE1_M odSym bols

UE1_ChannelBit s

SC_St at usUE1_PM I

LTE_A

DL

Src

UEs_n_SCID=0;0;0;0;0;0 [[0, 0, 0, 0, 0, 0]]

UserDefinedAntMappingMatrix=NO

LTE_A_DL_Src_2

FcChange

Spect rum Anal yzer

CCDF

Stop=10ms

Start=0s

CCDF_CA

CCDF

Stop=10ms

Start=0s

WoCA

ModOUT

QUAD

OUT

Freq

Phas e

Q

I

Am p

Re

Im1 1 0 1 0

1 1 0 1 0

UE1_Dat a

HARQ _Bit s

f r m _TD

f r m _FD

UE1_M odSym bols

UE1_ChannelBit s

SC_St at us

UE1_PM I

LTE_A

DL

Src

UEs_n_SCID=0;0;0;0;0;0 [[0, 0, 0, 0, 0, 0]]


LTE_A_DL_Src_4

ModOUT

QUAD

OUT

Freq

Phas e

Q

I

Am p

Re

Im

1 1 0 1 0

1 1 0 1 0

UE1_Dat a

HARQ _Bit s

f r m _TD

f r m _FD

UE1_M odSym bols

UE1_ChannelBit s

SC_St at usUE1_PM I

LTE_A

DL

Src

UEs_n_SCID=0;0;0;0;0;0 [[0, 0, 0, 0, 0, 0]]


LTE_A_DL_Src_3

ModOUT

QUAD

OUT

Freq

Phas e

Q

I

Am p

Re

Im

ModOUT

QUAD

OUT

Freq

Phas e

Q

I

Am p

1 1 0 1 0

1 1 0 1 0

UE1_Dat a

HARQ _Bit s

f r m _TD

f r m _FD

UE1_M odSym bols

UE1_ChannelBit s

SC_St at us

UE1_PM I

LTE_A

DL

Src

UEs_n_SCID=0;0;0;0;0;0 [[0, 0, 0, 0, 0, 0]]


LTE_A_DL_Src_1

20 MHz

CCs 80 MHz

total

Page

FDD and TDD LTE-Advanced Carrier Aggregation

EEsof EDA SystemVue


Scenario Link Configuration PAPR of single CC,

before aggregation

PAPR with CCs,

after aggregation

Scenario 1 FDD DL 4x20 MHz CCs 8.45 dB 9.98 dB

Scenario 2 TDD DL 5x20 MHz CCs 9.17 dB 11.71 dB

Scenario 4

FDD DL 2x20+2x20MHz 8.38 dB 9.58 dB

FDD UL 20 + 20MHz 5.79 dB 6.86 dB

Scenario 1 FDD DL

Scenario 2

TDD DL

Scenario 4 FDD DL Scenario 4 FDD UL

Page

Intra-Band Carrier Aggregation

EEsof EDA SystemVue


–Multiple CCs are used inside of a single frequency Band (3GPP

defined bands)

–CCs can be contiguous or non-contiguous or both if more than 2 are

used

–Some chipsets support this mode with a single receiver

Page

Inter-Band Carrier Aggregation

EEsof EDA SystemVue


– CCs are in different frequency bands

– Allows carriers to combine their spectrum assets to gain higher throughput

– More expensive to implement since UE must support 2 receivers

– Probably the most common network implementation since it optimizes the

spectrum holdings of many carriers

Page

Digital Pre-Distortion

EEsof EDA SystemVue


LINEAR

INPUT

POWER

OUTPUT

POWER

DPD pre-expanded peaks

INPUT

POWER

PA compresses peaks LINEAR

Baseband

Digital Pre-Distortion

RF

Power Amplification

Page

What does a DPD look like? (Volterra Model)

EEsof EDA SystemVue


K

k

k nznz1

)()(

Q

m

Q

m

k

l

lkkk

k

mnymmhnz0 0 1

1

1

)(),,()(

Q

m

Q

m

Q

m

mnymnymmhmnymhhnz0 0

21212

0

1110

1 21

)()(),()()()(

Volterra series pre-distorter can be described by

where

Which is a 2-dimensional summation of power series & past time envelope responses

A full Volterra produces a huge computational load.

People usually simplify it into

• Wiener model

• Hammerstein model

• Wiener-Hammerstein model

• Memory polynomial model

Page

DPD Model of Dual-band PA

EEsof EDA SystemVue


This Figure is from Ref [1] A. Bassam, M. Helaoui and F. M.

