SystemVue SatComm Webcast Final

Dingqing Lu Sr. Application Specialist Agilent EEsof EDA

Copyright © 2012 Agilent Technologies June 7, 2012 Webcast:

“System-Level Satellite Design & Verification”

Welcome

Daren McClearnon ESL Product Planning Mgr. Agilent EEsof EDA

Agenda

• Overview • Modeling and Simulation • Verification and Testing • Algorithm design • Advanced Systems • Summary

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Satellite Comms PHY Design Challenges 1. I need to develop new SatComm components. How do I get started?

2. How do I verify my SatComm design consistently at all stages of development?

3. How do I measure early SatComm system performance more accurately?

4. How can I reduce the test costs of my System test?

5. How can I get measured waveforms integrated into my simulations?

SYSTEM DESIGN BB Hardware

Design

RF/MW Design

Algorithms, Standards

Test & Measurement

Requirements

Test Plans

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Simulation • Integration capability • Connection to leading RF EDA flows • Performance Evaluation for RF & BB • Advanced Measurement o BER, FER, PER o Sensitivity, Selectivity o Throughput

HW Implementation • Existing Modeling Templates • DSP Algorithm Creation • Fixed Point Simulation • HDL Code Generation • FPGA Synthesis

Open Modeling • Existing Models/Templates • Custom Models : C++,SystemC,.m, HDL • Model Import: MATLAB, ADS, SignalStudio, VSA, STK • Recorded Data

HW Test • Link to VSG/VSA/Scope/LA • Integration/Controlling/Automation • Custom Waveform Generation • Advanced RF & BB Measurements • Parameter Estimation • Troubleshooting

A unifying, system-level approach

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SystemVue • Advanced Dataflow engine • Co-Simulation • Model Libraries • Integration of SW, HW • HDL Simulation • FPGA Implementation

Model more accurately across domains, verify earlier, and continue naturally into test



Agenda


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Satellite Communication Systems

Info Source

Signal Format Modulation

Transmit

Filter

High-Power Amplifier

Transponder Filter

Channel Encode

Info Sink

Signal Format DSP

Demodulation

Receiver Filter TWTA AGC Channel

Decode

BER Measurements

Transmitter

Receiver

Satellite Transponder

Waveform, Spectrum Constellation, EVM

Measurements

Channel

Interferences

Channel Interferences

• Typical satellite communication system

• A Simulation Platform is created including Transmitter, Transponder and Receiver are considered

• System performance is measured

Earth

Earth Transmitting Station

Earth Receiving Station

Satellite

Uplink

Downlink

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Satellite Link Simulation in SystemVue • Framed data with R-S encoded transmitted through the link

• Uplink Frequency: 5.925 to 6.425GHz and Down Link Frequency: 3.7 to 4.2 GHz

• TWTA in Transponder is included

• Received matched with the transmitted data

• Tx and Rx measurements are provided

Modeling a Point to Point Satellite Communication System Satellite Antenna

Earth Station 1

Earth Station 2

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Key Models for SatComm Modulation models

• BPSK, SBPSK, QPSK, OQPSK, 8PSK, pi/4 DQPSK, SOQPSK, Pi/4 CQPSK, MSK, GMFSK, CPM, CPFSK

• FHSS, DSSS FEC – forward error correction

• Convolutional Coding • Turbo Coding • LDPC

Multiple Access Scheme • FDMA • TDMA • CDMA

Satellite Channel Model

Transponder

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Key Modulation Types in Satellite Navigation: DSSS and BOC DSSS: • Data signal is multiplied

by a PRN code (XOR operation for binary signals).

• The result signal has PRN like properties.

BOC: (binary offset carrier) • It is derived by mixing of

the data/code signal and a sub-carrier (a square wave for BOC).

• The “traditional” BPSK spectrum is divided into two parts.



Advanced Applications for Satellite Systems Multiple Access and Broadcasting • Many earth station can access the satellite from different locations using CDMA, SDMA, TDMA, FDMA and OFDMA

Broadcasting • Direct Broadcast Satellite

• DVB-S/DVS-S2

Custom Satellite DSSS (direct-sequence spread spectrum) System • Support Flexible Spreading Code • Support BPSK, QPSK, easy to extend to

other modulation

Satellite Navigation • Galileo: E1/E5

• GPS : L1/L2/L5/L1C/L2C • BeiDou: B1

Satellite Antenna

Multiple Receivers

Multiple Receivers Transmitter

Broadcast

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SystemVue model set – Modulation

• Generic models fit for – Oscillator with phase noise – Transmitter – Tx Filtering

