Modeling 4G & 5G Systems in SystemVue August 28, 2014

Keysight EEsof EDA

1 August 2014: We are now Keysight Technologies What remains the same?

What is different?

Technology Leadership

Enterprise 100% Focused on EM Customers

#1 in Key Markets

EM Top Opportunities are Company’s Top Priority

Same Target Markets, Products, Roadmap Same Team and Global Footprint

Corporate HQ in Santa Rosa, CA USA

Strong Position in Emerging Markets IP, Patents, Research Labs, ASIC Design

以是为本 ∙ 以德致远 © Keysight Technologies August 2014

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5G: A Broad Spectrum of Opportunity The Mobile Data Future

Today’s 2G/3G/4G NW Tomorrow’s 5G NW  Mobile data is real  Great Service in a Crowd  Works most of the time

 Amazingly Fast

ₓ

Works well some of the time

ₓ

WiFi works but not integrated

 All Things Communicating

Centralized ₓ Don’t try this and in a Seamless crowd! ₓ

Networks

Gateway to Competing NW

Consumes 2% of WW power © Keysight Technologies August 2014

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5G Wireless: Opportunities to Innovate Why this will be exciting to us: 10 GHz

1 GHz

Frequency Wavelength Microwave

10 cm

100X Efficiency (energy/bit) Reliability 99.999% 1mS Latency 100X Data Rates 100X Densification 1000X Capacity

100 GHz

mm-Wave 1 cm

1 THz

10 THz

THz

Far IR

1 mm

100 µm

1PHz

100 THz Infrared 10 µm

UV 1 µm

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

– Design – Simulate

2. New >400GB/s Fiber

– Validate

5. Hyper-Fast Data Buses 6. C-RAN & New NW Topology © Keysight Technologies August 2014

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Agenda – 4G/5G Technology Overview – 4G standards references growing into pre-5G • Link Adaptation Technique • Coordinated Multi-Points • Inter-band Carrier Aggregation and 2D Digital Pre-distortion – 5G Research Engineering Technologies • New waveform study • Shared spectrum and co-existence • Cross domain simulation • MIMO and channel • Multi-channel real time signal processing © Keysight Technologies August 2014

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4G/5G Technologies Roadmap PHYSICAL LAYER

2010

2011

4G Technology Leader Rel 10, 11

• OFDM/SCFDMA • FDD/TDD • CoMP • eICIC

2012

ANTENNA • MU-MIMO • Beamforming • MIMO channel model • Correlation, WINNERII

*ESL Perspective

SIMULATION

MEASURE

MISC.

• Dynamic Dataflow Simulation • HARQ, AMC • Distributed simulation

• GP Instrument • Minor modular adaption

• • • •

Wi-Fi Offload Small cell Backhaul Software defined radio network

• Combined external event driven control • Simulation Acceleration

• Multi-channel • Wide bandwidth • Real time FPGA

• • • •

HetNet Mobile Relay Coexistence Selfinterference cancellation

• Simulation in enterprise IT infrastructure • L1, L2 cross simulation

• Ultra High speed interface

• Integrated RF radio and antenna elements • Full-duplex radio

2013

2015

2016

• CoMP Enhance • Inter-eNB CA • Control plane overhead reduction • MTC

• FD-MIMO (TR 36.873)

• Active Array Antenna • 3D Channel Model

2017

2018

2019

2020

5G Maintain Leadership Rel 14,15,16

5GNOW Candidate • GFDM, FBMC • UFMC, BFDM F-OFDM SCMA

???

OFDM GFDM

• Massive-MIMO • mmWave Channel

???

???

Throughput(%)

2014

B4G Continuous innovation Rel 12,13

EbNo(dB)

© Keysight Technologies August 2014

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5G Enabling Devices Advanced signal processing New waveforms • •

Legacy OFDM enhancement FBMC, GFDM, UFDM

• • •

Multiple MIMO modes and beamforming Network interference suppression Adaptive channel estimation / equalization

Full duplex communications • • •

Amplifier • • •

Envelope tracking Digital predistortion Wide, multi bands

Multi-antenna • • •

Access • •

Self interference cancellation Dual polarization antenna Real time operation

Non-orthogonal multiple access Random / scheduled / hybrid

•

Multi-band

Multiple radio access technologies • •

Impedance matching Mutual coupling Multi-band, multi-RAT port sharing FD / Massive MIMO