Ghannouchi, "2-D Digital Predistortion (2-D-DPD)

Architecture for Concurrent Dual-Band Transmitters," IEEE

Transactions on Microwave Theory and Techniques,

Vol. 59: Issue 10, pp. 2547-2553, October 2011.

The limitation of bandwidth of

ADCs and DACs

The rather high model complexity

due to the cross modulation of two

bands

Measure each band separately

Build DPD model of each band

considering the cross modulation of the

other band

Linearize each band separately

Challenge Approach

Page

Dual Band DPD for Inter-Band CA

EEsof EDA SystemVue


Attenuator

89600

VSA

M9381A PXI VSG and M9393A PXI VSA

RF1

RF DUT

MEASUREMENT-BASED DPD

RF2

Combiner

Download Waveform

Band X Band Y

3D Wireless Channel

Keysight EEsof EDA

November 14, 2014

Page

Motivation

– Multiple-antenna (MIMO) technology is becoming mature for wireless communications

– The many antennas for better performance; data rate and link reliability

– Challenged by increased complexity of the hardware and energy consumption

– More signal processing challenges needs to be addressed thru simulation in early

design phase

EEsof EDA SystemVue


2

Page

Channel Model Evolution

EEsof EDA SystemVue


3

3GPP Description

TR 25.966 Spatial channel model (SCM) for Multiple Input Multiple Output (MIMO) simulations

TR 36.814 Further advancements for E-UTRA physical layer aspects

TR 37.976 Measurement of radiated performance for Multiple Input Multiple Output (MIMO) and multi-antenna

reception for High Speed Packet Access (HSPA) and LTE terminals

TR 37.977 Verification of radiated multi-antenna reception performance of User Equipment (UE)

TR 36.873 3D-channel model for LTE

ICT-317669-

METIS/D1.2 Initial channel models based on measurements

Define 5G Channel Model Requirements

• Spatial consistency and mobility

• Diffuse versus specular scattering

• Very large antenna arrays

• Frequency range

• Complexity vs. Accuracy

• Applicability of the existing and proposed models on the 5G requirements

Page

MIMO Channel Model

EEsof EDA SystemVue


4

Characterized in Four Domains

time

frequency

Delay spread

• Frequency selectivity

• Coherence bandwidth

Doppler spread

• Time selectivity

• Coherence time

Angular spread

• Spatial selectivity

• Coherence distance

mnmn

stxmnurxmn

mnHstx

mnVstx

HHmnHVmn

VHmnVVmn

T

mnHurx

mnVurxM

m

nsu

tj

rjrj

F

F

aF

FtH

,,

,,

1

0,,

1

0

,,,

,,,

,,,,

,,,,

,,,

,,,

1

,,

2exp

2exp2exp

;

* Tx antenna element s to Rx element u for cluster n

Page

Coordinate Systems

EEsof EDA SystemVue


5

AoD

ZoD

LCS AoA

ZoA

LCS

GCS

GCS : Global Coordinate System

LCS : Local Coordinate System

GPP 3D Channel Model

EEsof EDA SystemVue


6

TR 36.873

Urban Micro cell

with high UE density

(3D-UMi)

Urban Macro cell

with high UE density

(3D-UMa)

Urban Macro cell with

one high-rise per sector and

300m ISD

(3D-UMa-H)

Layout Hexagonal grid, 19 micro sites,3 sectors

per site

Hexagonal grid, 19 macro sites,3

sectors per site

Hexagonal grid, 19 macro sites,3

sectors per site

UE mobility (movement in

horizontal plane) 3km/h 3km/h 3kmph

BS antenna height 10m 25m 25m

Total BS Tx Power 41/44 dBm for 10/20MHz 46/49 dBm for 10/20MHz 46/49 dBm for 10/20MHz

Carrier frequency 2 GHz 2 GHz 2 GHz

Min. UE-eNB 2D distance 10m [other values FFS] 35m 35m

UE height (hUT) in meters

general equation hUT=3(nfl – 1) + 1.5 hUT=3(nfl – 1) + 1.5 hUT=3(nfl – 1) + 1.5

nfl for outdoor UEs 1 1 1

nfl for indoor UEs nfl ~ uniform(1,Nfl) where

Nfl ~ uniform(4,8)

nfl ~ uniform(1,Nfl) where

Nfl ~ uniform(4,8) nfl ~ uniform(1,Nfl)