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SystemVue model set – High Power Amplifier • High-Power Amplifier (HPA) • Nonlinearity • Noise Figure

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SystemVue model set – Satellite Channel Model • Channel Model • User Channel Profile

to simulate channel condition • Path loss • Channel Noise • Additional Interferers

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Modeling Satellite RF Components Agilent provides a rich variety of RF modeling choices

Custom RF modeling interfaces – Custom math language .m code (example: Saleh TWTA) – Custom Visual C++ (example: Amplifier DLL with thermal droop, part of a DPD example) – Custom GUI-based (example: Volterra algorithm, such as “DPD_PAModel” in DPD models)

RF Design Flow modeling interfaces (system prediction or system verification)

– Native RF System engine, using RF_LINK (for block level modeling; very fast) – X-parameter devices exported from ADS (for bottom-up verification, IP exchange) – Golden Gate “Fast Circuit Envelope” models (for CMOS transceivers, with memory effects) – Direct co-simulations with ADS,GoldenGate (for highest-accuracy diagnosis & verification)

Measurement-based RF modeling

– Behavioral compressing amp/mixer/osc model from datasheet parameters (P2D, S2P, phase noise, etc) – Measured compressing amp/mixer model (from P2D curve from a PNA-X network analyzer) – X-parameter measurements from a Nonlinear VNA – Digital Pre-Distortion (DPD) – creates a DPD correction network, AND a memory polynomial PA model

that can be used in system simulations.

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SystemVue Satellite Transponder (math language)

• Transponder • Transponder Filter • Template TWTA based

on Saleh’s model • AGC

Inline math model, or direct MATLAB

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Modeling Satellite components using RF_LINK

SystemVue Dataflow

SystemVue Spectrasys

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Modeling Satellite components using Co-simulation

ADS Dataflow/Ckt

SystemVue Dataflow

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Advanced Application: Digital Pre-Distortion for digital satellite TWTA or HPA • TWTAs in satellite systems add severe nonlinear signal distortions. • Higher-order modulation types are more sensitive to nonlinear distortions (tighter constellations) • Therefore there is a tradeoff between power efficiency (i.e. transmitted signal power) and spectral efficiency (e.g. use of M-QAM modulations. M>4) • Several authors have proposed equalization and pre-distortion techniques to overcome nonlinear distortions and intersymbol interference in nonlinear transmission channels • The following scheme is proposed:

Filter DPD Filter Equalization TWTA HPA

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Steps to Achieving Digital Pre-distortion (DPD)

1. Characterize DUT PA using DUT input and output waveforms

2. Calculate complex memory coefficients using QR and SVD algorithms

3. Apply memory polynomial coefficients to construct memory polynomial pre-distorter

4. Pre-distorted signal cancels nonlinear distortion in PA (including major memory effects)

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Theory of Operation – Desired Pout

•Uncorrected PA: Pout vs. Pin curve saturates at Psat (in dBm)

•DPD+PA: Pout-pd vs. Pin curve is linear, up to a higher limit, where Max(Pin) is the maximum correctible input power

Linear Output

Input Power Pin Pin-pd

Output Power

Pout Pout-pd

Desired Output Saturation

Psat

Max Correctable Pin

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5-Step Measurement-Based DPD Modeling Flow

1. Create DPD Stimulus

2. Capture PA Response

3. Extract DPD Model

4. Capture DPD+PA Response

5. Verify DPD+PA Response

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DPD of 1000W TWTA PA w/o RF Feed Forward AM-AM response

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DPD of 1000W TWTA PA w/o RF Feed Forward AM-PM response

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DPD of 1000W TWTA PA w/o RF Feed Forward

ACLR -2BW Lower

-1BW Lower

+1BW Upper

+2BW Upper

PA input 64.05 63.63 63.82 64.26

Raw PA output

46.62 32.52 27.01 44.26

DPD+PA output

49.87 46.61 46.69 50.99

OFDM 10MHz System with QPSK Source：MXG Vector Analyzer：PXA PA output Spectrum(Blue), PA+DPD Spectrum(Red) after one iteration to extract DPD coefficients

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Predictive DPD using Simulation vs. Measurements

External Trigger

Attenuator N5182 MXG

or E8257D PSG as external modulator M9330A AWG if > 100 MHz

89600 VSA

M9392A PXI VSA (>140MHz) or N9030A PXA (<140 MHz)

I,Q RF

RF DUT

SIMULATION-BASED DPD (predictive)

• ADS & GoldenGate Circuits as simulated RF DUTs - Complex loading, memory FX, dynamic behaviors • NVNA X-parameter measurement model, - Great for smaller solid-state devices