GSM/EDGE/WCDMA/HSPA/LTE WiFi/BT/WiGig/GNSS/5G

• • •

Traditional cellular bands Sensing -> Reconfiguration -> Coexistence

LTE Figure. Spectrum Sharing and Avoid Interference © Keysight Technologies August 2014

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Co-existence with Multiple Standard Radio Interoperability of 5G with 2G/3G/4G/WLAN: GSM

LTE

FBMC

• • •

Generate multiple format signals Sweep the power of the Interferer and noise density Measure BER © Keysight Technologies August 2014

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Combining Multiple Signals

The SignalCombiner model combines multiple input signals with different sample rates, different characterization (carrier) frequencies, and different bandwidths into a single signal at the specified characterization frequency and sample rate. © Keysight Technologies August 2014

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Cross Domain Simulation August 28, 2014

Keysight EEsof EDA

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

© Keysight Technologies August 2014

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Modeling Transmitter Path Different waveform, modulation

Phase Noise

Gain, NF & Compression Characteristics

Ripple, Group Delay & BPF Characteristics

Gain, phase imbalance, IQ offset

Signal quality degraded by:

Signal quality degraded by:

• Different multi-carrier waveform • Apply different prototype filter

• PA Compression • Intermods • Spectral Spread • LO Phase Noise • BPF Filter Effects © Keysight Technologies August 2014

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Modeling Receiver Path LNA Characteristic • Gain • Noise Figure • Compression

Add Noise

Phase Noise

RF/Analog Modeled Effects • Multipath • Path Loss • LNA NF • LO Phase Noise • ADC, Clock Jitter

BB Modeled Effects • Baseband algorithm performance

© Keysight Technologies August 2014

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Tackling Multi-Domain Issue

Baseband & RF cross domain simulation

DATAFLOW SIMULATION

Baseband Receiver

Baseband Source

BER & FER

RF SYSTEM ANALYSIS

ADS RF Modeling

SpectraSys RF Modeling © Keysight Technologies August 2014

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Verification Test Benches

Analog PA

VTB

SIMULATE LOCALLY INSIDE ADS © Keysight Technologies August 2014

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Full Duplex Radio – 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

© Keysight Technologies August 2014

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Simulations

Full Duplex Transceiver Variable delay and gain

Adaptive algorithms

Dual polarized antenna Electrical balance Hybrid transformer

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

Reference PHY IPs • WIFI, LTE/A, Future 5G

– Electro magnetic simulation – RF circuit simulation – Baseband algorithm verification – System level simulation and performance evaluation © Keysight Technologies August 2014

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Full Duplex Transceiver Modelling Required Block Set

© Keysight Technologies August 2014

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MIMO and Channel August 28, 2014

Keysight EEsof EDA

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

© Keysight Technologies August 2014

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MIMO Channel Model

Characterized in Four Domains frequency

Delay spread • Frequency selectivity • Coherence bandwidth

Doppler spread • Time selectivity • Coherence time

time

Angular spread • Spatial selectivity • Coherence distance

α n ,m ,VH   Ftx , s ,V (φ n ,m )  Frx ,u ,V (ϕ n , m ) α n , m ,VV H u , s , n (t ;τ ) = ∑      a n , m , HH  m =1  Frx ,u , H (ϕ n , m ) α n , m , HV   Ftx , s , H (φ n , m ) −1 (ϕ n ,m ⋅ rrx ,u ) exp j 2πλ0−1 (φ n ,m ⋅ rtx , s ) × exp j 2πλ0 T

M

(

)

× exp( j 2πυ n , m t )δ (τ − τ n , m

)

(

)

* Tx antenna element s to Rx element u for cluster n © Keysight Technologies August 2014

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Channel Model Evolution 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-317669METIS/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

© Keysight Technologies August 2014

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Massive MIMO – The use of a very large number of service antennas operated fully coherent and adaptive – System Model : M transmit antenna with maximum S streams, K users each with a single antenna – Brings huge improvements in throughput and energy efficiency when combined with simultaneous scheduling of a large number of UEs – Originally envisioned for time division duplex(TDD), but can potentially be applied in frequency division duplex(FDD)