3)

Indoor UE fraction 80% 80% 80%

Page

Antenna Modelling Parameters

EEsof EDA SystemVue


7

Parameter Applicability Values

Number of horizontal antenna elements cross-pol (X) 2, 4, 8

co-pol (| |) 1, 2, 4, 8

Polarization slant angle cross-pol (X) +/- 450

co-pol (| |) 00

Horizontal antenna element spacing dH 0.5λ baseline (other values FFS)

Antenna element vertical radiation

pattern (dB)

Antenna element horizontal radiation

pattern (dB)

3D-UMa, 3D-UMi,

LPN deployments

3D-UMi, LPN deployments FFS:

Combining method for 3D antenna

element pattern (dB)

Maximum directional gain of an antenna

element GE,max 8 dBi

Page

Problems and Solutions

EEsof EDA SystemVue


8

Throughput

LTE-A BB Source

Tx RF

MIMOChannel

Rx RF

LTE-A BB ReceiverRe

Im

C8

ModO UT

Q UAD

O UT

Fr eq

Phase

Q

I

Am p


InputTy pe=I/Q

M8

Re

Im

C9

ModO UT

Q UAD

O UT

Fr eq

Phase

Q

I

Am p


InputTy pe=I/Q

M7

ModO UT

Q UAD

O UT

Fr eq

Phase

Q

I

Am p

FCarrier=2e+9Hz [FCarrier]InputTy pe=I/Q

M6

Re

Im

C7

ModO UT

Q UAD

O UT

Fr eq

Phase

Q

I

Am p


InputTy pe=I/Q

M5

Re

Im

C6

Sam pleRate=15.36e+6Hz [Sam pl ingRate]

Power=1W

Frequenc y =2e+9Hz [FCarrier]O1

OutputTim ing=BeforeInputN=7

D11 {Delay @Data Flow M odels}

Fc

CxEnv

E5 {Env ToCx @Data Flow M odels}

Fc

CxEnv


Fc

CxEnv


Fc

CxEnv


DeMod I

Am p

Fr eq

Phase

Q

FCarrier=2e+9Hz [FCarrier]OutputTy pe=I/Q

D2

Re

Im

R1 {Rec tToCx @Data Flow M odels}

Re

Im


DeModI

Am p

Fr eq

Phase

Q


OutputTy pe=I/Q

D7

Re

Im


Fc

EnvCx

Fc =2e+9Hz [FCarrier]

C17 {Cx ToEnv @Data Flow M odels}

1 1 0 1 0

DataPattern=PN15

B4

1 1 0 1 0

DataPattern=PN9

B2

Re

Im

C5

ModO UT

Q UAD

O UT

Fr eq

Phase

Q

I

Am p


InputTy pe=I/Q

M4

Re

Im

C4

ModO UT

Q UAD

O UT

Fr eq

Phase

Q

I

Am p


InputTy pe=I/Q

M3

Re

Im

C3

Re

Im

C2

Fc

EnvCx



Fc

EnvCx



Fc

EnvCx



Fc

EnvCx



Fc

EnvCx



Fc

EnvCx



Fc

EnvCx



NoiseDensity

NDens i ty =167.5e-12W [NDensity]NDens i ty Ty pe=Cons tant no ise density

A2

NoiseDensity

NDens i ty =167.5e-12W [NDensity]

NDens i ty Ty pe=Cons tant no ise density

A1

NoiseDensity



A4

NoiseDensity



A3

NoiseDensity



A8

NoiseDensity



A7

NoiseDensity



A5

NoiseDensity



A6

DeMod I

Am p

Fr eq

Phase

Q


OutputTy pe=I/Q

D6

DeModI

Am p

Fr eq

Phase

Q


OutputTy pe=I/Q

D8

DeModI

Am p

Fr eq

Phase

Q


OutputTy pe=I/Q

D9

DeModI

Am p

Fr eq

Phase

Q


OutputTy pe=I/Q

D4

DeModI

Am p

Fr eq

Phase

Q


OutputTy pe=I/Q

D5

DeModI

Am p

Fr eq

Phase

Q


OutputTy pe=I/Q

D3

Re

Im


Re

Im


Re

Im


Re

Im


Re

Im


1

Value=1

C10 {Cons t@Data Flow M odels}

LTE

Thr oughputCRC

TBS

Status UpdatePeriod=1

Subfram eStop=2000 [Num Subframes]