X-parameters

RF DUT N5241,2 PNA-X

MEASUREMENT-BASED DPD

CO-SIM, MODELS

CO-SIM, MODELS

MODEL

ADS

GG

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Agenda


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Satellite Communication System Simulation • Test platform is needed for SatComm systems to generate test signals and

measurements • Simulation Emulation Pre-qualification testing • Replace system simulation models with RF hardware component, via the

instrument link “connector”

“Connector” Structure

MXG Sink

VSA Source

VSA MXG

Info Source


Transmit

Filter


Transponder Filter

Channel Encode

Info Sink

Signal Format DSP

Demodulation

RF Receiver TWTA AGC Channel

Decode

BER Measurement

Transmitter

Receiver


Channel

+

+

HW Receiver

Interferences

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Interface to Agilent Instruments – Wideband AWG

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Interface to Agilent Instruments

Capture from Signal Analyzer

– VSA_89600_Source can capture data from MXA, PSA, PXA, Modular M9392, and Infiniuum

– Parameter settings listed in the following table, assuming you know:

• SamplingRate • SignalRange

– Most SV examples provide a VSA

setup file (.setx), to pre-configure the software parameters

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Signal Generation and Measurement

1. SV generates wideband I/Q data, then downloads to M8190A, 81180A, M9330/N6030 AWG

2. Wideband analog test signal formed in M8190A and sent to analog I,Q inputs of PSG signal generator

3. Wideband microwave signals actually test the Analog/RF components 4. The DUT output is captured by a VSA (PXA or Infiniium scope) and

brought back to the PC for analysis using 89600 VSA, or further signal processing using SystemVue.

SystemVue/VSA Wideband PSG DUT Infiniuum 90000 Scope / M9392A VSA M9330/

M8190A

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Satellite Communication System Simulation with HPA working in leaner region

Spectrum, Waveform, Constellations, Phase Error, Mag Error, EVM

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Satellite Communication System Simulation with nonlinear HPA (Output P1dB=10 dBm, TOI=20 dBm)


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Satellite Communication System Simulation with nonlinear HPA (Output P1dB=10 dBm, TOI=20 dBm, and phase noise )


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Agenda


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Algorithm design example: Phase error correction Algorithm implementation and Trade-off analysis

– Replace system models with custom model and run simulation – Compare the performances – Example for phase correction algorithms

Info Source


Transmit

Filter


Transponder Filter

Channel Encode

Info Sink

Signal Format DSP

Demodulation

Receiver Filter TWTA AGC Channel

Decode

BER Measurement

Transmitter

Receiver


Channel Interferences

+

+

Custom .m Algorithm

C++ Model

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Satellite System with Phase Noise • Performance of communication systems with phase noise needs to be

discussed.

• Performance case study shows that system performance degradation is directly related to phase noise random properties.

• To reduce the performance degradation, a phase error correction algorithm is proposed.

• Simulation results show that the algorithm works properly and the system bit error rate (BER) performance can be improved significantly.

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Source Models • To observe how phase noise affects system performances in simulation a

typical communication system model is structured in Figure 1.

• At the receiver input the equivalent baseband received signal can be described as

Baseband Signal

RF Modulator

RF + DSP Receiver Channel

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Phase Noise • Assume that the phase noise is caused by the Oscillator in the RF

modulator.

• As a typical example, the phase noise in (1) is modeled as a color Gaussian noise with a mean value and a power density spectrum

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Ideal Signal without phase noise • Receiver constellation for the system without phase noise

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Ideal Signal with phase noise • Receiver constellation for the system with phase noise

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Ideal Signal with phase and amplitude noise • Receiver constellation for the system with phase and amplitude noise

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Phase Error correction • An algorithm to correct the phase error is proposed for improving the

system performances.

Receiver Filtering

Phase Error Estimation

DSP Receiver

Phase Error Compensation

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Phase Error correction • The phase error correction algorithm de-rotates the constellation.

Phase Error Correction Algorithm

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Phase Error correction • The Constellation is improved as seen in the following figures, in (a) the

averaging signal states are biased from the ideal QPSK constellation in (b) the averaging signal states are aligned with the ideal QPSK constellation.

(a) Before Phase correction (b) After Phase correction

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Phase Error correction • The phase error correction also works for the system with both amplitude

and phase noise. • Below, the Constellation for the system with phase error correction is given

and the phase rotation caused by the phase noise is corrected..