© Keysight Technologies August 2014

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Problems and Solutions

Channel sounding / extraction / simulation Channel impulse response

Reference transmit signal(chirp/pn)

t[𝑘] Channel sounding

channel H[z]

𝑧[𝑘]

∑

CIR

• • •

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

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

PDP (Path delay, path loss) AOA, AOD Doppler shift Channel parameters

Estimation algorithms

correlation Parameters estimation

Statistics & modeling • • •

Scenario selection Network layout Antenna parameters

• • • • •

AS AoA/AoD PAS Doppler spectrum Correlation Rician K factor

Large/Small scale parameters generation

Fading coefficient generation

Input signal

𝑥[𝑘]

¤

faded signal

𝑦[𝑘]

SystemVue Simulation © Keysight Technologies August 2014

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Problems and Solutions

Measurement and Calibration

8 CH LNA / BPF / Rubidium clock source

MXG N5183B Analog 9 kHz to 40 GHz

1x8 RF Mux / 8Ch Amplifier Rubidium clock source

M9362 40GHz 8CH Down Converter

E8267D PSG

M8190A AWG

M9703A 8CH Digitizer

© Keysight Technologies August 2014

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Problems and Solutions Signal Processing

– TDD operation and required calibration methods – Pilot contamination in multi-cell scenario sharing the same pilot – The resources (antenna, users and power) allocation algorithm – Precoding, Tx beamforming and Tx matched filtering for mitigating the multiuser interference – Parameter estimation and detection algorithms – Iterative detection and decoding – Mitigation of RF impairments(Mutual coupling, I/Q imbalance, failures of antenna elements) Algorithmic research using simulator © Keysight Technologies August 2014

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Problems and Solutions

Modeling and Simulation (Acceleration) % 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 © Keysight Technologies August 2014

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Multi-channel real time signal processing August 28, 2014

Keysight EEsof EDA

Motivation – Further extensions of the multiple-antenna and CoMP technologies – The use of Active Antenna Systems (AAS) – Enhanced support for elevation beamforming – Multi-channel real time signal processing requirement for massiveMIMO

© Keysight Technologies August 2014

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Real Time Signal Processing in FPGA RF Front End

BB Processor I

FIR W

Φ

DDC

FIR W

Φ

AD

DDC

FIR W

Φ

AD

DDC

FIR W

Φ

AD

DDC

Q AD

BEAMS

FPGA

∑

SpectraSys RF Modeling SystemVue System Level Simulation

Adaptive Algorithm Complex Weight Wk update

𝑒[𝑘]

Figure 1. Adaptive Digital Beam Forming Signal Processing

• •

−

𝑦[𝑘] ∑

+

𝑑[𝑘]

Hardware implementation for digital down conversion and filtering Adaptive beam forming algorithm to update weighting vector on the fly © Keysight Technologies August 2014

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Integrated Hardware Design Flow for Digitizer MODEL-BASED DESIGN FLOW W1462 FPGA Architect

Continuous top-down verification

W1461

Algorithm/Floating pt

REAL-TIME T&M

W1717

Behavioral Fixed pt Digitizer FPGA Development Kit Integration RTL-level VHDL, Verilog

FPGA M9703A

MODEL-BASED VERIFICATION

New FPGA flow enables Multi-channel GHz-wide tests

Enterprise FPGA Tools HW Implementations

M9703A

Real Time Co-Sim © Keysight Technologies August 2014

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SystemVue + M9703A Modular development ADC

Firmware

RAM ……

Algorithm development

FPGA Abstract IPs HDL level hardware behavior

Abstract layer Gap between hardware design and 1. Mask off hardware detail algorithm 2. provide hardwaredesign transparent

Bus

Driver Bus level hardware behavior

Physical interface

data stream interface

Host abstract APIs

Hardware behavior interface

FPGA algorithm

SystemVue FPGA Host

Data Stream level algorithm design

Host algorithm

Data stream interface

© Keysight Technologies August 2014

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Demo & Discussion Video

© Keysight Technologies August 2014

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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]

© Keysight Technologies August 2014

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Resources • Use the following keywords for • 5G: www.keysight.com/find/5G • SystemVue : www.keysight.com/find/eesof-systemvue • 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

© Keysight Technologies August 2014

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