Subfram eStart=1

L1 {LTE_Throughput@LTE 8.9 M odels}

Fc

CxEnv


Fc

CxEnv


Fc

CxEnv


Fc

CxEnv


ModO UT

Q UAD

O UT

Fr eq

Phase

Q

I

Am p


InputTy pe=I/Q

M2

ModO UT

Q UAD

O UT

Fr eq

Phase

Q

I

Am p


InputTy pe=I/Q

M1

UE1_Data

CQ I _Bits

f r m _TD

f r m _FD

UE1_M odSym bols

UE1_ChannelBits


LTE_A

DL

Src

CSIRS_Enable=NO

UE1_AM C_Enable=NO

UEs _n_RNTI=(1x 6) [1 ,2,3,4,5,6]UEs _Spec i fic RS=(1x 6) [0 ,0,0,0,0,0]

UEs _Trans M ode=(1x 6) [8 ,1,1,1,1,1]

LTE_A_DL_Src_1

Fr ame

UE1_RawBits

UE1_ChannelBits

UE1_M odSym bols

UE2_M odSym bols

UE3_M odSym bols

UE4_M odSym bols

UE5_M odSym bols

UE6_M odSym bols

PDCCH_M odSym bols

PHI CH_M odSymbols

PCFI CH_M odSymbols

PBCH_M odSym bols

SSS_M odSym bols

PSS_M odSym bols

Dat aOutUE1_HARQ _BitsUE1_TBSUE1_PMIUE1_CQI

LTE_A

DL

Bas eband

Rec eiver

CSIRS_Enable=NO

UE1_AM C_Enable=NOUEs _Spec i fic RS=(1x 6) [1 ,0,0,0,0,0]

UEs _Trans M ode=(1x 6) [8 ,1,1,1,1,1]

LTE_A_DL_Rc v_1

LTEAdvance_Channel

Corre la tionM atrix OutputFlag=NO

ChannelCoeffic ientOutputFlag=NO

Us ePathLos s M odel=NOUs eIntraClus terDelay s=NO

Us eLOS=NO

Us eShadowM odel=NO

Us ePolaris e=NO

Us eFix edCDLParam eter=YES

DropInterv a l=0.05s

M SDirec tion=30M SVeloc i ty =5.4e-3 [M s Velocity]

ThetaM s=0

ThetaBs=0

Rx AntennaPatternTy pe=Om niDirectional

Rx Pos i tion_Y=(1x 8) [0 ,1,2,3,4,5,6,7]

Rx Pos i tion_X=(1x 8) [0 ,0,0,0,0,0,0,0]

Num berofRx=8

Tx RotationAngle=0Tx AntennaPatternTy pe=Om niDirectional

Tx Pos i tion_Y=(1x 8) [0 ,1,2,3,4,5,6,7]

Tx Pos i tion_X=(1x 8) [0 ,0,0,0,0,0,0,0]

Num berofTx=8

Seed=10

ChannelL ink Direc tion=Downlink

Sam pleRate=15.36e+6Hz [Sam pl ingRate]CarrierFrequenc y =2e+9Hz

LTEAdv anc eSc enarioTy pe=InH

L2 {LTEAdv anc e_Channel@M IM O Channel Models}

% Channel matrix

Channel = eye(8);

ChIn = zeros(8,1);

ChOut = zeros(8,1);

for i=1:8

ChIn(i) = input{i};

end

ChOut = Channel*ChIn;

% Add your script here

for i=1:8

output{i} = ChOut(i);