(a) Before Phase correction (b) After Phase correction

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Phase Error correction • BER for the system with both amplitude and phase noise, • With the phase correction, the BER changes from very high to reasonable

BER With Phase Noise

BER With Amplitude and Phase Noise

No Phase Correction

4.8E-1 5.03E-1

With Phase Correction

1.1E-12 2.1e-10

Table 1. BER for the S Band Satellite system with 10 dB of Eb/No for Additive Noise (plus -40 dBm for phase noise)

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Agenda


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Example – DVS-S2 Transmitter

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Example – DVB-S2 Receiver

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Example – DVB-S2 BER test, with ADS Co-sim

ADS

SystemVue

DVB-S PA

DVB-S Source

DVB-S Receiver

LDPC Coder

LDPC Decoder

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Example – DVB-S2 System Results

DUT – DVB PA

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Example – DSSS Satellite Communication

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DSSS QPSK Transmitter: Flexible Spreading Code, Spreading Factor, Chip Rate, Number of samples per Chip

DSSS QPSK Receiver: Timing and Frequency synchronization, Channel estimator and Rake combiner.



Example – DSSS Satellite Communication

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It will be extended to other DSSS system (such as OQPSK, 8-PSK, 16-QAM and etc).



Example – BeiDou B1 Satellite Navigation

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Satellite Navigation is not like Satellite Communication. It’s a message broadcasting system and it adopts DSSS modulation and BOC (Binary Offset Carrier) modulation.



BeiDou B1 Satellite Navigation measurements

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Carrier Freq Tracking

Spreading Code Phase Tracking



Example – Custom OFDM Basic Frame Structure

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:Idle can be turned ON/OFF :Preamble1 can be turned ON/OFF

:Data 1 is mandatory :Data 2 can be turned ON/OFF

:Preamble2 can be turned ON/OFF Preamble (1 and 2) sequence can be set as time-domain sequence or frequency-domain sequence

• There are two kinds of pilots (Pilot1 and Pilot2) supported in Data 1 and Data 2. • Both Pilot1 and Pilot2 can be turned ON/OFF.

Idle Preamble 1 Preamble 2 Data 1 Data 2

OFDM symbol

OFDM symbol

OFDM symbol

OFDM symbol

Block … Block

Block Block …

…

…



Example – Wideband Military Satellite

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The above figure is from Ludong Wang and Jezek B’s paper, “OFDM modulation schemes for military satellite communications”, IEEE MILCOM 2008.



Example – Wideband Military Satellite

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Agenda


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Summary SystemVue provides a platform solution for designing and verification of satellite communication systems

o Modeling integration: SV integrates all SW models in C++, MATLAB code, math language, HDL code, together as a system. Without the integration, each different modeling format makes system-level PHY verification very difficult.

o Test integration: SV integrates test instruments together as a system test tool. Without integration, each HW instrument only provides individual functionality. SystemVue integrates powerful system-level verification suites in software and hardware.

o Unique Value: From functionality point of view Agilent Design-Verification-Test provides unique value in the following areas

Embedded reference transmitters and receivers, to validate your systems earlier Custom waveform generation and integration of user IP, to customize test systems More sophisticated system-level measurements, including closed-loop tests, and tests

of partial systems

Contact Agilent about SystemVue’s “Early Access Program”

to evaluate new SatComm and SatNav capabilities

http://www.agilent.com/find/eesof-systemvue-earlyaccess

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For Additional Information:

SystemVue: www.agilent.com/find/eesof-systemvue

Design Validation: www.agilent.com/find/eesof-systemvue-dvt

Agilent SatComm Resource DVD: www.agilent.com/find/satcomm

At the websites above, • Select Contact an Expert to get further information, or • Contact your local Agilent EEsof EDA sales representative.

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

http://www.agilent.com/find/eesof-systemvue-dvt

http://www.agilent.com/find/satcomm

References

1. S. Benedetto, E. Biglieri, and V. Castellani, " Digital trunsmission theory”, Prentice Hall International, Englewood Cliffs. New Jersey, 1987.

2. D. Lu and K. Yao, "Estimation Variance Bounds of Importance Sampling Simulations in Digital Communication Systems," IEEE Trans. On Communications vol. 39, Oct., 1991, pp 1413-1417.

3. Dingqing Lu, “Quasi-Analytical Method For Estimating low False Alarm Rate,” EuRAD2010, 2010.

4. Dingqing Lu and Zhengrong Zhou, "Integrated Solutions for testing Wireless Communication Systems," IEEE Com Mag, June, 2011

Author’s contact information: [email protected]

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mailto:[email protected]

Jack Sifri MMIC Design Flow Specialist Agilent EEsof EDA

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SystemVue SatComm Webcast Final