End

Page

Simulation Parameters Snap Shots

EEsof EDA SystemVue


9

Coordinated Multi-Points Keysight EEsof EDA

November 14, 2014

Page

Motivation

– CoMP is a wide range of techniques that enable dynamic coordination with

multiple geographically separated eNBs

– To enhance the overall system performance

– To utilize the resources more effectively and improve the end user service

quality

– Cell edges are the most challenging as low signal level and interference from

neighboring eNBs

EEsof EDA SystemVue


2

Page

Coordinated Multi-Points

EEsof EDA SystemVue


3

Exchange of feedback report thru backhaul

eNodeB RRE

UE1 UE2

Cell

eNodeB Cell

UE RRE

Figure. Coordinated beamforming / scheduling

Figure. Joint Processing or Dynamic cell selection

Dynamic points selection

Coherent/Non-coherent transmission

PMI/CQI/RI feedback extensions

Page

Dynamic Point Selection Simulation Example

EEsof EDA SystemVue


4

BER

LTE-A BB Receiver

Re

Im


DeModI

Amp

FreqPhase

Q


OutputType=I/Q

D3

NoiseDensity



A1

Re

Im

C2

ModOUT

QUADOUT

Freq

PhaseQ

IAmp


InputType=I/Q

M1


Power=1W


O1

Re

Im

C1


Power=1W


O2

ModOUT

QUADOUT

Freq

PhaseQ

IAmp


InputType=I/Q

M2

Env

OutputFc=Center

A2 {AddEnv@Data Flow Models}

ChannelOut

Taps


C5

Logic=NOT

L1 {Logic@Data Flow Models}

OutputTiming=BeforeInput

N=7 [CQI_Delay-1]

D1 {Delay@Data Flow Models}

ChannelOut

Taps


C3 {CommsChannel@Data Flow Models}

OutputTiming=BeforeInput

N=7

D2 {Delay@Data Flow Models}

UE1_Dat a

CQ I _Bit s

f r m _TD

f r m _FD

U E 1_M odSym bols

U E 1 _ChannelBit s

SC_St at us

HARQ _Bit s

LTE_A

DL

Src

LTE_A_DL_Src_1

UE1_Dat a

CQ I _Bit s

f r m _TD

f r m _FD

U E 1_M odSym bols

U E 1 _ChannelBit s

SC_St at us

HARQ _Bit s

LTE_A

DL

Src

LTE_A_DL_Src_2

Fr am e

U E 1_RawBit s

U E 1 _ChannelBit s

U E 1_M odSym bols

U E 2_M odSym bols

U E 3_M odSym bols

U E 4_M odSym bols

U E 5_M odSym bols

U E 6_M odSym bols

P D C C H_M odSym bols

P H I CH_M odSym bols

P C F I CH_M odSym bols

P B C H_M odSym bols

S S S_M odSym bols

P S S_M odSym bols

Dat aO utU E 1_HARQ _Bit sUE1_TBS

UE1_PM IUE1_CQ I

LTE_A

DL

Baseband

Receiver

LTE_A_DL_Rcv_1

1 1 0 1 0

DataPattern=PN9


r ef

t est LTE_A

BER_FER

L3 {LTE_A_BER_FER@LTE Advanced Models}

LTE

ThroughputCRC

TBS

L2 {LTE_Throughput@LTE 8.9 Models}

1 1 0 1 0

DataPattern=PN9


1 1 0 1 0

DataPattern=PN9


CQI

Feedback

Different

Cell-ID Different

Channel

Path

Throughput

Measurement

BS1

BS2

UE1

Page

Throughput Measurement Result for DPS

EEsof EDA SystemVue


5

Single

Point

Two

Points

Throughput Gain

Page

Signaling support for CoMP

– Release 8/9: Cell-specific RS (CRS) for up to 4 layer SM

– Release 10: Channel state information reference signal (CSI-RS) came with 8-layer

spatial multiplexing

– Release 11: Multipoint CSI feedback framework

– Release12: Enhancements to CSI from terminals to the network

– Beyond: Further extensions

EEsof EDA SystemVue


6

Page

Improved Interference Suppression

– Interference rejection combining(MMSE-IRC) receiver (Rel 11)

– Use multiple receiver antenna on the mobile terminal

– Suppress interference arriving from adjacent cell

– Improve throughput performance, mainly near cell boundaries

EEsof EDA SystemVue


7

UE1

UE2

Serving Cell Interfering Cell

MMSE-IRC

Receiver

3GPP TR 36.829 v11.1.0

Page

Algorithm Validation

EEsof EDA SystemVue


8

MMSE-IRC

LTE_A

DL DMRS

UE_SpecificRS=Port 7 [UEs_SpecificRS(1)]

n_SCID=0 [UE1_n_SCID]

NumOfLayers=1 [UEs_NumOfLayers(1)]

RB_Alloc=(1x2) [0,8] [UE1_RB_Alloc]

RB_AllocType=StartRB + NumRBs

RB_Gap=Ngap1 [RB_Gap]

RB_MappingType=Localized [RB_MappingType]

CellID_Group=0 [CellID_Group]

CellID_Sector=0 [CellID_Sector]

CyclicPrefix=Normal [CyclicPrefix]

Bandwidth=BW 5 MHz [Bandwidth]

FrameMode=FDD [FrameMode]

DMRS {LTE_A_DL_DMRS@LTE Advanced Models}

DMRS

input

Coef

LTE_A

DL_ChEstimator

SubframeIgnored=1 [SubframeIgnored]

Fmax=100Hz [Fmax]

Tmax=1e-6s [Tmax]

SNR=15 [SNR]

MMSE_RBWinLen=3 [MMSE_RBWinLen]

ChEstimatorMode=Linear [ChEstimatorMode]

UE_SpecificRS=Port 7 [UEs_SpecificRS(1)]

UE_TransMode=TM 8:Dual-Layer transmissi…

RB_Alloc=(1x2) [0,8] [UE1_RB_Alloc]

RB_AllocType=StartRB + NumRBs

RB_Gap=Ngap1 [RB_Gap]

RB_MappingType=Localized [RB_MappingType]

CyclicPrefix=Normal [CyclicPrefix]

NumRxAnts=Rx1 [NumRxAnts]

NumOfLayers=1 [UEs_NumOfLayers(1)]

CRS_NumAntPorts=CRS_Tx1 [CRS_NumAntPorts]

Bandwidth=BW 5 MHz [Bandwidth]

SpecialSF_Config=Config 0

TDD_Config=Config 0 [TDD_Config]

FrameMode=FDD [FrameMode]

H_DataIn

H_PSCH

H_SSCH

H_PBCH

H_PDCCH

H_PCFICH

H_PHICH

H_Data_UE6

H_Data_UE5

H_Data_UE4

H_Data_UE3

H_Data_UE2

H_Data_UE1

LTE_A_DL

MIMO

DemuxCIR

CSIRS_PowerRatio=0 [CSIRS_PowerRatio]

L1 {LTE_A_DL_MIMO_DemuxCIR@LTE Advanced Models}

MATLAB_ScriptCoef

input

DMRS

M2 {MATLAB_Script@Data Flow Models}

New

enhanced

algorithm

Legacy MMSE Algorithm

FILL

HOLES

Page

Demo & Discussion

– Use LTE-A_DL_DPS example

– Review Transmitter and Receiver Blocks

– Review fading channel model parameters

– Review throughput simulation result using graph

– Discuss why CoMP is important for 4G and 5G research

EEsof EDA SystemVue


9

Page

Try SystemVue

– Obtain a “FREE” 45-day evaluation copy of SystemVue and explore how SystemVue

can help with early 5G systems exploration and evaluation

• http://www.keysight.com/find/eesof-systemvue-evaluation

– Early collaboration on 5G modem architectures and systems

• Contact your Keysight sales representative

• Or, e-mail to: [email protected]

• [email protected]

EEsof EDA SystemVue


1

http://www.keysight.com/find/eesof-systemvue-evaluation





mailto:[email protected]




Page

Resources

• SystemVue : www.keysight.com/find/eesof-systemvue

• 5G Library: www.keysight.com/find/eesof-systemvue-5g-exploration

- LTE & LTE-A : www.keysight.com/find/cellular or www.keysight.com/find/eesof-systemvue-lte-advanced

- MIMO Channel : www.keysight.com/find/eesof-systemvue-channel-builder

- Knowledge center: www.keysight.com/find/eesof-knowledgecenter

- Keysight EDA software: www.keysight.com/find/eesof

- Keysight EEsof EDA YouTube : www.keysight.com/find/eesof-videos

- FPGA Flow YouTube Video : http://youtu.be/8EmuV6EzcMQ

- ESL Applications Center: www.keysight.com/find/eesof-esl-applications-center

- ESL Design Notebook: www.keysight.com/find/eesof-esl-design-notebook

EEsof EDA SystemVue


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http://www.keysight.com/find/eesof-systemvue



http://www.keysight.com/find/eesof-systemvue-5g-exploration







http://www.keysight.com/find/cellular

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http://www.keysight.com/find/eesof-systemvue-channel-builder








http://www.keysight.com/find/eesof-knowledgecenter



http://www.keysight.com/find/eesof

http://www.keysight.com/find/eesof-videos



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